diff --git a/src/main/java/object_detection/types/CameraIntrinsics.java b/src/main/java/object_detection/types/CameraIntrinsics.java index b92eb85f7a70e644792c2a4f3cd81b8c8cd73941..8f9550b1644bff0ef80538cff6c2dbcda6178775 100644 --- a/src/main/java/object_detection/types/CameraIntrinsics.java +++ b/src/main/java/object_detection/types/CameraIntrinsics.java @@ -38,6 +38,25 @@ public class CameraIntrinsics { this.K = new DMatrixRMaj(ktemp); } + /* ########## + Getters + ########## */ + public float[] getFocalLength() { + return FocalLength; + } + + public float[] getPrincipalPoint() { + return PrincipalPoint; + } + + public float[] getImageSize() { + return ImageSize; + } + + public DMatrixRMaj getK() { + return K; + } + /* ############### Members ############### */ diff --git a/src/main/java/object_detection/types/CameraPose.java b/src/main/java/object_detection/types/CameraPose.java index 44ad67f7b433d7e8e92217722c36013d346bca3f..47c123c99a7ea52f576f7345e8cf0605863d332a 100644 --- a/src/main/java/object_detection/types/CameraPose.java +++ b/src/main/java/object_detection/types/CameraPose.java @@ -39,6 +39,16 @@ public class CameraPose { }); } + /* ########## + Getters + ########## */ + public DMatrixRMaj getR() { + return R; + } + + public DMatrixRMaj getTranslation() { + return translation; + } /* ################## Members diff --git a/src/test/java/object_detection/BoundingBox2DTests.java b/src/test/java/object_detection/BoundingBox2DTests.java new file mode 100644 index 0000000000000000000000000000000000000000..df79cd5c5837d58ca7b02c39f49ea454793a35b0 --- /dev/null +++ b/src/test/java/object_detection/BoundingBox2DTests.java @@ -0,0 +1,66 @@ +package object_detection; + +import static org.junit.jupiter.api.Assertions.*; +import org.junit.jupiter.api.Test; +import object_detection.types.*; + +class BoundingBox2DTests { + + @Test + void testPointOnEachEdge() { + BoundingBox2D box = new BoundingBox2D(0, 0, 10, 10, "vehicle"); + + // Points on the boundaries of the box + Point2D topEdge = new Point2D(5, 10); + Point2D bottomEdge = new Point2D(5, 0); + Point2D leftEdge = new Point2D(0, 5); + Point2D rightEdge = new Point2D(10, 5); + + assertTrue(box.within(topEdge), "Point on top edge should be within"); + assertTrue(box.within(bottomEdge), "Point on bottom edge should be within"); + assertTrue(box.within(leftEdge), "Point on left edge should be within"); + assertTrue(box.within(rightEdge), "Point on right edge should be within"); + } + + @Test + void testPointsJustOutsideEachEdge() { + BoundingBox2D box = new BoundingBox2D(0, 0, 10, 10, "animal"); + + // Points just outside the boundaries of the box + Point2D leftOfBox = new Point2D(-1, 5); + Point2D rightOfBox = new Point2D(11, 5); + Point2D belowBox = new Point2D(5, -1); + Point2D aboveBox = new Point2D(5, 11); + + assertFalse(box.within(leftOfBox), "Point just left of the bounding box should not be within"); + assertFalse(box.within(rightOfBox), "Point just right of the bounding box should not be within"); + assertFalse(box.within(belowBox), "Point just below the bounding box should not be within"); + assertFalse(box.within(aboveBox), "Point just above the bounding box should not be within"); + } + + @Test + void testZeroWidthHeightBoundingBox() { + BoundingBox2D box = new BoundingBox2D(5, 5, 0, 0, "object"); + + // Points to test + Point2D exactPoint = new Point2D(5, 5); + Point2D nearbyPoint1 = new Point2D(5, 4); + Point2D nearbyPoint2 = new Point2D(6, 5); + + assertTrue(box.within(exactPoint), "Exact point should be within"); + assertFalse(box.within(nearbyPoint1), "Nearby point should not be within"); + assertFalse(box.within(nearbyPoint2), "Nearby point should not be within"); + } + + @Test + void testLargeCoordinates() { + BoundingBox2D box = new BoundingBox2D(0, 0, 10000, 10000, "space"); + + // Points to test + Point2D wellWithin = new Point2D(5000, 5000); + Point2D justOutside = new Point2D(10001, 5000); + + assertTrue(box.within(wellWithin), "Point well within large bounding box should be within"); + assertFalse(box.within(justOutside), "Point just outside large bounding box should not be within"); + } +} diff --git a/src/test/java/object_detection/BoundingBox3DTests.java b/src/test/java/object_detection/BoundingBox3DTests.java new file mode 100644 index 0000000000000000000000000000000000000000..65a389196fa3b23c7569e17b191cd06bc3c8ef6f --- /dev/null +++ b/src/test/java/object_detection/BoundingBox3DTests.java @@ -0,0 +1,46 @@ +package object_detection; + +import static org.junit.jupiter.api.Assertions.*; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.Test; +import object_detection.types.*; + +class BoundingBox3DTests { + + private PointSet ps; + private BoundingBox3D box; + + @BeforeEach + void setUp() { + // Create a PointSet with some sample points + ps = new PointSet( + 1, + "object", + new Point(1.0f, 2.0f, 3.0f), + new Point(4.0f, 5.0f, 6.0f) + ); + + // Initialize a BoundingBox3D with this PointSet + box = new BoundingBox3D(ps); + } + + @Test + void testBoundingBoxCreation() { + assertNotNull(box, "BoundingBox3D should not be null after initialization"); + + // Assuming BoundingBox3D internally manages the given PointSet + assertEquals(ps, getPointSet(box), "BoundingBox3D should contain the same PointSet used during initialization"); + } + + // Helper function to access the PointSet within BoundingBox3D + private PointSet getPointSet(BoundingBox3D box) { + try { + java.lang.reflect.Field field = box.getClass().getDeclaredField("ps"); + field.setAccessible(true); + return (PointSet) field.get(box); + } catch (Exception e) { + fail("Failed to retrieve the PointSet from BoundingBox3D."); + return null; + } + } +} diff --git a/src/test/java/object_detection/BoundingBoxTests.java b/src/test/java/object_detection/BoundingBoxTests.java deleted file mode 100644 index 0242104e6df190f901edb22848f863233c0f7019..0000000000000000000000000000000000000000 --- a/src/test/java/object_detection/BoundingBoxTests.java +++ /dev/null @@ -1,65 +0,0 @@ -package object_detection; - -import static org.junit.jupiter.api.Assertions.*; -import org.junit.jupiter.api.Test; -import object_detection.types.*; - -class BoundingBoxTests { - - @Test - void testPointOnEachEdge() { - Point2D tr = new Point2D(10, 10, 1); - Point2D tl = new Point2D(0, 10, 1); - Point2D br = new Point2D(10, 0, 1); - Point2D bl = new Point2D(0, 0, 1); - BoundingBox box = new BoundingBox(tr, tl, br, bl, 1, "vehicle"); - - // Assume points on the boundary should be considered outside - assertFalse(box.within(new Point2D(5, 10, 1)), "Point on top edge should not be within"); - assertFalse(box.within(new Point2D(5, 0, 1)), "Point on bottom edge should not be within"); - assertFalse(box.within(new Point2D(0, 5, 1)), "Point on left edge should not be within"); - assertFalse(box.within(new Point2D(10, 5, 1)), "Point on right edge should not be within"); - } - - @Test - void testPointsJustOutsideEachEdge() { - Point2D tr = new Point2D(10, 10, 2); - Point2D tl = new Point2D(0, 10, 2); - Point2D br = new Point2D(10, 0, 2); - Point2D bl = new Point2D(0, 0, 2); - BoundingBox box = new BoundingBox(tr, tl, br, bl, 2, "animal"); - - // Test points just outside the bounding box - assertFalse(box.within(new Point2D(-1, 5, 2)), "Point just left of the bounding box"); - assertFalse(box.within(new Point2D(11, 5, 2)), "Point just right of the bounding box"); - assertFalse(box.within(new Point2D(5, -1, 2)), "Point just below the bounding box"); - assertFalse(box.within(new Point2D(5, 11, 2)), "Point just above the bounding box"); - } - - @Test - void testZeroWidthHeightBoundingBox() { - Point2D tr = new Point2D(5, 5, 3); - Point2D tl = new Point2D(5, 5, 3); - Point2D br = new Point2D(5, 5, 3); - Point2D bl = new Point2D(5, 5, 3); - BoundingBox box = new BoundingBox(tr, tl, br, bl, 3, "object"); - - // Test that only the exact point is within - //assertTrue(box.within(new Point2D(5, 5, 3)), "Exact point should be within"); - assertFalse(box.within(new Point2D(5, 4, 3)), "Nearby point should not be within"); - assertFalse(box.within(new Point2D(6, 5, 3)), "Nearby point should not be within"); - } - - @Test - void testLargeCoordinates() { - Point2D br = new Point2D(10000, 10000, 4); - Point2D bl = new Point2D(0, 10000, 4); - Point2D tr = new Point2D(10000, 0, 4); - Point2D tl = new Point2D(0, 0, 4); - BoundingBox box = new BoundingBox(tr, tl, br, bl, 4, "space"); - - // Large coordinates inside the box - assertTrue(box.within(new Point2D(5000, 5000, 4)), "Point well within large bounding box"); - assertFalse(box.within(new Point2D(10001, 5000, 4)), "Point just outside large bounding box"); - } -} diff --git a/src/test/java/object_detection/CameraInstrinsicsTests.java b/src/test/java/object_detection/CameraInstrinsicsTests.java new file mode 100644 index 0000000000000000000000000000000000000000..4e8778ce26c4639350e1829658122e43533dfeb7 --- /dev/null +++ b/src/test/java/object_detection/CameraInstrinsicsTests.java @@ -0,0 +1,49 @@ +package object_detection; + +import static org.junit.jupiter.api.Assertions.*; +import org.junit.jupiter.api.Test; +import object_detection.types.*; + +import java.io.FileWriter; +import java.io.IOException; +import java.io.File; + +class CameraIntrinsicsTests { + + @Test + void testCameraIntrinsicsInitialization() throws IOException { + // Create a temporary configuration file for testing + String tempFilePath = "test_intrinsics.csv"; + try (FileWriter writer = new FileWriter(tempFilePath)) { + writer.write("1000.0,2000.0\n"); // FocalLength + writer.write("500.0,500.0\n"); // PrincipalPoint + writer.write("1280.0,720.0\n"); // ImageSize + writer.write("1.0,0.0,0.0\n"); // K matrix rows + writer.write("0.0,1.0,0.0\n"); + writer.write("0.0,0.0,1.0\n"); + } + + // Create a CameraIntrinsics object + CameraIntrinsics ci = new CameraIntrinsics(tempFilePath); + + // Check its attributes + assertArrayEquals(new float[]{1000.0f, 2000.0f}, ci.getFocalLength(), "FocalLength should be correctly initialized"); + assertArrayEquals(new float[]{500.0f, 500.0f}, ci.getPrincipalPoint(), "PrincipalPoint should be correctly initialized"); + assertArrayEquals(new float[]{1280.0f, 720.0f}, ci.getImageSize(), "ImageSize should be correctly initialized"); + + double[][] expectedK = new double[][]{ + {1.0, 0.0, 0.0}, + {0.0, 1.0, 0.0}, + {0.0, 0.0, 1.0} + }; + for (int i = 0; i < 3; i++) { + for (int j = 0; j < 3; j++) { + assertEquals(expectedK[i][j], ci.getK().get(i, j), 0.01, "K matrix values should match"); + } + } + + // Clean up temporary file + new File(tempFilePath).delete(); + } +} + diff --git a/src/test/java/object_detection/CameraPoseTests.java b/src/test/java/object_detection/CameraPoseTests.java new file mode 100644 index 0000000000000000000000000000000000000000..f950b13c85654600e1889a58bb282413dbf80396 --- /dev/null +++ b/src/test/java/object_detection/CameraPoseTests.java @@ -0,0 +1,50 @@ +package object_detection; + +import org.ejml.data.*; + +import java.io.File; +import static org.junit.jupiter.api.Assertions.*; +import org.junit.jupiter.api.Test; +import object_detection.types.*; + +import java.io.FileWriter; +import java.io.IOException; + +class CameraPoseTests { + + @Test + void testCameraPoseInitialization() throws IOException { + // Create a temporary configuration file for testing + String tempFilePath = "test_pose.csv"; + try (FileWriter writer = new FileWriter(tempFilePath)) { + writer.write("1.0,2.0,3.0\n"); // Translation vector + writer.write("1.0,0.0,0.0\n"); // R matrix rows + writer.write("0.0,1.0,0.0\n"); + writer.write("0.0,0.0,1.0\n"); + } + + // Create a CameraPose object + CameraPose cp = new CameraPose(tempFilePath); + + // Check the translation vector + DMatrixRMaj expectedTranslation = new DMatrixRMaj(new double[]{1.0, 2.0, 3.0}); + assertArrayEquals(expectedTranslation.data, cp.getTranslation().data, "Translation vector should be correctly initialized"); + + // Check the rotation matrix + DMatrixRMaj expectedR = new DMatrixRMaj(new double[][]{ + {1.0, 0.0, 0.0}, + {0.0, 1.0, 0.0}, + {0.0, 0.0, 1.0} + }); + + for (int i = 0; i < 3; i++) { + for (int j = 0; j < 3; j++) { + assertEquals(expectedR.get(i, j), cp.getR().get(i, j), 0.01, "R matrix values should match"); + } + } + + // Clean up temporary file + new File(tempFilePath).delete(); + } +} + diff --git a/src/test/java/object_detection/ObjectSetTests.java b/src/test/java/object_detection/ObjectSetTests.java index c98f08f444ce3ff62b66ff69adaad4f565c73cb5..42261394e886bd86173776764f5dc7ef2266a0c9 100644 --- a/src/test/java/object_detection/ObjectSetTests.java +++ b/src/test/java/object_detection/ObjectSetTests.java @@ -5,41 +5,87 @@ import org.junit.jupiter.api.BeforeEach; import org.junit.jupiter.api.Test; import object_detection.types.*; +import java.io.FileWriter; +import java.io.IOException; +import java.io.FileNotFoundException; +import java.util.Arrays; +import java.util.List; +import java.io.File; +import org.junit.jupiter.api.AfterEach; + class ObjectSetTests { + private CameraIntrinsics intrinsics; + private List pointCloud; private ObjectSet os; @BeforeEach - void setUp() { - os = new ObjectSet(); // Initialize a new ObjectSet for each test + void setUp() throws IOException, FileNotFoundException { + // Create a temporary configuration file for CameraIntrinsics + String tempIntrFile = "test_intr.csv"; + try (FileWriter writer = new FileWriter(tempIntrFile)) { + writer.write("1000.0,2000.0\n"); // FocalLength + writer.write("500.0,500.0\n"); // PrincipalPoint + writer.write("1280.0,720.0\n"); // ImageSize + writer.write("1.0,0.0,0.0\n"); // K matrix rows + writer.write("0.0,1.0,0.0\n"); + writer.write("0.0,0.0,1.0\n"); + } + + // Initialize CameraIntrinsics from the configuration file + intrinsics = new CameraIntrinsics(tempIntrFile); + + // Create a temporary configuration file for CameraPose + String tempPoseFile = "test_pose.csv"; + try (FileWriter writer = new FileWriter(tempPoseFile)) { + writer.write("1.0,2.0,3.0\n"); // Translation vector + writer.write("1.0,0.0,0.0\n"); // R matrix rows + writer.write("0.0,1.0,0.0\n"); + writer.write("0.0,0.0,1.0\n"); + } + + // Initialize a point cloud + pointCloud = Arrays.asList( + new Point(1.0f, 2.0f, 3.0f), + new Point(4.0f, 5.0f, 6.0f), + new Point(7.0f, 8.0f, 9.0f) + ); + + // Initialize a new ObjectSet with intrinsics and a point cloud + os = new ObjectSet(intrinsics, pointCloud); } @Test - void testObjectCreation() { - // Create objects using multiple points - int objId1 = os.makeObject(new Point(1, 2, 3, 1), new Point(4, 5, 6, 2)); - int objId2 = os.makeObject(new Point(7, 8, 9, 3), new Point(10, 11, 12, 4)); - - assertEquals(2, os.objects.size(), "There should be two objects in the set after addition."); - assertNotNull(os.objects.get(objId1), "The object with objId1 should not be null."); - assertNotNull(os.objects.get(objId2), "The object with objId2 should not be null."); + void testObjectSetCreation() throws IOException, FileNotFoundException { + assertNotNull(os, "ObjectSet should not be null after initialization"); + assertNotNull(os.objects, "ObjectSet should have a list of objects"); + assertTrue(os.objects.isEmpty(), "Initially, ObjectSet should be empty"); } @Test - void testObjectComparisonAndCombination() { - // Create two objects that should be similar enough to be considered the same - int objId1 = os.makeObject(new Point(0, 0, 0, 1)); - int objId2 = os.makeObject(new Point(0, 0, 0, 2)); + void testReconcileCandidate() { + // Create a candidate PointSet + PointSet candidate = new PointSet(1, "object", + new Point(1.0f, 2.0f, 3.0f), + new Point(4.0f, 5.0f, 6.0f) + ); - assertTrue(os.compareObjects(objId1, objId2), "Identical objects should be considered the same."); + os.reconcileCandidate(candidate, 0.5); - // Now combine these objects into one - os.combineObjects(objId1, objId2); - assertEquals(1, os.objects.size(), "There should be one object left after combining."); + assertEquals(1, os.objects.size(), "One object should be added or reconciled"); } @Test - void testEmptyObjectSetCreation() { - assertTrue(os.objects.isEmpty(), "Newly created ObjectSet should be empty."); + void testToString() { + assertEquals("ObjectSet of : 0 objects:", os.toString(), "Initial string representation should match expected format"); + + // Add an object and check the string representation again + os.reconcileCandidate(new PointSet(1, "vehicle", new Point(1.0f, 2.0f, 3.0f)), 0.5); + assertTrue(os.toString().startsWith("ObjectSet of : 1 objects:"), "String representation should reflect the new object count"); + } + @AfterEach + void tearDown() { + new File("test_intr.csv").delete(); // Clean up intrinsics file + new File("test_pose.csv").delete(); // Ensure to delete pose file if it wasn't cleaned up earlier } } diff --git a/src/test/java/object_detection/Point2DTests.java b/src/test/java/object_detection/Point2DTests.java new file mode 100644 index 0000000000000000000000000000000000000000..c30d075ba78d11ebeeee5e13fdf2842906755359 --- /dev/null +++ b/src/test/java/object_detection/Point2DTests.java @@ -0,0 +1,37 @@ +package object_detection; + +import static org.junit.jupiter.api.Assertions.*; +import org.junit.jupiter.api.Test; +import object_detection.types.*; + +class Point2DTests { + + @Test + void testPoint2DCreation() { + Point2D point = new Point2D(3.5f, 7.2f); + + assertEquals(3.5f, point.getX(), "X coordinate should match the constructor input"); + assertEquals(7.2f, point.getY(), "Y coordinate should match the constructor input"); + } + + @Test + void testToString() { + Point2D point = new Point2D(3.5f, 7.2f); + String expectedString = "{3.5, 7.2}"; + + assertEquals(expectedString, point.toString(), "toString should correctly represent the Point2D"); + } + + @Test + void testMultiplePoints() { + Point2D point1 = new Point2D(1.0f, 2.0f); + Point2D point2 = new Point2D(3.0f, 4.0f); + + assertEquals(1.0f, point1.getX(), "Point1's X coordinate should match the constructor input"); + assertEquals(2.0f, point1.getY(), "Point1's Y coordinate should match the constructor input"); + + assertEquals(3.0f, point2.getX(), "Point2's X coordinate should match the constructor input"); + assertEquals(4.0f, point2.getY(), "Point2's Y coordinate should match the constructor input"); + } +} + diff --git a/src/test/java/object_detection/PointSetTests.java b/src/test/java/object_detection/PointSetTests.java new file mode 100644 index 0000000000000000000000000000000000000000..395e8c80a37d386e0b1caf9e2091b85892ce5f73 --- /dev/null +++ b/src/test/java/object_detection/PointSetTests.java @@ -0,0 +1,51 @@ +package object_detection; + +import static org.junit.jupiter.api.Assertions.*; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.Test; +import object_detection.types.*; + +class PointSetTests { + + private PointSet ps; + + @BeforeEach + void setUp() { + ps = new PointSet(1, "vehicle", new Point(1.0f, 2.0f, 3.0f), new Point(4.0f, 5.0f, 6.0f)); // Initialize a PointSet with a sample ID, prediction name, and points + } + + @Test + void testPointSetCreation() { + Point[] points = ps.getPoints(); + + assertEquals(2, points.length, "PointSet should contain two points initially"); + + assertEquals(1.0f, points[0].getX(), 0.001, "First point's X coordinate should match"); + assertEquals(2.0f, points[0].getY(), 0.001, "First point's Y coordinate should match"); + assertEquals(3.0f, points[0].getZ(), 0.001, "First point's Z coordinate should match"); + + assertEquals(4.0f, points[1].getX(), 0.001, "Second point's X coordinate should match"); + assertEquals(5.0f, points[1].getY(), 0.001, "Second point's Y coordinate should match"); + assertEquals(6.0f, points[1].getZ(), 0.001, "Second point's Z coordinate should match"); + + assertEquals("vehicle", ps.getPred(), "Prediction name should be 'vehicle'"); + } + + @Test + void testAddPoint() { + Point newPoint = new Point(7.0f, 8.0f, 9.0f); + ps.addPoint(newPoint); + + Point[] points = ps.getPoints(); + + assertEquals(3, points.length, "PointSet should contain three points after addition"); + assertEquals(7.0f, points[2].getX(), 0.001, "Third point's X coordinate should match"); + assertEquals(8.0f, points[2].getY(), 0.001, "Third point's Y coordinate should match"); + assertEquals(9.0f, points[2].getZ(), 0.001, "Third point's Z coordinate should match"); + } + + @Test + void testGetIDX() { + assertEquals(1, ps.getIDX(), "IDX should be 1 as specified during creation"); + } +} diff --git a/src/test/java/object_detection/PointTests.java b/src/test/java/object_detection/PointTests.java index 1a1c2b32402350e31f45180aee58b32ece993eb8..25a4b1d171f2eb4bae6fae52e81ea221e3db343b 100644 --- a/src/test/java/object_detection/PointTests.java +++ b/src/test/java/object_detection/PointTests.java @@ -9,39 +9,51 @@ class PointTests { @Test void testPointCreation() { // Test the creation of a Point object - Point point = new Point(1.0f, 2.0f, 3.0f, 0); + Point point = new Point(1.0f, 2.0f, 3.0f); assertNotNull(point, "Point object should not be null"); assertEquals(1.0f, point.getX(), "X coordinate should match the constructor input"); assertEquals(2.0f, point.getY(), "Y coordinate should match the constructor input"); assertEquals(3.0f, point.getZ(), "Z coordinate should match the constructor input"); } + @Test + void testPointCreationWithColor() { + // Test the creation of a Point object with color attributes + Point point = new Point(1.0f, 2.0f, 3.0f, 255, 0, 0); + int[] color = point.getColor(); + + assertNotNull(point, "Point object should not be null"); + assertEquals(1.0f, point.getX(), "X coordinate should match the constructor input"); + assertEquals(2.0f, point.getY(), "Y coordinate should match the constructor input"); + assertEquals(3.0f, point.getZ(), "Z coordinate should match the constructor input"); + + assertArrayEquals(new int[]{255, 0, 0}, color, "Color should match the constructor input"); + } + @Test void testPointEquality() { // Test the equality method under two scenarios - Point p1 = new Point(1.005f, 2.005f, 3.005f, 0); - Point p2 = new Point(1.006f, 2.006f, 3.006f, 0); - Point p3 = new Point(1.007f, 2.007f, 3.007f, 0); + Point p1 = new Point(1.005f, 2.005f, 3.005f); + Point p2 = new Point(1.006f, 2.006f, 3.006f); assertTrue(Point.equals(p1, p2, 0.01f), "Points p1 and p2 should be considered equal with a tolerance of 0.01"); - //assertFalse(Point.equals(p1, p2, 0.0001f), "Points p1 and p2 should not be considered equal with a tolerance of 0.0001"); - assertTrue(Point.equals(p1, p3, 0.01f), "Points p1 and p3 should be considered equal with a tolerance of 0.01"); - //assertFalse(Point.equals(p1, p3, 0.0001f), "Points p1 and p3 should not be considered equal with a tolerance of 0.0001"); + assertFalse(Point.equals(p1, p2, 0.001f), "Points p1 and p2 should not be considered equal with a tolerance of 0.001"); } @Test - void testPointPrecisionEquality() { + void testPrecisionEquality() { // Test precision issues and rounding errors - Point p1 = new Point(0.0000001f, 0.0000001f, 0.0000001f, 0); - Point p2 = new Point(0.0000002f, 0.0000002f, 0.0000002f, 0); - //assertFalse(Point.equals(p1, p2, 0.00000001f), "Points p1 and p2 should not be considered equal with a tolerance of 0.00000001"); + Point p1 = new Point(0.0000001f, 0.0000001f, 0.0000001f); + Point p2 = new Point(0.0000002f, 0.0000002f, 0.0000002f); + + assertFalse(Point.equals(p1, p2, 0.00000001f), "Points p1 and p2 should not be considered equal with a tolerance of 0.00000001"); } @Test void testNegativeCoordinates() { // Test points with negative coordinates to ensure that equality checks are not biased by sign - Point p1 = new Point(-1.005f, -2.005f, -3.005f, 0); - Point p2 = new Point(-1.005f, -2.005f, -3.005f, 0); + Point p1 = new Point(-1.005f, -2.005f, -3.005f); + Point p2 = new Point(-1.005f, -2.005f, -3.005f); assertTrue(Point.equals(p1, p2, 0.01f), "Negative coordinate points should be considered equal"); } @@ -49,8 +61,8 @@ class PointTests { @Test void testZeroCoordinates() { // Test points with all coordinates set to zero - Point p1 = new Point(0.0f, 0.0f, 0.0f, 0); - Point p2 = new Point(0.0f, 0.0f, 0.0f, 0); + Point p1 = new Point(0.0f, 0.0f, 0.0f); + Point p2 = new Point(0.0f, 0.0f, 0.0f); assertTrue(Point.equals(p1, p2, 0.0001f), "Zero coordinate points should be exactly equal"); } @@ -58,9 +70,26 @@ class PointTests { @Test void testDistinctPoints() { // Test distinct points that should not be equal - Point p1 = new Point(1.000f, 1.000f, 1.000f, 0); - Point p2 = new Point(2.000f, 2.000f, 2.000f, 0); + Point p1 = new Point(1.000f, 1.000f, 1.000f); + Point p2 = new Point(2.000f, 2.000f, 2.000f); + + assertFalse(Point.equals(p1, p2, 0.001f), "Distinct points should not be considered equal"); + } + + @Test + void testToString() { + // Test the toString method of the Point class + Point point = new Point(1.0f, 2.0f, 3.0f); + assertEquals("Point(1.0 ,2.0 ,3.0)", point.toString(), "String representation should match expected format"); + } - //assertFalse(Point.equals(p1, p2, 0.001f), "Distinct points should not be considered equal"); + @Test + void testHashCode() { + // Test the hash code generation for the Point class + Point p1 = new Point(1.0f, 2.0f, 3.0f); + Point p2 = new Point(1.0f, 2.0f, 3.0f); + + assertEquals(p1.hashCode(), p2.hashCode(), "Hash codes should be identical for points with identical coordinates"); } } + diff --git a/target/classes/.DS_Store b/target/classes/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..126c679b58893cbc25f95559ddb8efe7b9a9d6dd Binary files /dev/null and b/target/classes/.DS_Store differ diff --git a/target/classes/README.md b/target/classes/README.md new file mode 100644 index 0000000000000000000000000000000000000000..c93df4abbe8779abb9ad11834d608762c273d314 --- /dev/null +++ b/target/classes/README.md @@ -0,0 +1,15 @@ + +# Entry into System + +Things that are true: +1. A student should be able to build the system, then press run, then open a localhost and see the video and the point cloud of each object +2. A student should also be able to choose between different object and get information (need interactive display) +3. The entry needs to do the entire workflow + - get keyframes and featurepoints + - get objects from keyframes + - start object detection + - finish object detection and update database + - ping GUI server + - GUI server pulls information and displays point cloud to user + +TODO: function to process each frame within the ObjectSet \ No newline at end of file diff --git a/target/classes/application.properties b/target/classes/application.properties new file mode 100644 index 0000000000000000000000000000000000000000..46bdbc7319f29388ce78d09d61617fccaf719818 --- /dev/null +++ b/target/classes/application.properties @@ -0,0 +1,3 @@ +server.port = 5555 +logging.level.org.springframework=OFF +logging.level.root=OFF \ No newline at end of file diff --git a/target/classes/database/MongoDBInteraction.class b/target/classes/database/MongoDBInteraction.class new file mode 100644 index 0000000000000000000000000000000000000000..874eee73353f3caf1a22d1e95c7f15feda500cc0 Binary files /dev/null and b/target/classes/database/MongoDBInteraction.class differ diff --git a/target/classes/object_detection/.DS_Store b/target/classes/object_detection/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..aff5713ce0a01c7592b2fac9d9fad1c285ba7641 Binary files /dev/null and b/target/classes/object_detection/.DS_Store differ diff --git a/target/classes/object_detection/Downsampler.class b/target/classes/object_detection/Downsampler.class new file mode 100644 index 0000000000000000000000000000000000000000..4e87d39bd91ff4a077f03c3c3a105e9adc2e0cbd Binary files /dev/null and b/target/classes/object_detection/Downsampler.class differ diff --git a/target/classes/object_detection/ObjectDetector.class b/target/classes/object_detection/ObjectDetector.class new file mode 100644 index 0000000000000000000000000000000000000000..4172fca99d7c58c533ebb4d7d3fc1f476c2e1d86 Binary files /dev/null and b/target/classes/object_detection/ObjectDetector.class differ diff --git a/target/classes/object_detection/layout.md b/target/classes/object_detection/layout.md new file mode 100644 index 0000000000000000000000000000000000000000..16ebc3523eb6e7b7f2264393d8d91f92bac9f7ba --- /dev/null +++ b/target/classes/object_detection/layout.md @@ -0,0 +1,30 @@ + + +Input to System: +- pointcloud +- keyframes: + - camera angles (x,y,z + angle ?) + - 2D points captured + - YOLO-captured bounding boxes + +1) Take pointcloud, and downsample +2) For each frame: + a. project downsampled pointcloud onto frame + b. overlay 2D bounding boxes from YOLO + c. create candidate objects based on points falling within boxes + d. do overlap combinations based on thresholding voxels +3) Given final objectset, transmit corners to GUI +4) Display corners over original downsampled pointcloud to show objects + + +Output of System: +- pointcloud +- 3D bounding box of objects + + + +Projecting 3D points onto 2D screen based on camera pose: +1) Calculate camera matrix = K * [R, t'] where R is rotation matrix, t is translation vector, and K is intrinsic of camera pose +2) Get projection by appling projPoints = [point, 1] * cameraMatrix' +3) Divide projPoints[1:2] by projPoints[3] (i.e. divide x and y coordinates by z) +4) Return projPoints if z > 0 (infront of camera), or x,y fall into size of image (0-ImageSize.x, 0-ImageSize.y) \ No newline at end of file diff --git a/target/classes/object_detection/types/BoundingBox2D.class b/target/classes/object_detection/types/BoundingBox2D.class new file mode 100644 index 0000000000000000000000000000000000000000..1416df28631dc1c808ca26722452863608c13e7e Binary files /dev/null and b/target/classes/object_detection/types/BoundingBox2D.class differ diff --git a/target/classes/object_detection/types/BoundingBox3D.class b/target/classes/object_detection/types/BoundingBox3D.class new file mode 100644 index 0000000000000000000000000000000000000000..9747fab3112805f5c85b4186ba4b116513f16e8c Binary files /dev/null and b/target/classes/object_detection/types/BoundingBox3D.class differ diff --git a/target/classes/object_detection/types/CameraIntrinsics.class b/target/classes/object_detection/types/CameraIntrinsics.class new file mode 100644 index 0000000000000000000000000000000000000000..8b4558190ecefa1db3912281621c4800718c5be6 Binary files /dev/null and b/target/classes/object_detection/types/CameraIntrinsics.class differ diff --git a/target/classes/object_detection/types/CameraPose.class b/target/classes/object_detection/types/CameraPose.class new file mode 100644 index 0000000000000000000000000000000000000000..d102f73c6dc1dadc3731300c4cb78b023881e507 Binary files /dev/null and b/target/classes/object_detection/types/CameraPose.class differ diff --git a/target/classes/object_detection/types/Frame.class b/target/classes/object_detection/types/Frame.class new file mode 100644 index 0000000000000000000000000000000000000000..437cb66f95c3425ea084877cd1fb766b558a3f03 Binary files /dev/null and b/target/classes/object_detection/types/Frame.class differ diff --git a/target/classes/object_detection/types/ObjectSet.class b/target/classes/object_detection/types/ObjectSet.class new file mode 100644 index 0000000000000000000000000000000000000000..67a9c2b84d9dcce795586e9c7f0cf6e3a55d4df8 Binary files /dev/null and b/target/classes/object_detection/types/ObjectSet.class differ diff --git a/target/classes/object_detection/types/Point.class b/target/classes/object_detection/types/Point.class new file mode 100644 index 0000000000000000000000000000000000000000..cd48191aba342a8453e3d6e2289d9a912c0ed125 Binary files /dev/null and b/target/classes/object_detection/types/Point.class differ diff --git a/target/classes/object_detection/types/Point2D.class b/target/classes/object_detection/types/Point2D.class new file mode 100644 index 0000000000000000000000000000000000000000..cd4cfb7dfe1d7aac29fbcd741135e76e4056d737 Binary files /dev/null and b/target/classes/object_detection/types/Point2D.class differ diff --git a/target/classes/object_detection/types/PointSet.class b/target/classes/object_detection/types/PointSet.class new file mode 100644 index 0000000000000000000000000000000000000000..bdb368791ce44390baed9d451d486bfe3e866c4a Binary files /dev/null and b/target/classes/object_detection/types/PointSet.class differ diff --git a/target/classes/templates/html/index.html b/target/classes/templates/html/index.html new file mode 100644 index 0000000000000000000000000000000000000000..d0e8b4e66a060b7a41319a9d38a5c2f057f8ed31 --- /dev/null +++ b/target/classes/templates/html/index.html @@ -0,0 +1,55 @@ + + + + + + VSlam + + + + + + + + + +

Integrating RGBD-VSLAM with Object Detection and Tracking

+

Visual Simultaneous Localization and Mapping (VSLAM) is the process of taking camera feed, as well as its position, and building a map of the current local world, specifically using visual input. This project uses this process, and builds upon it by also tracking objects within a frame. In this comes two problems: object detection, and then subsequent mapping and tracking of objects within a 3D space. For more information go here

+

These are the steps to this process:

+
    +
  1. Taking a video source as input, start the VSLAM algorithm to iteratively build a worldmap
    2. +
  2. Save the finalized and error-corrected worldmap, as well as the camera position for each important frame
    3. +
  3. Use YOLOv4 ConvNet on each frame, a model that returns 2D bounding boxes around objects found within an image
    4. +
  4. Project the 3D points collected from VSLAM onto each frame
    5. +
  5. For each 2D bounding box, create a potential object containing all 3D points that are projected within its bounds
    6. +
  6. Check if there is overlap in this set of points when comparing to past objects from other frames
    7. +
  7. Given sufficient overlap, combine these objects using intersection on the points
    8. +
+ +

Given some video of an environment, the output of this algorithm is essentially 3D groupings of points that correspond to objects within that environment.

+ +

Select a dataset from the dropdown below. It will take some time to process the dataset.

+ + + +
+
+
Select An Object To View Point Cloud With That Object Highlighted
+
+ +
+
+ +
+ + + + + + + + diff --git a/target/classes/templates/js/app.js b/target/classes/templates/js/app.js new file mode 100644 index 0000000000000000000000000000000000000000..2ac1825de39da991bfba1b760d4678512b9a04f1 --- /dev/null +++ b/target/classes/templates/js/app.js @@ -0,0 +1,71 @@ +async function fetchImageAndObjects() { + try { + const response = await fetch('http://127.0.0.1:5555/api/getObjects'); + if (!response.ok) { + throw new Error('Failed to fetch image and objects'); + } + const data = await response.json(); + + displayImageAndObjects(data.objects); + } catch (error) { + console.error(error); + } +} + +function displayImageAndObjects(objects) { + const objectsContainer = document.getElementById('objectsContainer'); + const container = document.getElementById('resultContainer'); + + // Create a list for objects + const objectsList = document.createElement('ul'); + objects.forEach(object => { + const objectButton = document.createElement('button'); + objectButton.textContent = object; + // Add event listener to each button + objectButton.addEventListener('click', () => { + // You can define what happens when the button is clicked + drawPointCloud(object); + }); + const objectItem = document.createElement('li'); + objectItem.appendChild(objectButton); + objectsList.appendChild(objectItem); + }); + + // Append objects list to the objects container + objectsContainer.appendChild(objectsList); + + container.style.visibility = "visible"; +} + + +// selecting loading div +const loader = document.querySelector("#loading"); + +// showing loading +function displayLoading() { + loader.classList.add("display"); +} + +// hiding loading +function hideLoading() { + loader.classList.remove("display"); +} + +async function startWorkflow(){ + const startButton = document.getElementById("process"); + startButton.style.display = "none"; + displayLoading(); + try { + const response = await fetch('http://127.0.0.1:5555/runProcess'); + if (!response.ok) { + throw new Error('Failed to fetch image and objects'); + } + const data = await response; + console.log(data); + hideLoading(); + } catch (error) { + console.error(error); + } + fetchImageAndObjects(); + +} diff --git a/target/classes/templates/js/buildPC.js b/target/classes/templates/js/buildPC.js new file mode 100644 index 0000000000000000000000000000000000000000..154ff9dad10c8a118535c9935cfe328cf7d29629 --- /dev/null +++ b/target/classes/templates/js/buildPC.js @@ -0,0 +1,123 @@ +var renderForm = document.getElementById("render_form"); +renderForm.addEventListener("change", render); + +// selecting loading div +const loader = document.getElementById("loading"); +hideLoading(); + +var objectSet = [] +var traces = [] +var meshes = [] +var highlighted = false; + +async function render(event) { + + var dataset_name = renderForm.value; + Plotly.purge('myDiv'); + objectSet = []; + traces = []; + meshes = []; + highlighted = false; + + // start loading + displayLoading(); + console.log("Start"); + d3.json(`http://127.0.0.1:5555/api/getObjects?dataset=${dataset_name}`, function(data){ + console.log(data); + objectSet = data; + + // build object list + var i = 0; + const container = document.getElementById('resultContainer') + const objectList = document.getElementById('objectList'); + objectSet['objects'].forEach(object => { + + // create a button for that object, and store the index of the trace + const objectButton = document.createElement('button'); + //objectButton.textContent = String(i); // text will be the index of the object + objectButton.textContent = object["predName"]; // text will be the index of the object + objectButton.setAttribute("idx", i); + objectButton.title = "Object " + String(i); + objectButton.className = "myBtn"; + + // Add event listener to each button + objectButton.addEventListener('click', () => { + // remove all meshes from graph, and add current + if(highlighted != false){ + Plotly.deleteTraces('myDiv', [-1]); + } + else{ + highlighted = true; + } + + // get index of current mesh + var i = objectButton.getAttribute("idx"); + Plotly.addTraces('myDiv', [meshes[i]]); + }); + + objectList.appendChild(objectButton); + objectList.style.visibility = "visible"; + container.style.visibility = "visible"; + + // create trace + var currTrac = { + x: object['points'].map((x) => x['x']), + y: object['points'].map((x) => x['y']), + z: object['points'].map((x) => x['z']), + type: 'scatter3d', + mode: 'markers', + marker: { + color: object['points'].map((x) => 'rgb(' + x['R'] + ', ' + x['G'] + ', ' + x['B'] + ')'), + size: 3, + width: 0.2 + } + } + + // create mesh + var currMesh = { + alphahull: 0, + opacity: 0.9, + type: 'mesh3d', + x: object['points'].map((x) => x['x']), + y: object['points'].map((x) => x['y']), + z: object['points'].map((x) => x['z']) + } + + // add object and mesh to lists + traces.push(currTrac); + meshes.push(currMesh); + + i++; + }); + + + var layout = { + margin: { + l: 0, + r: 0, + b: 0, + t: 0 + }, + showlegend: false + }; + + Plotly.newPlot('myDiv', traces, layout); + + // finish loading + hideLoading(); + }); + +} + + + +// showing loading +function displayLoading() { + loader.style.visibility = "visible"; + console.log("HERE"); +} + +// hiding loading +function hideLoading() { + loader.style.visibility = "hidden"; +} diff --git a/target/classes/templates/js/pointCloud.js b/target/classes/templates/js/pointCloud.js new file mode 100644 index 0000000000000000000000000000000000000000..205af4b79c4f2681e1cfde4610f564cf2f5c8f99 --- /dev/null +++ b/target/classes/templates/js/pointCloud.js @@ -0,0 +1,140 @@ + +async function drawPointCloud(object) { + await fetch('http://127.0.0.1:5555/getJSON') + .then(response => response.json()) + .then(responseText => { + let pointCloudData = parseJSONToPointCloud(responseText, object); + + // Use three.js to render the point cloud + let scene = new THREE.Scene(); + let camera = new THREE.PerspectiveCamera(75, window.innerWidth / window.innerHeight, 0.1, 1000); + let renderer = new THREE.WebGLRenderer(); + renderer.setSize(window.innerWidth, window.innerHeight); + document.body.appendChild(renderer.domElement); + + // Create a buffer geometry and add the point cloud data + let geometry = new THREE.BufferGeometry(); + geometry.setAttribute('position', new THREE.Float32BufferAttribute(new Float32Array(pointCloudData.positions), 3)); + geometry.setAttribute('color', new THREE.Float32BufferAttribute(new Float32Array(pointCloudData.colors), 3)); + + let material = new THREE.PointsMaterial({ vertexColors: true, size: 0.005 }); + + let pointCloud = new THREE.Points(geometry, material); + scene.add(pointCloud); + + camera.position.z = 2; + + let angleX = 0; + let angleY = 0; + + // Handle user interaction for rotation + let isDragging = false; + let previousMousePosition = { + x: 0, + y: 0 + }; + + // Add event listeners to renderer's DOM element + renderer.domElement.addEventListener("mousedown", (event) => { + isDragging = true; + previousMousePosition = { + x: event.clientX, + y: event.clientY + }; + }); + + renderer.domElement.addEventListener("mousemove", (event) => { + if (isDragging) { + let deltaX = event.clientX - previousMousePosition.x; + let deltaY = event.clientY - previousMousePosition.y; + + angleY += deltaX * 0.01; + angleX += deltaY * 0.01; + + pointCloud.rotation.y = angleY; + pointCloud.rotation.x = angleX; + + previousMousePosition = { + x: event.clientX, + y: event.clientY + }; + + renderer.render(scene, camera); + } + }); + + renderer.domElement.addEventListener("mouseup", () => { + isDragging = false; + }); + + let zoomFactor = 1; // Initial zoom level + + const zoomSensitivity = 0.01; // Adjust zoom sensitivity as needed + + renderer.domElement.addEventListener("wheel", (event) => { + event.preventDefault(); + + zoomFactor += event.deltaY * zoomSensitivity; + zoomFactor = Math.max(0.1, zoomFactor); // Enforce minimum zoom level + camera.position.z = camera.initialPosition.z / zoomFactor; + renderer.render(scene, camera); + }); + + camera.initialPosition = { z: camera.position.z }; // Store initial position + + function animate() { + requestAnimationFrame(animate); + renderer.render(scene, camera); + } + + animate(); + + function parseJSONToPointCloud(jsonObject, target) { + // Initialize point cloud data + let positions = []; + let colors = []; + + // Check if the object name exists in the JSON + if (target in jsonObject || target == null) { + + for (let objectKey in jsonObject) { + let object = jsonObject[objectKey]['pset']; + + // Loop through each coordinate in the object + for (let i = 0; i < object.length; i++) { + let coordinate = object[i]; + + // Extract x, y, z values + let x = coordinate['x']; + let y = coordinate['y']; + let z = coordinate['z']; + let r,g,b; + + if(objectKey == target){ + console.log(target); + r = 1; // Red component + g = 0; // Green component + b = 0; // Blue component + } else { + r = 1; + g = 1; + b = 1; + } + + // Push to positions list + positions.push(x, y, z ); + colors.push(r,g,b); + } + } + + } else { + console.error(`Object '${object}' not found in JSON.`); + } + + return { positions: positions, colors: colors }; + } + }) + .catch(error => { + console.error('Error loading JSON:', error); + }); +} \ No newline at end of file diff --git a/target/classes/templates/style/main.css b/target/classes/templates/style/main.css new file mode 100644 index 0000000000000000000000000000000000000000..de91d596830b8c66e2e1ea2eb9ca01e5a3143592 --- /dev/null +++ b/target/classes/templates/style/main.css @@ -0,0 +1,93 @@ +html { + height: 100%; +} + +canvas { + display: flex; +} + +h1 { + margin-top: 70px; +} + +body { + margin-left: 20%; + margin-right: 20%; +} + +.myBtn { + height:25px; + margin: 5px; + width: fit-content; +} + +#resultContainer { + visibility: hidden; + display: inline; +} + +#objectList { + margin-top: 20px; + visibility: hidden; + display:flex; + flex-wrap: wrap; + flex-direction: row; + justify-content: center; +} + +.container { + display: flex; + justify-content: space-between; +} + +.image-container { + flex: 1; + margin-right: 20px; +} + +#myDiv { + display: flex !important; + justify-content: center !important; + padding-bottom: 100px; + margin-bottom: 100px; +} + + +img { + max-width: 100%; + height: auto; +} + +ul { + list-style-type: none; + padding-left: 0; +} + +li { + margin-bottom: 5px; +} + +/* creating css loader */ + +#loading { + margin: 20px auto auto; + width: 2rem; + height: 2rem; + border: 5px solid #f3f3f3; + border-top: 6px solid #9c41f2; + border-radius: 100%; + animation: spin 1s infinite linear; +} + + +@keyframes spin { + from { + transform: rotate(0deg); + } + to { + transform: rotate(360deg); + } +} + + + diff --git a/target/classes/top/BackendJava$BackendService.class b/target/classes/top/BackendJava$BackendService.class new file mode 100644 index 0000000000000000000000000000000000000000..815eba5392245ca4c8fa22e7d393dc99675e4398 Binary files /dev/null and b/target/classes/top/BackendJava$BackendService.class differ diff --git a/target/classes/top/BackendJava$ObjectSetController.class b/target/classes/top/BackendJava$ObjectSetController.class new file mode 100644 index 0000000000000000000000000000000000000000..274fc4ea0059bf6e13f5a123ecb0a17f44495f0d Binary files /dev/null and b/target/classes/top/BackendJava$ObjectSetController.class differ diff --git a/target/classes/top/BackendJava$WebMvcConfig.class b/target/classes/top/BackendJava$WebMvcConfig.class new file mode 100644 index 0000000000000000000000000000000000000000..42ea8561593e9962638743672f94ec24ea1bf7c4 Binary files /dev/null and b/target/classes/top/BackendJava$WebMvcConfig.class differ diff --git a/target/classes/top/BackendJava.class b/target/classes/top/BackendJava.class new file mode 100644 index 0000000000000000000000000000000000000000..ae8ab9c2c89421170e7c8859295894d834b3f42f Binary files /dev/null and b/target/classes/top/BackendJava.class differ diff --git a/target/classes/vid2frames/.DS_Store b/target/classes/vid2frames/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..d89c2ebd6e71812c2a8943429f83ac719db3fc39 Binary files /dev/null and b/target/classes/vid2frames/.DS_Store differ diff --git a/target/classes/vid2frames/Vid2Frames.class b/target/classes/vid2frames/Vid2Frames.class new file mode 100644 index 0000000000000000000000000000000000000000..85698353f85bd4b21933884b00d4bfce78a7a0d7 Binary files /dev/null and b/target/classes/vid2frames/Vid2Frames.class differ diff --git a/target/classes/vid2frames/input_video.mov b/target/classes/vid2frames/input_video.mov new file mode 100644 index 0000000000000000000000000000000000000000..569829b969d88d0e9ab159972297ca8222a6382f Binary files /dev/null and b/target/classes/vid2frames/input_video.mov differ diff --git a/target/classes/vslam/.DS_Store b/target/classes/vslam/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..19a7d37d9b41f17c2d7dcf2d9ae54922454c080f Binary files /dev/null and b/target/classes/vslam/.DS_Store differ diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/MonocularVisualSimultaneousLocalizationAndMappingExample.mlx b/target/classes/vslam/Mathworks_VSLAM_Example/MonocularVisualSimultaneousLocalizationAndMappingExample.mlx new file mode 100644 index 0000000000000000000000000000000000000000..25864978c4c3f4e433ddf9052b55627daaede5c4 Binary files /dev/null and b/target/classes/vslam/Mathworks_VSLAM_Example/MonocularVisualSimultaneousLocalizationAndMappingExample.mlx differ diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/bagOfFeaturesDataSLAM.mat b/target/classes/vslam/Mathworks_VSLAM_Example/bagOfFeaturesDataSLAM.mat new file mode 100644 index 0000000000000000000000000000000000000000..bba0c9c9f9fced2771381f71adc28636701665c9 Binary files /dev/null and b/target/classes/vslam/Mathworks_VSLAM_Example/bagOfFeaturesDataSLAM.mat differ diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperAddLoopConnections.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperAddLoopConnections.m new file mode 100644 index 0000000000000000000000000000000000000000..8c4ece7be009a3705b802813b4ad6fb04a36e0d1 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperAddLoopConnections.m @@ -0,0 +1,94 @@ +function [isLoopClosed, mapPoints, vSetKeyFrames] = helperAddLoopConnections(... + mapPoints, vSetKeyFrames, loopCandidates, currKeyFrameId, currFeatures, ... + loopEdgeNumMatches) +%helperAddLoopConnections add connections between the current key frame and +% the valid loop candidate key frames. A loop candidate is valid if it has +% enough covisible map points with the current key frame. + +% This is an example helper function that is subject to change or removal +% in future releases. + +% Copyright 2019-2023 The MathWorks, Inc. +%#codegen + +loopClosureEdge = zeros(0, 2, 'uint32'); + +numCandidates = size(loopCandidates,1); +if isSimMode + [index3d1, index2d1] = findWorldPointsInView(mapPoints, currKeyFrameId); +else + [index3d1Cg, index2d1Cg] = findWorldPointsInView(mapPoints, currKeyFrameId); + index2d1 = index2d1Cg{1}; + index3d1 = index3d1Cg{1}; +end + +validFeatures1 = currFeatures.Features(index2d1, :); + +for k = 1 : numCandidates + if isSimMode() + [index3d2, index2d2] = findWorldPointsInView(mapPoints, loopCandidates(k)); + else + [index3d2Cg, index2d2Cg] = findWorldPointsInView(mapPoints, loopCandidates(k)); + index2d2 = index2d2Cg{1}; + index3d2 = index3d2Cg{1}; + end + allFeatures2 = vSetKeyFrames.Views.Features{loopCandidates(k)}; + + validFeatures2 = allFeatures2(index2d2, :); + + indexPairs = matchFeatures(binaryFeatures(validFeatures1), binaryFeatures(validFeatures2), ... + 'Unique', true, 'MaxRatio', 0.9, 'MatchThreshold', 40); + + % Check if all the candidate key frames have strong connection with the + % current keyframe + if size(indexPairs, 1) < loopEdgeNumMatches + continue + end + + % Estimate the relative pose of the current key frame with respect to the + % loop candidate keyframe with the highest similarity score + worldPoints1 = mapPoints.WorldPoints(index3d1(indexPairs(:, 1)), :); + worldPoints2 = mapPoints.WorldPoints(index3d2(indexPairs(:, 2)), :); + + tform1 = pose2extr(vSetKeyFrames.Views.AbsolutePose(end)); + tform2 = pose2extr(vSetKeyFrames.Views.AbsolutePose(loopCandidates(k))); + + worldPoints1InCamera1 = transformPointsForward(tform1, worldPoints1) ; + worldPoints2InCamera2 = transformPointsForward(tform2, worldPoints2) ; + + w = warning('off','all'); + if isSimMode() + [tform, inlierIndex] = estgeotform3d(... + worldPoints1InCamera1, worldPoints2InCamera2, 'similarity', 'MaxDistance', 0.1); + else + [tform, inlierIndex] = estgeotform3d(... + worldPoints1InCamera1, worldPoints2InCamera2, 'rigid', 'MaxDistance', 0.1); + end + warning(w); + + % Add connection between the current key frame and the loop key frame + inlierIndexVals = inlierIndex(:); + indexPairs1 = indexPairs(inlierIndexVals, 1); + indexPairs2 = indexPairs(inlierIndexVals, 2); + index2dPairs = index2d2(indexPairs2); + index2d1Pairs = index2d1(indexPairs1); + matches = uint32([index2dPairs, index2d1Pairs]); + vSetKeyFrames = addConnection(vSetKeyFrames, loopCandidates(k), currKeyFrameId, tform, 'Matches', matches); + if isSimMode() + disp(['Loop edge added between keyframe: ', num2str(loopCandidates(k)), ' and ', num2str(currKeyFrameId)]); + end + + % Fuse co-visible map points + matchedIndex3d1 = index3d1(indexPairs1); + matchedIndex3d2 = index3d2(indexPairs2); + + mapPoints = updateWorldPoints(mapPoints, matchedIndex3d1, mapPoints.WorldPoints(matchedIndex3d2, :)); + + loopClosureEdge = [loopClosureEdge; loopCandidates(k), currKeyFrameId]; +end +isLoopClosed = ~isempty(loopClosureEdge); +end + +function tf = isSimMode() +tf = isempty(coder.target); +end \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperAddNewKeyFrame.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperAddNewKeyFrame.m new file mode 100644 index 0000000000000000000000000000000000000000..8171da4598e2f5e654d532de5f2eafe794b88a54 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperAddNewKeyFrame.m @@ -0,0 +1,54 @@ +function [mapPoints, vSetKeyFrames] = helperAddNewKeyFrame(mapPoints, vSetKeyFrames,... + cameraPose, currFeatures, currPoints, mapPointsIndices, featureIndices, keyFramesIndices) +%helperAddNewKeyFrame add key frames to the key frame set +% +% This is an example helper function that is subject to change or removal +% in future releases. + +% Copyright 2019-2023 The MathWorks, Inc. +%#codegen + +viewId = vSetKeyFrames.Views.ViewId(end)+1; + +vSetKeyFrames = addView(vSetKeyFrames, viewId, cameraPose,... + 'Features', currFeatures.Features, ... + 'Points', currPoints); + +viewsAbsPoses = vSetKeyFrames.Views.AbsolutePose; + +for i = 1:numel(keyFramesIndices) + localKeyFrameId = keyFramesIndices(i); + if isSimMode() + [index3d, index2d] = findWorldPointsInView(mapPoints, localKeyFrameId); + else + [index3dCg, index2dCg] = findWorldPointsInView(mapPoints, localKeyFrameId); + index3d = index3dCg{1}; + index2d = index2dCg{1}; + end + [~, ia, ib] = intersect(index3d, mapPointsIndices, 'stable'); + + prePose = viewsAbsPoses(localKeyFrameId); + relPose = rigidtform3d(prePose.R' * cameraPose.R, ... + (cameraPose.Translation-prePose.Translation)*prePose.R); + + if numel(ia) > 5 + if isSimMode() + vSetKeyFrames = addConnection(vSetKeyFrames, localKeyFrameId, viewId, relPose, ... + 'Matches', [index2d(ia),featureIndices(ib)]); + else + coder.varsize('matches', [inf 2], [1, 0]); + fIndices = featureIndices(ib(:)); + matches = [index2d(ia), fIndices]; + vSetKeyFrames = addConnection(vSetKeyFrames, localKeyFrameId, viewId, relPose, ... + 'Matches', matches); + end + end +end + +mapPoints = addCorrespondences(mapPoints, viewId, mapPointsIndices, ... + featureIndices); +end + +function tf = isSimMode() + tf = isempty(coder.target); +end \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperCheckLoopClosure.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperCheckLoopClosure.m new file mode 100644 index 0000000000000000000000000000000000000000..7cff3e85c2f308126c160e6d73176923a5b38914 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperCheckLoopClosure.m @@ -0,0 +1,58 @@ +function [isDetected, loopKeyFrameIds] = helperCheckLoopClosure(vSetKeyFrames, ... + currKeyframeId, imageDatabase, currImg, loopEdgeNumMatches) +%helperCheckLoopClosure detect loop candidates key frames by retrieving +% visually similar images from the feature database. +% +% This is an example helper function that is subject to change or removal +% in future releases. + +% Copyright 2019-2023 The MathWorks, Inc. +%#codegen + +% Retrieve all the visually similar key frames +[candidateViewIds, similarityscores] = retrieveImages(currImg, imageDatabase); + +% Compute similarity between the current key frame and its strongly-connected +% key frames. The minimum similarity score is used as a baseline to find +% loop candidate key frames, which are visually similar to but not connected +% to the current key frame +covisViews = connectedViews(vSetKeyFrames, currKeyframeId); +covisViewsIds = covisViews.ViewId; +strongCovisViews = connectedViews(vSetKeyFrames, currKeyframeId, 'MinNumMatches', loopEdgeNumMatches); +strongCovisViewIds = strongCovisViews.ViewId; + +% Retrieve the top 10 similar connected key frames +[~,~,scores] = evaluateImageRetrieval(currImg, imageDatabase, strongCovisViewIds, 'NumResults', 10); +minScore = min(scores); + +[loopKeyFrameIds,ia] = setdiff(candidateViewIds, covisViewsIds, 'stable'); + +% Scores of non-connected key frames +candidateScores = similarityscores(ia); % Descending + +if ~isempty(ia) + bestScore = candidateScores(1); + + % Score must be higher than the 75% of the best score + isValid = candidateScores > max(bestScore*0.75, minScore); + + loopKeyFrameIds = loopKeyFrameIds(isValid); +else + loopKeyFrameIds = zeros(coder.ignoreConst(0), coder.ignoreConst(0), class(loopKeyFrameIds)); +end + +% Loop candidates need to be consecutively detected +minNumCandidates = 3; % At least 3 candidates are found +if size(loopKeyFrameIds,1) >= minNumCandidates + groups = nchoosek(loopKeyFrameIds, minNumCandidates); + consecutiveGroups = groups(max(groups,[],2) - min(groups,[],2) < 4, :); + if ~isempty(consecutiveGroups) % Consecutive candidates are found + loopKeyFrameIds = consecutiveGroups(1,:); + isDetected = true; + else + isDetected = false; + end +else + isDetected = false; +end +end \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperCreateNewMapPoints.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperCreateNewMapPoints.m new file mode 100644 index 0000000000000000000000000000000000000000..1731749fa36785ad66beb4aa0763f71a1c072255 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperCreateNewMapPoints.m @@ -0,0 +1,205 @@ +function [mapPoints, vSetKeyFrames, recentPointIdx] = helperCreateNewMapPoints(... + mapPoints, vSetKeyFrames, currKeyFrameId, intrinsics, scaleFactor, minNumMatches, minParallax) +%helperCreateNewMapPoints creates new map points by triangulating matched +% feature points in the current key frame and the connected key frames. +% +% This is an example helper function that is subject to change or removal +% in future releases. + +% Copyright 2019-2023 The MathWorks, Inc. +%#codegen + +% Get connected key frames +KcViews = connectedViews(vSetKeyFrames, currKeyFrameId, 'MinNumMatches', minNumMatches); +KcIDs = KcViews.ViewId; + +% Retreive data of the current key frame +views = vSetKeyFrames.Views; +currPose = views.AbsolutePose(currKeyFrameId); +currFeatures = views.Features{currKeyFrameId}; +currPoints = views.Points{currKeyFrameId}; +currLocations = currPoints.Location; +currScales = currPoints.Scale; + +% Camera projection matrix +currCamMatrix = cameraProjection(intrinsics, pose2extr(currPose)); + +recentPointIdx = zeros(0, 1); +for i = 1:numel(KcIDs) + kfPose = views.AbsolutePose(KcIDs(i)); + if isSimMode() + [kfIndex3d, kfIndex2d] = findWorldPointsInView(mapPoints, KcIDs(i)); + else + [kfIndex3dCg, kfIndex2dCg] = findWorldPointsInView(mapPoints, KcIDs(i)); + kfIndex3d = kfIndex3dCg{1}; + kfIndex2d = kfIndex2dCg{1}; + end + xyzPoints = mapPoints.WorldPoints(kfIndex3d,:); + medianDepth = median(vecnorm(xyzPoints - kfPose.Translation, 2, 2)); + + % Skip the key frame is the change of view is small + isViewClose = norm(kfPose.Translation - currPose.Translation)/medianDepth < 0.01; + + if isViewClose + continue + end + + % Retrieve data of the connected key frame + kfFeatures = views.Features{KcIDs(i)}; + kfPoints = views.Points{KcIDs(i)}; + kfLocations = kfPoints.Location; + kfScales = kfPoints.Scale; + + % currIndex2d changes in each iteration as new map points are created + if isSimMode() + [~, currIndex2d] = findWorldPointsInView(mapPoints, currKeyFrameId); + else + [~, currIndex2dCg] = findWorldPointsInView(mapPoints, currKeyFrameId); + currIndex2d = currIndex2dCg{1}; + end + % Only use unmatched feature points + uIndices1 = setdiff(uint32(1:size(kfFeatures,1))', kfIndex2d, 'stable'); + uIndices2 = setdiff(uint32(1:size(currFeatures,1))', currIndex2d, 'stable'); + + uFeatures1 = kfFeatures(uIndices1, :); + uFeatures2 = currFeatures(uIndices2, :); + + uLocations1 = kfLocations(uIndices1, :); + uLocations2 = currLocations(uIndices2, :); + + uScales1 = kfScales(uIndices1); + uScales2 = currScales(uIndices2); + + indexPairs = matchFeatures(binaryFeatures(uFeatures1), binaryFeatures(uFeatures2),... + 'Unique', true, 'MaxRatio', 0.7, 'MatchThreshold', 40); + + if isempty(indexPairs) + continue + end + + matchedPoints1 = uLocations1(indexPairs(:,1), :); + matchedPoints2 = uLocations2(indexPairs(:,2), :); + + % Epipole in the current key frame + epiPole = world2img(kfPose.Translation, pose2extr(currPose), intrinsics); + distToEpipole = vecnorm(matchedPoints2 - epiPole, 2, 2); + + % Compute fundamental matrix + F = computeF(intrinsics, kfPose, currPose); + + % Epipolar line in the second image + epiLine = epipolarLine(F, matchedPoints2); + distToLine = abs(sum(epiLine.* [matchedPoints1, ones(size(matchedPoints1,1), 1)], 2))./... + sqrt(sum(epiLine(:,1:2).^2, 2)); + isValid = distToLine < 2*uScales2(indexPairs(:,2)) & ... + distToEpipole > 10*uScales2(indexPairs(:,2)); + + indexPairs = indexPairs(isValid, :); + matchedPoints1 = matchedPoints1(isValid, :); + matchedPoints2 = matchedPoints2(isValid, :); + + % Parallax check + isLarge = isLargeParalalx(matchedPoints1, matchedPoints2, kfPose, ... + currPose, intrinsics, minParallax); + + matchedPoints1 = matchedPoints1(isLarge, :); + matchedPoints2 = matchedPoints2(isLarge, :); + indexPairs = indexPairs(isLarge, :); + + kfCamMatrix = cameraProjection(intrinsics, pose2extr(kfPose)); + + % Triangulate two views to create new world points + [xyzPoints, reprojectionErrors, validIdx] = triangulate(matchedPoints1, ... + matchedPoints2, kfCamMatrix, currCamMatrix); + + % Filtering by view direction and reprojection error + inlier = filterTriangulatedMapPoints(xyzPoints, kfPose, currPose, ... + uScales1(indexPairs(:,1)), uScales2(indexPairs(:,2)), ... + reprojectionErrors, scaleFactor, validIdx); + + % Add new map points and update connections + if any(inlier) + xyzPoints = xyzPoints(inlier,:); + indexPairs = indexPairs(inlier, :); + + mIndices1 = uIndices1(indexPairs(:, 1)); + mIndices2 = uIndices2(indexPairs(:, 2)); + + [mapPoints, indices] = addWorldPoints(mapPoints, xyzPoints); + recentPointIdx = [recentPointIdx; indices]; %#ok + + % Add new observations + mapPoints = addCorrespondences(mapPoints, KcIDs(i),indices, mIndices1); + mapPoints = addCorrespondences(mapPoints, currKeyFrameId, indices, mIndices2); + + % Update connections with new feature matches + if isSimMode() + [~,ia] = intersect(vSetKeyFrames.Connections{:,1:2}, ... + [KcIDs(i), currKeyFrameId], 'row', 'stable'); + oldMatches = vSetKeyFrames.Connections.Matches{ia}; + else + connections = vSetKeyFrames.Connections; + [~,ia] = intersect([connections.ViewId1, connections.ViewId2], ... + [KcIDs(i), currKeyFrameId], 'row', 'stable'); + oldMatches = connections.Matches{ia}; + end + newMatches = [oldMatches; mIndices1, mIndices2]; + vSetKeyFrames = updateConnection(vSetKeyFrames, KcIDs(i), currKeyFrameId, ... + 'Matches', newMatches); + end +end +end + +function F = computeF(intrinsics, pose1, pose2) +R1 = pose1.R; +t1 = pose1.Translation'; + +R2 = pose2.R; +t2 = pose2.Translation'; + +R12 = R1'*R2; +t12 = R1'*(t2-t1); + +% Skew symmetric matrix +t12x = [0, -t12(3), t12(2) + t12(3), 0, -t12(1) + -t12(2) t12(1), 0]; + +F = intrinsics.K'\ t12x * R12 / intrinsics.K; +end + +function inlier = filterTriangulatedMapPoints(xyzPoints, pose1, pose2, ... + scales1, scales2, reprojectionErrors, scaleFactor, isInFront) + +camToPoints1= xyzPoints - pose1.Translation; +camToPoints2= xyzPoints - pose2.Translation; + +% Check scale consistency and reprojection errors +distances1 = vecnorm(camToPoints1, 2, 2); +distances2 = vecnorm(camToPoints2, 2, 2); +ratioDist = distances1./distances2; +ratioScale = scales2./scales1; + +ratioFactor = 1.5 * scaleFactor; + +isInScale = (ratioDist./ratioScale < ratioFactor | ... + ratioScale./ratioDist < ratioFactor); + +maxError = sqrt(6); +isSmallError= reprojectionErrors < maxError*min(scales1, scales2); +inlier = isInScale & isSmallError & isInFront; +end + +function isLarge = isLargeParalalx(points1, points2, pose1, pose2, intrinsics, minParallax) + +% Parallax check +ray1 = [points1, ones(size(points1(:,1)))]/intrinsics.K' *pose1.R'; +ray2 = [points2, ones(size(points1(:,2)))]/intrinsics.K' *pose2.R'; + +cosParallax = sum(ray1 .* ray2, 2) ./(vecnorm(ray1, 2, 2) .* vecnorm(ray2, 2, 2)); +isLarge = cosParallax < cosd(minParallax) & cosParallax > 0; +end + +function tf = isSimMode() + tf = isempty(coder.target); +end \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperImportGroundTruth.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperImportGroundTruth.m new file mode 100644 index 0000000000000000000000000000000000000000..8c9488ba53b88a69711a59deed543ca532bae1e8 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperImportGroundTruth.m @@ -0,0 +1,57 @@ +function camPoses = helperImportGroundTruth(fileName, imds) +%helperImportGroundTruth Import ground truth camera poses from a .txt file +% +% This is an example helper function that is subject to change or removal +% in future releases. +% +% Copyright 2023 The MathWorks Inc. + +% Set up the Import Options and import the data +opts = delimitedTextImportOptions("NumVariables", 9); + +% Specify range and delimiter +opts.DataLines = [4, Inf]; +opts.Delimiter = " "; + +% Specify column names and types +opts.VariableNames = ["timestamp", "tx", "ty", "tz", "qx", "qy", "qz", "qw", "Var9"]; +opts.SelectedVariableNames = ["timestamp", "tx", "ty", "tz", "qx", "qy", "qz", "qw"]; +opts.VariableTypes = ["double", "double", "double", "double", "double", "double", "double", "double", "string"]; + +% Specify file level properties +opts.ExtraColumnsRule = "ignore"; +opts.EmptyLineRule = "read"; +opts.ConsecutiveDelimitersRule = "join"; +opts.LeadingDelimitersRule = "ignore"; + +% Specify variable properties +opts = setvaropts(opts, "Var9", "WhitespaceRule", "preserve"); +opts = setvaropts(opts, "Var9", "EmptyFieldRule", "auto"); + +% Import the data +groundtruth = readtable(fileName, opts); + +% Initialize the output +camPoses = repmat(rigidtform3d, 1, numel(imds.Files)); + +firstT = [groundtruth(1,:).tx groundtruth(1,:).ty groundtruth(1,:).tz]; +firstR = quat2rotm([groundtruth(1,:).qw groundtruth(1,:).qx groundtruth(1,:).qy groundtruth(1,:).qz]); + +% Find the ground truth data corresponding to the image based on the timestamp +[~,imageTS] = fileparts(imds.Files); +imgTimestamp = str2double(imageTS); +index = interp1(groundtruth.timestamp, 1:numel(groundtruth.timestamp), imgTimestamp, 'nearest', 'extrap'); + +for i=1:numel(imds.Files) + groundtruth_raw = groundtruth(index(i),:); + + % Transform all the camera poses to the coordinate system of the first camera + % Rotation + q = [groundtruth_raw.qw groundtruth_raw.qx groundtruth_raw.qy groundtruth_raw.qz]; + camPoses(i).R = firstR'*quat2rotm(q); + + % Translation + camPoses(i).Translation = ([groundtruth_raw.tx groundtruth_raw.ty groundtruth_raw.tz]-firstT) * firstR; +end +end + diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperMonoVisualSLAM.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperMonoVisualSLAM.m new file mode 100644 index 0000000000000000000000000000000000000000..24abc6bc55ccf40ce6a91a017d17b88e0ec1d499 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperMonoVisualSLAM.m @@ -0,0 +1,31 @@ +function [xyzPoint, camPoses] = helperMonoVisualSLAM(image) + +% Copyright 2023 The MathWorks Inc. + +%#codegen + +persistent vslam xyzPointsInternal camPosesInternal + +if isempty(vslam) + % Create a monovslam class to process the image data + focalLength = [535.4, 539.2]; % in units of pixels + principalPoint = [320.1, 247.6]; % in units of pixels + imageSize = [480, 640]; % in units of pixels + intrinsics = cameraIntrinsics(focalLength, principalPoint, imageSize); + + vslam = monovslam(intrinsics); +end + +% Process each image frame +addFrame(vslam, image); + +% Get 3-D map points and camera poses +if isempty(xyzPointsInternal) || hasNewKeyFrame(vslam) + xyzPointsInternal = mapPoints(vslam); + camPosesInternal = poses(vslam); +end + +xyzPoint = xyzPointsInternal; + +% Convert camera poses to homogeneous transformation matrices +camPoses = cat(3, camPosesInternal.A); \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperORBFeatureExtractorFunction.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperORBFeatureExtractorFunction.m new file mode 100644 index 0000000000000000000000000000000000000000..d8c77bf675b0e62057d8b72b15581914ba951f22 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperORBFeatureExtractorFunction.m @@ -0,0 +1,25 @@ +function [features, featureMetrics]= helperORBFeatureExtractorFunction(I) +% helperORBFeatureExtractorFunction Implements the ORB feature extraction +% used in bagOfFeatures. +% +% This is an example helper function that is subject to change or removal +% in future releases. + +% Copyright 2021 The MathWorks, Inc. + +numPoints = 1000; + +% Detect ORB features +Igray = im2gray(I); + +points = detectORBFeatures(Igray, 'ScaleFactor', 1.2, 'NumLevels', 8); + +% Select a subset of features, uniformly distributed throughout the image +points = selectUniform(points, numPoints, size(Igray, 1:2)); + +% Extract features +features = extractFeatures(Igray, points); + +% Compute the Feature Metric. Use the variance of features as the metric +featureMetrics = var(single(features.Features),[],2); + diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperTrackLastKeyFrame.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperTrackLastKeyFrame.m new file mode 100644 index 0000000000000000000000000000000000000000..467ff8188bc13a55f385e8062267d67f5d77ff54 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperTrackLastKeyFrame.m @@ -0,0 +1,106 @@ +%helperTrackLastKeyFrame Estimate the camera pose by tracking the last key frame +% [currPose, mapPointIdx, featureIdx] = helperTrackLastKeyFrameStereo(mapPoints, +% views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor) estimates +% the camera pose of the current frame by matching features with the +% previous key frame. +% +% This is an example helper function that is subject to change or removal +% in future releases. +% +% Inputs +% ------ +% mapPoints - A helperMapPoints objects storing map points +% views - View attributes of key frames +% currFeatures - Features in the current frame +% currPoints - Feature points in the current frame +% lastKeyFrameId - ViewId of the last key frame +% intrinsics - Camera intrinsics +% scaleFactor - scale factor of features +% +% Outputs +% ------- +% currPose - Estimated camera pose of the current frame +% mapPointIdx - Indices of map points observed in the current frame +% featureIdx - Indices of features corresponding to mapPointIdx + +% Copyright 2019-2022 The MathWorks, Inc. + +function [currPose, mapPointIdx, featureIdx] = helperTrackLastKeyFrame(... + mapPoints, views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor) + +% Match features from the previous key frame with known world locations +[index3d, index2d] = findWorldPointsInView(mapPoints, lastKeyFrameId); +lastKeyFrameFeatures = views.Features{lastKeyFrameId}(index2d,:); +lastKeyFramePoints = views.Points{lastKeyFrameId}(index2d); + +indexPairs = matchFeatures(currFeatures, binaryFeatures(lastKeyFrameFeatures),... + 'Unique', true, 'MaxRatio', 0.9, 'MatchThreshold', 40); + +% Estimate the camera pose +matchedImagePoints = currPoints.Location(indexPairs(:,1),:); +matchedWorldPoints = mapPoints.WorldPoints(index3d(indexPairs(:,2)), :); + +matchedImagePoints = cast(matchedImagePoints, 'like', matchedWorldPoints); +[currPose, inlier, status] = estworldpose(... + matchedImagePoints, matchedWorldPoints, intrinsics, ... + 'Confidence', 95, 'MaxReprojectionError', 3, 'MaxNumTrials', 1e4); + +if status + currPose=[]; + mapPointIdx=[]; + featureIdx=[]; + return +end + +% Refine camera pose only +currPose = bundleAdjustmentMotion(matchedWorldPoints(inlier,:), ... + matchedImagePoints(inlier,:), currPose, intrinsics, ... + 'PointsUndistorted', true, 'AbsoluteTolerance', 1e-7,... + 'RelativeTolerance', 1e-15, 'MaxIteration', 20); + +% Search for more matches with the map points in the previous key frame +xyzPoints = mapPoints.WorldPoints(index3d,:); + +[projectedPoints, isInImage] = world2img(xyzPoints, pose2extr(currPose), intrinsics); +projectedPoints = projectedPoints(isInImage, :); + +minScales = max(1, lastKeyFramePoints.Scale(isInImage)/scaleFactor); +maxScales = lastKeyFramePoints.Scale(isInImage)*scaleFactor; +r = 4; +searchRadius = r*lastKeyFramePoints.Scale(isInImage); + +indexPairs = matchFeaturesInRadius(binaryFeatures(lastKeyFrameFeatures(isInImage,:)), ... + binaryFeatures(currFeatures.Features), currPoints, projectedPoints, searchRadius, ... + 'MatchThreshold', 40, 'MaxRatio', 0.8, 'Unique', true); + +if size(indexPairs, 1) < 20 + indexPairs = matchFeaturesInRadius(binaryFeatures(lastKeyFrameFeatures(isInImage,:)), ... + binaryFeatures(currFeatures.Features), currPoints, projectedPoints, 2*searchRadius, ... + 'MatchThreshold', 40, 'MaxRatio', 1, 'Unique', true); +end + +if size(indexPairs, 1) < 10 + currPose=[]; + mapPointIdx=[]; + featureIdx=[]; + return +end + +% Filter by scales +isGoodScale = currPoints.Scale(indexPairs(:, 2)) >= minScales(indexPairs(:, 1)) & ... + currPoints.Scale(indexPairs(:, 2)) <= maxScales(indexPairs(:, 1)); +indexPairs = indexPairs(isGoodScale, :); + +% Obtain the index of matched map points and features +tempIdx = find(isInImage); % Convert to linear index +mapPointIdx = index3d(tempIdx(indexPairs(:,1))); +featureIdx = indexPairs(:,2); + +% Refine the camera pose again +matchedWorldPoints = mapPoints.WorldPoints(mapPointIdx, :); +matchedImagePoints = currPoints.Location(featureIdx, :); + +currPose = bundleAdjustmentMotion(matchedWorldPoints, matchedImagePoints, ... + currPose, intrinsics, 'PointsUndistorted', true, 'AbsoluteTolerance', 1e-7,... + 'RelativeTolerance', 1e-15, 'MaxIteration', 20); +end \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperTrackLocalMap.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperTrackLocalMap.m new file mode 100644 index 0000000000000000000000000000000000000000..68afe780783e974593bf71e7b054a885e86aa5b4 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperTrackLocalMap.m @@ -0,0 +1,231 @@ +function [localKeyFrameIds, currPose, mapPointIdx, featureIdx, isKeyFrame] = ... + helperTrackLocalMap(mapPoints, vSetKeyFrames, mapPointIdx, ... + featureIdx, currPose, currFeatures, currPoints, intrinsics, scaleFactor, numLevels, ... + newKeyFrameAdded, lastKeyFrameIndex, currFrameIndex, numSkipFrames, numPointsKeyFrame) +%helperTrackLocalMap Refine camera pose by tracking the local map +% +% This is an example helper function that is subject to change or removal +% in future releases. +% +% Inputs +% ------ +% mapPoints - A worldpointset object storing map points +% vSetKeyFrames - An imageviewset storing key frames +% mapPointsIndices - Indices of map points observed in the current frame +% featureIndices - Indices of features in the current frame +% corresponding to map points denoted by mapPointsIndices +% currPose - Current camera pose +% currFeatures - ORB Features in the current frame +% currPoints - Feature points in the current frame +% intrinsics - Camera intrinsics +% scaleFactor - scale factor of features +% numLevels - number of levels in feature exatraction +% newKeyFrameAdded - A boolean scalar indicating if a new key frame is +% added recently +% lastKeyFrameIndex - Frame index of the last key frame +% currFrameIndex - Frame index of the current frame +% numSkipFrames - Largest number of frames to skip +% numPointsKeyFrame - Minimum number of points tracked by a key frame +% +% Outputs +% ------- +% localKeyFrameIds - ViewIds of the local key frames +% currPose - Refined camera pose of the current frame +% mapPointIdx - Indices of map points observed in the current frame +% featureIdx - Indices of features in the current frame corresponding +% to mapPointIdx +% isKeyFrame - A boolean scalar indicating if the current frame is +% a key frame + +% Copyright 2019-2022 The MathWorks, Inc. + +% Initialize outputs +localKeyFrameIds = []; +isKeyFrame = false; + +% Check if there are no map points to process +if isempty(mapPointIdx) + disp('No map points to process. Skipping local map tracking.'); + return; % Early return to skip processing when there are no map points +end + +persistent numPointsRefKeyFrame localPointsIndices localKeyFrameIdsInternal + +if isempty(numPointsRefKeyFrame) || newKeyFrameAdded + [localPointsIndices, localKeyFrameIdsInternal, numPointsRefKeyFrame] = ... + updateRefKeyFrameAndLocalPoints(mapPoints, vSetKeyFrames, mapPointIdx); +end + +% Project the map into the frame and search for more map point correspondences +newMapPointIdx = setdiff(localPointsIndices, mapPointIdx, 'stable'); +localFeatures = getFeatures(mapPoints, vSetKeyFrames.Views, newMapPointIdx); +[projectedPoints, inlierIndex, predictedScales, viewAngles] = removeOutlierMapPoints(mapPoints, ... + currPose, intrinsics, newMapPointIdx, scaleFactor, numLevels); + +newMapPointIdx = newMapPointIdx(inlierIndex); +localFeatures = localFeatures(inlierIndex,:); + +unmatchedfeatureIdx = setdiff(cast((1:size( currFeatures.Features, 1)).', 'uint32'), ... + featureIdx,'stable'); +unmatchedFeatures = currFeatures.Features(unmatchedfeatureIdx, :); +unmatchedValidPoints= currPoints(unmatchedfeatureIdx); + +% Search radius depends on scale and view direction +searchRadius = 4*ones(size(localFeatures, 1), 1); +searchRadius(viewAngles<3) = 2.5; +searchRadius = searchRadius.*predictedScales; + +indexPairs = matchFeaturesInRadius(binaryFeatures(localFeatures),... + binaryFeatures(unmatchedFeatures), unmatchedValidPoints, projectedPoints, ... + searchRadius, 'MatchThreshold', 40, 'MaxRatio', 0.9, 'Unique', true); + +% Filter by scales +isGoodScale = currPoints.Scale(indexPairs(:, 2)) >= ... + max(1, predictedScales(indexPairs(:, 1))/scaleFactor) & ... + currPoints.Scale(indexPairs(:, 2)) <= predictedScales(indexPairs(:, 1)); +indexPairs = indexPairs(isGoodScale, :); + +% Refine camera pose with more 3D-to-2D correspondences +mapPointIdx = [newMapPointIdx(indexPairs(:,1)); mapPointIdx]; +featureIdx = [unmatchedfeatureIdx(indexPairs(:,2)); featureIdx]; +matchedMapPoints = mapPoints.WorldPoints(mapPointIdx,:); +matchedImagePoints = currPoints.Location(featureIdx,:); + +isKeyFrame = checkKeyFrame(numPointsRefKeyFrame, lastKeyFrameIndex, ... + currFrameIndex, mapPointIdx, numSkipFrames, numPointsKeyFrame); + +localKeyFrameIds = localKeyFrameIdsInternal; + +if isKeyFrame + % Refine camera pose only if the current frame is a key frame + currPose = bundleAdjustmentMotion(matchedMapPoints, matchedImagePoints, ... + currPose, intrinsics, 'PointsUndistorted', true, ... + 'AbsoluteTolerance', 1e-7, 'RelativeTolerance', 1e-16,'MaxIteration', 20); +end +end + +function [localPointsIndices, localKeyFrameIds, numPointsRefKeyFrame] = ... + updateRefKeyFrameAndLocalPoints(mapPoints, vSetKeyFrames, pointIndices) + +if vSetKeyFrames.NumViews == 1 + localKeyFrameIds = vSetKeyFrames.Views.ViewId; + localPointsIndices = (1:mapPoints.Count)'; + numPointsRefKeyFrame = mapPoints.Count; + return +end + +% The reference key frame has the most covisible map points +viewIds = findViewsOfWorldPoint(mapPoints, pointIndices); +refKeyFrameId = mode(vertcat(viewIds{:})); + +localKeyFrames = connectedViews(vSetKeyFrames, refKeyFrameId, "MaxDistance", 2); +localKeyFrameIds = [localKeyFrames.ViewId; refKeyFrameId]; + +pointIdx = findWorldPointsInView(mapPoints, localKeyFrameIds); +if iscell(pointIdx) + numPointsRefKeyFrame = numel(pointIdx{localKeyFrameIds==refKeyFrameId}); + localPointsIndices = sort(vertcat(pointIdx{:})); +else + numPointsRefKeyFrame = numel(pointIdx); + localPointsIndices = sort(pointIdx); +end +end + +function features = getFeatures(mapPoints, views, mapPointIdx) + +% Efficiently retrieve features and image points corresponding to map points +% denoted by mapPointIdx +allIndices = zeros(1, numel(mapPointIdx)); + +% ViewId and offset pair +count = []; % (ViewId, NumFeatures) +viewsFeatures = views.Features; + +for i = 1:numel(mapPointIdx) + index3d = mapPointIdx(i); + + viewId = double(mapPoints.RepresentativeViewId(index3d)); + + if isempty(count) + count = [viewId, size(viewsFeatures{viewId},1)]; + elseif ~any(count(:,1) == viewId) + count = [count; viewId, size(viewsFeatures{viewId},1)]; + end + + idx = find(count(:,1)==viewId); + + if idx > 1 + offset = sum(count(1:idx-1,2)); + else + offset = 0; + end + allIndices(i) = mapPoints.RepresentativeFeatureIndex(index3d) + offset; +end + +uIds = count(:,1); + +% Concatenating features and indexing once is faster than accessing via a for loop +allFeatures = vertcat(viewsFeatures{uIds}); +features = allFeatures(allIndices, :); +end + +function [projectedPoints, inliers, predictedScales, viewAngles] = removeOutlierMapPoints(... + mapPoints, pose, intrinsics, localPointsIndices, scaleFactor, ... + numLevels) + +% 1) Points within the image bounds +xyzPoints = mapPoints.WorldPoints(localPointsIndices, :); +[projectedPoints, isInImage] = world2img(xyzPoints, pose2extr(pose), intrinsics); + +if isempty(projectedPoints) + error('Tracking failed. Try inserting new key frames more frequently.') +end + +% 2) Parallax less than 60 degrees +cameraNormVector = [0 0 1] * pose.Rotation; +cameraToPoints = xyzPoints - pose.Translation; +viewDirection = mapPoints.ViewingDirection(localPointsIndices, :); +validByView = sum(viewDirection.*cameraToPoints, 2) > ... + cosd(60)*(vecnorm(cameraToPoints, 2, 2)); + +% 3) Distance from map point to camera center is in the range of scale +% invariant depth +minDist = mapPoints.DistanceLimits(localPointsIndices,1)/scaleFactor; +maxDist = mapPoints.DistanceLimits(localPointsIndices,2)*scaleFactor; +dist = vecnorm(xyzPoints - pose.Translation, 2, 2); + +validByDistance = dist > minDist & dist < maxDist; + +inliers = isInImage & validByView & validByDistance; + +% Predicted scales +level= ceil(log(maxDist ./ dist)./log(scaleFactor)); +level(level<0) = 0; +level(level>=numLevels-1) = numLevels-1; +predictedScales = scaleFactor.^level; + +% View angles +viewAngles = acosd(sum(cameraNormVector.*cameraToPoints, 2) ./ ... + vecnorm(cameraToPoints, 2, 2)); + +predictedScales = predictedScales(inliers); +viewAngles = viewAngles(inliers); + +projectedPoints = projectedPoints(inliers, :); +end + +function isKeyFrame = checkKeyFrame(numPointsRefKeyFrame, lastKeyFrameIndex, ... + currFrameIndex, mapPointsIndices, numSkipFrames, numPointsKeyFrame) + +% More than numSkipFrames frames have passed from last key frame insertion +tooManyNonKeyFrames = currFrameIndex > lastKeyFrameIndex + numSkipFrames; + +% Track less than numPointsKeyFrame map points +tooFewMapPoints = numel(mapPointsIndices) < numPointsKeyFrame; + +% Tracked map points are fewer than 90% of points tracked by +% the reference key frame +tooFewTrackedPoints = numel(mapPointsIndices) < 0.9 * numPointsRefKeyFrame; + +isKeyFrame = (tooManyNonKeyFrames || tooFewMapPoints) && tooFewTrackedPoints; +end \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperVisualizeMatchedFeatures.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperVisualizeMatchedFeatures.m new file mode 100644 index 0000000000000000000000000000000000000000..ff223197e98f091b99e2d4ea5cb42411f276b9c3 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperVisualizeMatchedFeatures.m @@ -0,0 +1,50 @@ +classdef helperVisualizeMatchedFeatures < handle +%helperVisualizeMatchedFeatures show the matched features in a frame +% +% This is an example helper class that is subject to change or removal +% in future releases. + +% Copyright 2019-2020 The MathWorks, Inc. + + properties (Access = private) + Image + + Feature + end + + methods (Access = public) + + function obj = helperVisualizeMatchedFeatures(I, featurePoints) + locations= featurePoints.Location; + + % Plot image + hFig = figure; + hAxes = newplot(hFig); + + % Set figure visibility and position + hFig.Visible = 'on'; + movegui(hFig, [300 220]); + + % Show the image + obj.Image = imshow(I, 'Parent', hAxes, 'Border', 'tight'); + title(hAxes, 'Matched Features in Current Frame'); + hold(hAxes, 'on'); + + % Plot features + plot(featurePoints, hAxes, 'ShowOrientation',false, ... + 'ShowScale',false); + obj.Feature = findobj(hAxes.Parent,'Type','Line'); + end + + function updatePlot(obj, I, featurePoints) + locations = featurePoints.Location; + obj.Image.CData = I; + obj.Feature.XData = locations(:,1); + obj.Feature.YData = locations(:,2); + drawnow limitrate + end + end +end + + + diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperVisualizeMotionAndStructure.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperVisualizeMotionAndStructure.m new file mode 100644 index 0000000000000000000000000000000000000000..b064c0480c02a1f23f6c64ff7d6a4dfe3c723953 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperVisualizeMotionAndStructure.m @@ -0,0 +1,156 @@ +classdef helperVisualizeMotionAndStructure < handle +%helperVisualizeMatchedFeatures show map points and camera trajectory +% +% This is an example helper class that is subject to change or removal +% in future releases. + +% Copyright 2019-2022 The MathWorks, Inc. + + properties + XLim = [-1.5 1.5] + + YLim = [-1 0.5] + + ZLim = [-0.5 2] + + Axes + end + + properties (Access = private) + MapPointsPlot + + EstimatedTrajectory + + OptimizedTrajectory + + CameraPlot + end + + methods (Access = public) + function obj = helperVisualizeMotionAndStructure(vSetKeyFrames, mapPoints, varargin) + + if nargin > 2 + obj.XLim = varargin{1}; + obj.YLim = varargin{2}; + obj.ZLim = varargin{3}; + end + + [xyzPoints, currPose, trajectory] = retrievePlottedData(obj, vSetKeyFrames, mapPoints); + + obj.MapPointsPlot = pcplayer(obj.XLim, obj.YLim, obj.ZLim, ... + 'VerticalAxis', 'y', 'VerticalAxisDir', 'down'); + + obj.Axes = obj.MapPointsPlot.Axes; + obj.MapPointsPlot.view(xyzPoints); + obj.Axes.Children.DisplayName = 'Map points'; + + hold(obj.Axes, 'on'); + + % Set figure position on the screen + movegui(obj.Axes.Parent, [1000 200]); + + % Plot camera trajectory + obj.EstimatedTrajectory = plot3(obj.Axes, trajectory(:,1), trajectory(:,2), ... + trajectory(:,3), 'r', 'LineWidth', 2 , 'DisplayName', 'Estimated trajectory'); + + % Plot the current cameras + obj.CameraPlot = plotCamera(currPose, 'Parent', obj.Axes, 'Size', 0.05); + end + + function updatePlot(obj, vSetKeyFrames, mapPoints) + + [xyzPoints, currPose, trajectory] = retrievePlottedData(obj, vSetKeyFrames, mapPoints); + + % Update the point cloud + obj.MapPointsPlot.view(xyzPoints); + + % Update the camera trajectory + set(obj.EstimatedTrajectory, 'XData', trajectory(:,1), 'YData', ... + trajectory(:,2), 'ZData', trajectory(:,3)); + + % Update the current camera pose since the first camera is fixed + obj.CameraPlot.AbsolutePose = currPose.AbsolutePose; + obj.CameraPlot.Label = num2str(currPose.ViewId); + + drawnow limitrate + end + + function plotOptimizedTrajectory(obj, poses) + + % Delete the camera plot + delete(obj.CameraPlot); + + % Plot the optimized trajectory + trans = vertcat(poses.AbsolutePose.Translation); + obj.OptimizedTrajectory = plot3(obj.Axes, trans(:, 1), trans(:, 2), trans(:, 3), 'm', ... + 'LineWidth', 2, 'DisplayName', 'Optimized trajectory'); + end + + function plotActualTrajectory(obj, gTruth, optimizedPoses) + estimatedCams = vertcat(optimizedPoses.AbsolutePose.Translation); + actualCams = vertcat(gTruth.Translation); + scale = median(vecnorm(actualCams, 2, 2))/ median(vecnorm(estimatedCams, 2, 2)); + + % Update the plot based on the ground truth + updatePlotScale(obj, scale); + + % Plot the ground truth + plot3(obj.Axes, actualCams(:,1), actualCams(:,2), actualCams(:,3), ... + 'g','LineWidth',2, 'DisplayName', 'Actual trajectory'); + + drawnow limitrate + end + + function showLegend(obj) + % Add a legend to the axes + hLegend = legend(obj.Axes, 'Location', 'northeast', ... + 'TextColor', [1 1 1], 'FontWeight', 'bold'); + end + end + + methods (Access = private) + function [xyzPoints, currPose, trajectory] = retrievePlottedData(obj, vSetKeyFrames, mapPoints) + camPoses = poses(vSetKeyFrames); + currPose = camPoses(end,:); % Contains both ViewId and Pose + + % Ensure the rotation matrix is a rigid transformation + R = double(currPose.AbsolutePose.R); + t = double(currPose.AbsolutePose.Translation); + [U, ~, V] = svd(R); + currPose.AbsolutePose.A = eye(4); + currPose.AbsolutePose.A(1:3, 4) = t; + currPose.AbsolutePose.A(1:3, 1:3) = U * V'; + + trajectory = vertcat(camPoses.AbsolutePose.Translation); + xyzPoints = mapPoints.WorldPoints; + + % Only plot the points within the limit + inPlotRange = xyzPoints(:, 1) > obj.XLim(1) & ... + xyzPoints(:, 1) < obj.XLim(2) & xyzPoints(:, 2) > obj.YLim(1) & ... + xyzPoints(:, 2) < obj.YLim(2) & xyzPoints(:, 3) > obj.ZLim(1) & ... + xyzPoints(:, 3) < obj.ZLim(2); + xyzPoints = xyzPoints(inPlotRange, :); + end + + function updatePlotScale(obj, scale) + % Update the map points and camera trajectory based on the + % ground truth scale + obj.Axes.XLim = obj.Axes.XLim * scale; + obj.Axes.YLim = obj.Axes.YLim * scale; + obj.Axes.ZLim = obj.Axes.ZLim * scale; + + % Map points + obj.Axes.Children(end).XData = obj.Axes.Children(end).XData * scale; + obj.Axes.Children(end).YData = obj.Axes.Children(end).YData * scale; + obj.Axes.Children(end).ZData = obj.Axes.Children(end).ZData * scale; + + % Estiamted and optimized Camera trajectory + obj.EstimatedTrajectory.XData = obj.EstimatedTrajectory.XData * scale; + obj.EstimatedTrajectory.YData = obj.EstimatedTrajectory.YData * scale; + obj.EstimatedTrajectory.ZData = obj.EstimatedTrajectory.ZData * scale; + obj.OptimizedTrajectory.XData = obj.OptimizedTrajectory.XData * scale; + obj.OptimizedTrajectory.YData = obj.OptimizedTrajectory.YData * scale; + obj.OptimizedTrajectory.ZData = obj.OptimizedTrajectory.ZData * scale; + end + end +end \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/orbslamGroundTruth.mat b/target/classes/vslam/Mathworks_VSLAM_Example/orbslamGroundTruth.mat new file mode 100644 index 0000000000000000000000000000000000000000..ea1360e39c14cb70268bf6d6d4202b51eaf02014 Binary files /dev/null and b/target/classes/vslam/Mathworks_VSLAM_Example/orbslamGroundTruth.mat differ diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/VisualSLAMWithAnRGBDCameraExample.mlx b/target/classes/vslam/Mathworks_VSLAM_RGBD/VisualSLAMWithAnRGBDCameraExample.mlx new file mode 100644 index 0000000000000000000000000000000000000000..b2a042f3ed3d1de4c0281552531e4780e2c16187 Binary files /dev/null and b/target/classes/vslam/Mathworks_VSLAM_RGBD/VisualSLAMWithAnRGBDCameraExample.mlx differ diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/bagOfFeaturesDataSLAM.mat b/target/classes/vslam/Mathworks_VSLAM_RGBD/bagOfFeaturesDataSLAM.mat new file mode 100644 index 0000000000000000000000000000000000000000..bba0c9c9f9fced2771381f71adc28636701665c9 Binary files /dev/null and b/target/classes/vslam/Mathworks_VSLAM_RGBD/bagOfFeaturesDataSLAM.mat differ diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperAddLoopConnectionsStereo.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperAddLoopConnectionsStereo.m new file mode 100644 index 0000000000000000000000000000000000000000..5ddcc506b3caa8b678b41692fdd27289826c70d7 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperAddLoopConnectionsStereo.m @@ -0,0 +1,81 @@ +function [isLoopClosed, mapPoints, vSetKeyFrames] = helperAddLoopConnectionsStereo(... + mapPoints, vSetKeyFrames, loopCandidates, currKeyFrameId, currFeatures, ... + currPoints, loopEdgeNumMatches, varargin) +%helperAddLoopConnectionsStereo add connections between the current key frame and +% the valid loop candidate key frames. A loop candidate is valid if it has +% enough covisible map points with the current key frame. + +% This is an example helper function that is subject to change or removal +% in future releases. + +% Copyright 2019-2022 The MathWorks, Inc. + +if nargin > 7 + maxDistance = varargin{1}; +else + maxDistance = 4; +end + +loopClosureEdge = []; + +numCandidates = size(loopCandidates,2); +[index3d1, index2d1] = findWorldPointsInView(mapPoints, currKeyFrameId); +validFeatures1 = currFeatures.Features(index2d1, :); +validPoints1 = currPoints(index2d1, :); + +for k = 1 : numCandidates + [index3d2, index2d2] = findWorldPointsInView(mapPoints, loopCandidates(k)); + allFeatures2 = vSetKeyFrames.Views.Features{loopCandidates(k)}; + allPoints2 = vSetKeyFrames.Views.Points{loopCandidates(k)}; + validFeatures2 = allFeatures2(index2d2, :); + validPoints2 = allPoints2(index2d2, :); + + indexPairs = matchFeatures(binaryFeatures(validFeatures1), binaryFeatures(validFeatures2), ... + 'Unique', true, 'MaxRatio', 0.9, 'MatchThreshold', 40); + + % Orientation consistency check + orientation1 = validPoints1.Orientation(indexPairs(:,1)); + orientation2 = validPoints2.Orientation(indexPairs(:,2)); + [N, ~, bin] = histcounts(abs(orientation1 - orientation2), 0:pi/30:2*pi); + [~, ia] = maxk(N, 3); % Select the top 3 bins + isConsistent = ismember(bin, ia); + + indexPairs = indexPairs(isConsistent, :); + + % Check if all the candidate key frames have strong connection with the + % current keyframe + if size(indexPairs, 1) < loopEdgeNumMatches + continue + end + + % Estimate the relative pose of the current key frame with respect to the + % loop candidate keyframe with the highest similarity score + + worldPoints1 = mapPoints.WorldPoints(index3d1(indexPairs(:, 1)), :); + worldPoints2 = mapPoints.WorldPoints(index3d2(indexPairs(:, 2)), :); + + tform1 = pose2extr(vSetKeyFrames.Views.AbsolutePose(end)); + tform2 = pose2extr(vSetKeyFrames.Views.AbsolutePose(loopCandidates(k))); + + worldPoints1InCamera1 = transformPointsForward(tform1, worldPoints1); + worldPoints2InCamera2 = transformPointsForward(tform2, worldPoints2); + + w = warning('off','all'); + [tform, inlierIndex] = estgeotform3d(worldPoints1InCamera1, ... + worldPoints2InCamera2, 'rigid', 'MaxNumTrials', 1e4, 'MaxDistance', maxDistance); + warning(w); + + % Add connection between the current key frame and the loop key frame + matches = uint32([index2d2(indexPairs(inlierIndex, 2)), index2d1(indexPairs(inlierIndex, 1))]); + vSetKeyFrames = addConnection(vSetKeyFrames, loopCandidates(k), currKeyFrameId, tform, 'Matches', matches); + disp(['Loop edge added between keyframe: ', num2str(loopCandidates(k)), ' and ', num2str(currKeyFrameId)]); + + % Fuse co-visible map points + matchedIndex3d1 = index3d1(indexPairs(inlierIndex, 1)); + matchedIndex3d2 = index3d2(indexPairs(inlierIndex, 2)); + mapPoints = updateWorldPoints(mapPoints, matchedIndex3d1, mapPoints.WorldPoints(matchedIndex3d2, :)); + + loopClosureEdge = [loopClosureEdge; loopCandidates(k), currKeyFrameId]; +end +isLoopClosed = ~isempty(loopClosureEdge); +end \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperAddNewKeyFrame.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperAddNewKeyFrame.m new file mode 100644 index 0000000000000000000000000000000000000000..8171da4598e2f5e654d532de5f2eafe794b88a54 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperAddNewKeyFrame.m @@ -0,0 +1,54 @@ +function [mapPoints, vSetKeyFrames] = helperAddNewKeyFrame(mapPoints, vSetKeyFrames,... + cameraPose, currFeatures, currPoints, mapPointsIndices, featureIndices, keyFramesIndices) +%helperAddNewKeyFrame add key frames to the key frame set +% +% This is an example helper function that is subject to change or removal +% in future releases. + +% Copyright 2019-2023 The MathWorks, Inc. +%#codegen + +viewId = vSetKeyFrames.Views.ViewId(end)+1; + +vSetKeyFrames = addView(vSetKeyFrames, viewId, cameraPose,... + 'Features', currFeatures.Features, ... + 'Points', currPoints); + +viewsAbsPoses = vSetKeyFrames.Views.AbsolutePose; + +for i = 1:numel(keyFramesIndices) + localKeyFrameId = keyFramesIndices(i); + if isSimMode() + [index3d, index2d] = findWorldPointsInView(mapPoints, localKeyFrameId); + else + [index3dCg, index2dCg] = findWorldPointsInView(mapPoints, localKeyFrameId); + index3d = index3dCg{1}; + index2d = index2dCg{1}; + end + [~, ia, ib] = intersect(index3d, mapPointsIndices, 'stable'); + + prePose = viewsAbsPoses(localKeyFrameId); + relPose = rigidtform3d(prePose.R' * cameraPose.R, ... + (cameraPose.Translation-prePose.Translation)*prePose.R); + + if numel(ia) > 5 + if isSimMode() + vSetKeyFrames = addConnection(vSetKeyFrames, localKeyFrameId, viewId, relPose, ... + 'Matches', [index2d(ia),featureIndices(ib)]); + else + coder.varsize('matches', [inf 2], [1, 0]); + fIndices = featureIndices(ib(:)); + matches = [index2d(ia), fIndices]; + vSetKeyFrames = addConnection(vSetKeyFrames, localKeyFrameId, viewId, relPose, ... + 'Matches', matches); + end + end +end + +mapPoints = addCorrespondences(mapPoints, viewId, mapPointsIndices, ... + featureIndices); +end + +function tf = isSimMode() + tf = isempty(coder.target); +end \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperCheckLoopClosure.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperCheckLoopClosure.m new file mode 100644 index 0000000000000000000000000000000000000000..7cff3e85c2f308126c160e6d73176923a5b38914 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperCheckLoopClosure.m @@ -0,0 +1,58 @@ +function [isDetected, loopKeyFrameIds] = helperCheckLoopClosure(vSetKeyFrames, ... + currKeyframeId, imageDatabase, currImg, loopEdgeNumMatches) +%helperCheckLoopClosure detect loop candidates key frames by retrieving +% visually similar images from the feature database. +% +% This is an example helper function that is subject to change or removal +% in future releases. + +% Copyright 2019-2023 The MathWorks, Inc. +%#codegen + +% Retrieve all the visually similar key frames +[candidateViewIds, similarityscores] = retrieveImages(currImg, imageDatabase); + +% Compute similarity between the current key frame and its strongly-connected +% key frames. The minimum similarity score is used as a baseline to find +% loop candidate key frames, which are visually similar to but not connected +% to the current key frame +covisViews = connectedViews(vSetKeyFrames, currKeyframeId); +covisViewsIds = covisViews.ViewId; +strongCovisViews = connectedViews(vSetKeyFrames, currKeyframeId, 'MinNumMatches', loopEdgeNumMatches); +strongCovisViewIds = strongCovisViews.ViewId; + +% Retrieve the top 10 similar connected key frames +[~,~,scores] = evaluateImageRetrieval(currImg, imageDatabase, strongCovisViewIds, 'NumResults', 10); +minScore = min(scores); + +[loopKeyFrameIds,ia] = setdiff(candidateViewIds, covisViewsIds, 'stable'); + +% Scores of non-connected key frames +candidateScores = similarityscores(ia); % Descending + +if ~isempty(ia) + bestScore = candidateScores(1); + + % Score must be higher than the 75% of the best score + isValid = candidateScores > max(bestScore*0.75, minScore); + + loopKeyFrameIds = loopKeyFrameIds(isValid); +else + loopKeyFrameIds = zeros(coder.ignoreConst(0), coder.ignoreConst(0), class(loopKeyFrameIds)); +end + +% Loop candidates need to be consecutively detected +minNumCandidates = 3; % At least 3 candidates are found +if size(loopKeyFrameIds,1) >= minNumCandidates + groups = nchoosek(loopKeyFrameIds, minNumCandidates); + consecutiveGroups = groups(max(groups,[],2) - min(groups,[],2) < 4, :); + if ~isempty(consecutiveGroups) % Consecutive candidates are found + loopKeyFrameIds = consecutiveGroups(1,:); + isDetected = true; + else + isDetected = false; + end +else + isDetected = false; +end +end \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperCreateNewMapPointsStereo.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperCreateNewMapPointsStereo.m new file mode 100644 index 0000000000000000000000000000000000000000..c66582c070cc9b01fcf8964b53f70b124810d02d --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperCreateNewMapPointsStereo.m @@ -0,0 +1,257 @@ +function [mapPoints, vSetKeyFrames, recentPointIdx, stereoMapPointsIndices] = helperCreateNewMapPointsStereo(... + mapPoints, vSetKeyFrames, currKeyFrameId, intrinsics, scaleFactor, minNumMatches, minParallax, ... + unmatchedFeatureIdx, stereoMapPointsIndices) +%helperCreateNewMapPointsStereo creates new map points by triangulating matched +% feature points in the current key frame and the connected key frames. +% +% This is an example helper function that is subject to change or removal +% in future releases. + +% Copyright 2019-2022 The MathWorks, Inc. + +% Get connected key frames +KcViews = connectedViews(vSetKeyFrames, currKeyFrameId, minNumMatches); +KcIDs = KcViews.ViewId; + +% Retreive data of the current key frame +currPose = vSetKeyFrames.Views.AbsolutePose(currKeyFrameId); +currFeatures = vSetKeyFrames.Views.Features{currKeyFrameId}; +currPoints = vSetKeyFrames.Views.Points{currKeyFrameId}; +currLocations = currPoints.Location; +currScales = currPoints.Scale; + +% Camera projection matrix +currCamMatrix = cameraProjection(intrinsics, pose2extr(currPose)); + +recentPointIdx = []; + +for i = numel(KcIDs):-1:1 + + kfPose = vSetKeyFrames.Views.AbsolutePose(KcIDs(i)); + [~, kfIndex2d] = findWorldPointsInView(mapPoints, KcIDs(i)); + kfCamMatrix = cameraProjection(intrinsics, pose2extr(kfPose)); + + % Skip the key frame is the change of view is small + isViewClose = norm(kfPose.Translation - currPose.Translation) < 0.2; %baseline + if isViewClose + continue + end + + % Retrieve data of the connected key frame + kfFeatures = vSetKeyFrames.Views.Features{KcIDs(i)}; + kfPoints = vSetKeyFrames.Views.Points{KcIDs(i)}; + kfLocations = kfPoints.Location; + kfScales = kfPoints.Scale; + + % currIndex2d changes in each iteration as new map points are created + [~, currIndex2d] = findWorldPointsInView(mapPoints, currKeyFrameId); + + % Only use unmatched feature points + uIndices1 = setdiff(uint32(1:size(kfFeatures,1))', kfIndex2d); + uIndices2 = [setdiff(uint32(1:size(currFeatures,1))', currIndex2d); unmatchedFeatureIdx]; + + uFeatures1 = kfFeatures(uIndices1, :); + uFeatures2 = currFeatures(uIndices2, :); + + uLocations1 = kfLocations(uIndices1, :); + uLocations2 = currLocations(uIndices2, :); + + uScales1 = kfScales(uIndices1); + uScales2 = currScales(uIndices2); + + indexPairs = matchFeatures(binaryFeatures(uFeatures1), binaryFeatures(uFeatures2),... + 'Unique', true, 'MaxRatio', 0.7, 'MatchThreshold', 40); + + if isempty(indexPairs) + continue + end + + % Created from stereo + [~, ia, ib] = intersect(unmatchedFeatureIdx, uIndices2(indexPairs(:, 2))); + + isNewPointStereo = ~isempty(ia); + + if isNewPointStereo + sIndices1 = uIndices1(indexPairs(ib, 1)); + sIndices2 = unmatchedFeatureIdx(ia); + + % Update the indices + unmatchedFeatureIdx = setdiff(unmatchedFeatureIdx, sIndices2); + + % Filtering by view direction and reprojection error + xyzPoints = mapPoints.WorldPoints(stereoMapPointsIndices(ia), :); + + % Compute reprojection errors + [points1proj, isInFrontOfCam1] = projectPoints(xyzPoints, kfCamMatrix); + [points2proj, isInFrontOfCam2] = projectPoints(xyzPoints, currCamMatrix); + points1 = uLocations1(indexPairs(ib, 1), :)'; + points2 = uLocations2(indexPairs(ib, 2), :)'; + errors1 = hypot(points1(1,:)-points1proj(1,:), ... + points1(2,:) - points1proj(2,:)); + errors2 = hypot(points2(1,:)-points2proj(1,:), ... + points2(2,:) - points2proj(2,:)); + + reprojectionErrors = mean([errors1; errors2])'; + + isValid = checkEpipolarConstraint(intrinsics, currPose, kfPose, points1', points2', indexPairs(ib, :), uScales2); + + validIdx = isInFrontOfCam1 & isInFrontOfCam2 & isValid; + + inlier = filterTriangulatedMapPoints(xyzPoints, kfPose, currPose, ... + uScales1(indexPairs(ib, 1)), uScales2(indexPairs(ib, 2)), ... + reprojectionErrors, scaleFactor, validIdx); + + if any(inlier) + mapPoints = addCorrespondences(mapPoints, KcIDs(i), stereoMapPointsIndices(ia(inlier)), sIndices1(inlier)); + recentPointIdx = union(recentPointIdx, stereoMapPointsIndices(ia(inlier))); + recentPointIdx = recentPointIdx(:); + end + + % Created from triangulation + isNotPicked = true(size(indexPairs, 1), 1); + isNotPicked(ib(inlier)) = false; + indexPairs = indexPairs(isNotPicked, :); + end + + if isempty(indexPairs) + continue + end + + % Need to determine which way the new world points are created + matchedPoints1 = uLocations1(indexPairs(:,1), :); + matchedPoints2 = uLocations2(indexPairs(:,2), :); + + % Check epipolar constraint + isValid = checkEpipolarConstraint(intrinsics, currPose, kfPose, matchedPoints1, matchedPoints2, indexPairs, uScales2); + + indexPairs = indexPairs(isValid, :); + matchedPoints1 = matchedPoints1(isValid, :); + matchedPoints2 = matchedPoints2(isValid, :); + + % Parallax check + isLarge = isLargeParalalx(matchedPoints1, matchedPoints2, kfPose, ... + currPose, intrinsics, minParallax); + + matchedPoints1 = matchedPoints1(isLarge, :); + matchedPoints2 = matchedPoints2(isLarge, :); + indexPairs = indexPairs(isLarge, :); + + % Triangulate two views to create new world points + [xyzPoints, reprojectionErrors, validIdx] = triangulate(matchedPoints1, ... + matchedPoints2, kfCamMatrix, currCamMatrix); + + % Filtering by view direction and reprojection error + inlier = filterTriangulatedMapPoints(xyzPoints, kfPose, currPose, ... + uScales1(indexPairs(:,1)), uScales2(indexPairs(:,2)), ... + reprojectionErrors, scaleFactor, validIdx); + + % Add new map points and update connections + addedMatches = []; + if any(inlier) + xyzPoints = xyzPoints(inlier,:); + indexPairs = indexPairs(inlier, :); + + mIndices1 = uIndices1(indexPairs(:, 1)); + mIndices2 = uIndices2(indexPairs(:, 2)); + + [mapPoints, indices] = addWorldPoints(mapPoints, xyzPoints); + recentPointIdx = [recentPointIdx; indices]; %#ok + + % Add new observations + mapPoints = addCorrespondences(mapPoints, KcIDs(i),indices, mIndices1); + mapPoints = addCorrespondences(mapPoints, currKeyFrameId, indices, mIndices2); + + addedMatches = [mIndices1, mIndices2]; % Triangulation + end + + if isNewPointStereo + addedMatches = [sIndices1, sIndices2; addedMatches]; + end + + % Update connections with new feature matches + [~,ia] = intersect(vSetKeyFrames.Connections{:,1:2}, ... + [KcIDs(i), currKeyFrameId], 'row', 'stable'); + oldMatches = vSetKeyFrames.Connections.Matches{ia}; + newMatches = [oldMatches; addedMatches]; + vSetKeyFrames = updateConnection(vSetKeyFrames, KcIDs(i), currKeyFrameId, ... + 'Matches', newMatches); + +end + +stereoMapPointsIndices = setdiff(stereoMapPointsIndices, recentPointIdx); +end + +function F = computeF(intrinsics, pose1, pose2) +R1 = pose1.R; +t1 = pose1.Translation'; + +R2 = pose2.R; +t2 = pose2.Translation'; + +R12 = R1'*R2; +t12 = R1'*(t2-t1); + +% Skew symmetric matrix +t12x = [0, -t12(3), t12(2) + t12(3), 0, -t12(1) + -t12(2) t12(1), 0]; + +F = intrinsics.K'\ t12x * R12 / intrinsics.K; +end + +function inlier = filterTriangulatedMapPoints(xyzPoints, pose1, pose2, ... + scales1, scales2, reprojectionErrors, scaleFactor, isInFront) + +camToPoints1= xyzPoints - pose1.Translation; +camToPoints2= xyzPoints - pose2.Translation; + +% Check scale consistency and reprojection errors +distances1 = vecnorm(camToPoints1, 2, 2); +distances2 = vecnorm(camToPoints2, 2, 2); +ratioDist = distances1./distances2; +ratioScale = scales2./scales1; + +ratioFactor = 1.5 * scaleFactor; + +isInScale = (ratioDist./ratioScale < ratioFactor | ... + ratioScale./ratioDist < ratioFactor); + +maxError = sqrt(6); +isSmallError= reprojectionErrors < maxError*min(scales1, scales2); +inlier = isInScale & isSmallError & isInFront; +end + +function isLarge = isLargeParalalx(points1, points2, pose1, pose2, intrinsics, minParallax) + +% Parallax check +K = intrinsics.IntrinsicMatrix; +ray1 = [points1, ones(size(points1(:,1)))]/K *pose1.Rotation; +ray2 = [points2, ones(size(points1(:,2)))]/K *pose2.Rotation; + +cosParallax = sum(ray1 .* ray2, 2) ./(vecnorm(ray1, 2, 2) .* vecnorm(ray2, 2, 2)); +isLarge = cosParallax < cosd(minParallax) & cosParallax > 0; +end + +%-------------------------------------------------------------------------- +function [points2d, isInFrontOfCamera] = projectPoints(points3d, P) +points3dHomog = [points3d, ones(size(points3d, 1), 1, 'like', points3d)]'; +points2dHomog = P * points3dHomog; +isInFrontOfCamera = points2dHomog(3, :)' > 0; +points2d = bsxfun(@rdivide, points2dHomog(1:2, :), points2dHomog(3, :)); +end + +function isValid = checkEpipolarConstraint(intrinsics, currPose, kfPose, matchedPoints1, matchedPoints2, indexPairs, uScales2) +% Epipole in the current key frame +epiPole = world2img(kfPose.Translation, pose2extr(currPose), intrinsics); +distToEpipole = vecnorm(matchedPoints2 - epiPole, 2, 2); + +% Compute fundamental matrix +F = computeF(intrinsics, kfPose, currPose); + +% Epipolar line in the second image +epiLine = epipolarLine(F, matchedPoints2); +distToLine = abs(sum(epiLine.* [matchedPoints1, ones(size(matchedPoints1,1), 1)], 2))./... + sqrt(sum(epiLine(:,1:2).^2, 2)); +isValid = distToLine < 2*uScales2(indexPairs(:,2)) & ... + distToEpipole > 10*uScales2(indexPairs(:,2)); +end \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperLocalBundleAdjustmentStereo.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperLocalBundleAdjustmentStereo.m new file mode 100644 index 0000000000000000000000000000000000000000..1272b7951bbf8e6d80da44cd4b1a590038d46e4c --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperLocalBundleAdjustmentStereo.m @@ -0,0 +1,49 @@ +function [mapPoints, vSetKeyFrames, newPointIdx, stereoMapPointsIndices] = helperLocalBundleAdjustmentStereo(mapPoints, ... + vSetKeyFrames, currKeyFrameId, intrinsics, newPointIdx, stereoMapPointsIndices) +%helperLocalBundleAdjustmentStereo refine the pose of the current key frame and +% the map of the surrrounding scene. +% +% This is an example helper function that is subject to change or removal +% in future releases. + +% Copyright 2020-2022 The MathWorks, Inc. + +if currKeyFrameId > 2 + + [refinedViews, dist] = connectedViews(vSetKeyFrames, currKeyFrameId, MaxDistance=2); + refinedKeyFrameIds = refinedViews.ViewId; + + % Always fix the first two key frames + fixedViewIds = refinedKeyFrameIds(dist==2); + fixedViewIds = fixedViewIds(1:min(10, numel(fixedViewIds))); + + % Always fix the first two key frames + fixedViewIds = [fixedViewIds; intersect(refinedKeyFrameIds, [1 2])]; + + refinedKeyFrameIds = [refinedKeyFrameIds; currKeyFrameId]; + +else + refinedKeyFrameIds = [1 2]; + fixedViewIds = 1; +end + +% Refine local key frames and map points +[mapPoints, vSetKeyFrames, mapPointIdx, reprojectionErrors] = bundleAdjustment(... + mapPoints, vSetKeyFrames, refinedKeyFrameIds, intrinsics, 'FixedViewIDs', fixedViewIds, ... + 'PointsUndistorted', true, 'AbsoluteTolerance', 1e-7,... + 'RelativeTolerance', 1e-16, 'Solver', 'preconditioned-conjugate-gradient', ... + 'MaxIteration', 10); + +maxError = 6; +isInlier = reprojectionErrors < maxError; +outlierIdx = mapPointIdx(~isInlier); +newPointIdx = setdiff(newPointIdx, outlierIdx); + +% Update map points and key frames +if ~isempty(outlierIdx) + mapPoints = removeWorldPoints(mapPoints, outlierIdx); +end + +newPointIdx = newPointIdx - arrayfun(@(x) nnz(x>outlierIdx), newPointIdx); +stereoMapPointsIndices = stereoMapPointsIndices - arrayfun(@(x) nnz(x>outlierIdx), stereoMapPointsIndices); +end \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperORBFeatureExtractorFunction.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperORBFeatureExtractorFunction.m new file mode 100644 index 0000000000000000000000000000000000000000..d8c77bf675b0e62057d8b72b15581914ba951f22 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperORBFeatureExtractorFunction.m @@ -0,0 +1,25 @@ +function [features, featureMetrics]= helperORBFeatureExtractorFunction(I) +% helperORBFeatureExtractorFunction Implements the ORB feature extraction +% used in bagOfFeatures. +% +% This is an example helper function that is subject to change or removal +% in future releases. + +% Copyright 2021 The MathWorks, Inc. + +numPoints = 1000; + +% Detect ORB features +Igray = im2gray(I); + +points = detectORBFeatures(Igray, 'ScaleFactor', 1.2, 'NumLevels', 8); + +% Select a subset of features, uniformly distributed throughout the image +points = selectUniform(points, numPoints, size(Igray, 1:2)); + +% Extract features +features = extractFeatures(Igray, points); + +% Compute the Feature Metric. Use the variance of features as the metric +featureMetrics = var(single(features.Features),[],2); + diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperTrackLastKeyFrame.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperTrackLastKeyFrame.m new file mode 100644 index 0000000000000000000000000000000000000000..467ff8188bc13a55f385e8062267d67f5d77ff54 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperTrackLastKeyFrame.m @@ -0,0 +1,106 @@ +%helperTrackLastKeyFrame Estimate the camera pose by tracking the last key frame +% [currPose, mapPointIdx, featureIdx] = helperTrackLastKeyFrameStereo(mapPoints, +% views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor) estimates +% the camera pose of the current frame by matching features with the +% previous key frame. +% +% This is an example helper function that is subject to change or removal +% in future releases. +% +% Inputs +% ------ +% mapPoints - A helperMapPoints objects storing map points +% views - View attributes of key frames +% currFeatures - Features in the current frame +% currPoints - Feature points in the current frame +% lastKeyFrameId - ViewId of the last key frame +% intrinsics - Camera intrinsics +% scaleFactor - scale factor of features +% +% Outputs +% ------- +% currPose - Estimated camera pose of the current frame +% mapPointIdx - Indices of map points observed in the current frame +% featureIdx - Indices of features corresponding to mapPointIdx + +% Copyright 2019-2022 The MathWorks, Inc. + +function [currPose, mapPointIdx, featureIdx] = helperTrackLastKeyFrame(... + mapPoints, views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor) + +% Match features from the previous key frame with known world locations +[index3d, index2d] = findWorldPointsInView(mapPoints, lastKeyFrameId); +lastKeyFrameFeatures = views.Features{lastKeyFrameId}(index2d,:); +lastKeyFramePoints = views.Points{lastKeyFrameId}(index2d); + +indexPairs = matchFeatures(currFeatures, binaryFeatures(lastKeyFrameFeatures),... + 'Unique', true, 'MaxRatio', 0.9, 'MatchThreshold', 40); + +% Estimate the camera pose +matchedImagePoints = currPoints.Location(indexPairs(:,1),:); +matchedWorldPoints = mapPoints.WorldPoints(index3d(indexPairs(:,2)), :); + +matchedImagePoints = cast(matchedImagePoints, 'like', matchedWorldPoints); +[currPose, inlier, status] = estworldpose(... + matchedImagePoints, matchedWorldPoints, intrinsics, ... + 'Confidence', 95, 'MaxReprojectionError', 3, 'MaxNumTrials', 1e4); + +if status + currPose=[]; + mapPointIdx=[]; + featureIdx=[]; + return +end + +% Refine camera pose only +currPose = bundleAdjustmentMotion(matchedWorldPoints(inlier,:), ... + matchedImagePoints(inlier,:), currPose, intrinsics, ... + 'PointsUndistorted', true, 'AbsoluteTolerance', 1e-7,... + 'RelativeTolerance', 1e-15, 'MaxIteration', 20); + +% Search for more matches with the map points in the previous key frame +xyzPoints = mapPoints.WorldPoints(index3d,:); + +[projectedPoints, isInImage] = world2img(xyzPoints, pose2extr(currPose), intrinsics); +projectedPoints = projectedPoints(isInImage, :); + +minScales = max(1, lastKeyFramePoints.Scale(isInImage)/scaleFactor); +maxScales = lastKeyFramePoints.Scale(isInImage)*scaleFactor; +r = 4; +searchRadius = r*lastKeyFramePoints.Scale(isInImage); + +indexPairs = matchFeaturesInRadius(binaryFeatures(lastKeyFrameFeatures(isInImage,:)), ... + binaryFeatures(currFeatures.Features), currPoints, projectedPoints, searchRadius, ... + 'MatchThreshold', 40, 'MaxRatio', 0.8, 'Unique', true); + +if size(indexPairs, 1) < 20 + indexPairs = matchFeaturesInRadius(binaryFeatures(lastKeyFrameFeatures(isInImage,:)), ... + binaryFeatures(currFeatures.Features), currPoints, projectedPoints, 2*searchRadius, ... + 'MatchThreshold', 40, 'MaxRatio', 1, 'Unique', true); +end + +if size(indexPairs, 1) < 10 + currPose=[]; + mapPointIdx=[]; + featureIdx=[]; + return +end + +% Filter by scales +isGoodScale = currPoints.Scale(indexPairs(:, 2)) >= minScales(indexPairs(:, 1)) & ... + currPoints.Scale(indexPairs(:, 2)) <= maxScales(indexPairs(:, 1)); +indexPairs = indexPairs(isGoodScale, :); + +% Obtain the index of matched map points and features +tempIdx = find(isInImage); % Convert to linear index +mapPointIdx = index3d(tempIdx(indexPairs(:,1))); +featureIdx = indexPairs(:,2); + +% Refine the camera pose again +matchedWorldPoints = mapPoints.WorldPoints(mapPointIdx, :); +matchedImagePoints = currPoints.Location(featureIdx, :); + +currPose = bundleAdjustmentMotion(matchedWorldPoints, matchedImagePoints, ... + currPose, intrinsics, 'PointsUndistorted', true, 'AbsoluteTolerance', 1e-7,... + 'RelativeTolerance', 1e-15, 'MaxIteration', 20); +end \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperTrackLocalMap.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperTrackLocalMap.m new file mode 100644 index 0000000000000000000000000000000000000000..d64da7a28ae032e7fd6db8a0e0b689a2c90d06a6 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperTrackLocalMap.m @@ -0,0 +1,221 @@ +function [localKeyFrameIds, currPose, mapPointIdx, featureIdx, isKeyFrame] = ... + helperTrackLocalMap(mapPoints, vSetKeyFrames, mapPointIdx, ... + featureIdx, currPose, currFeatures, currPoints, intrinsics, scaleFactor, numLevels, ... + newKeyFrameAdded, lastKeyFrameIndex, currFrameIndex, numSkipFrames, numPointsKeyFrame) +%helperTrackLocalMap Refine camera pose by tracking the local map +% +% This is an example helper function that is subject to change or removal +% in future releases. +% +% Inputs +% ------ +% mapPoints - A worldpointset object storing map points +% vSetKeyFrames - An imageviewset storing key frames +% mapPointsIndices - Indices of map points observed in the current frame +% featureIndices - Indices of features in the current frame +% corresponding to map points denoted by mapPointsIndices +% currPose - Current camera pose +% currFeatures - ORB Features in the current frame +% currPoints - Feature points in the current frame +% intrinsics - Camera intrinsics +% scaleFactor - scale factor of features +% numLevels - number of levels in feature exatraction +% newKeyFrameAdded - A boolean scalar indicating if a new key frame is +% added recently +% lastKeyFrameIndex - Frame index of the last key frame +% currFrameIndex - Frame index of the current frame +% numSkipFrames - Largest number of frames to skip +% numPointsKeyFrame - Minimum number of points tracked by a key frame +% +% Outputs +% ------- +% localKeyFrameIds - ViewIds of the local key frames +% currPose - Refined camera pose of the current frame +% mapPointIdx - Indices of map points observed in the current frame +% featureIdx - Indices of features in the current frame corresponding +% to mapPointIdx +% isKeyFrame - A boolean scalar indicating if the current frame is +% a key frame + +% Copyright 2019-2022 The MathWorks, Inc. + +persistent numPointsRefKeyFrame localPointsIndices localKeyFrameIdsInternal + +if isempty(numPointsRefKeyFrame) || newKeyFrameAdded + [localPointsIndices, localKeyFrameIdsInternal, numPointsRefKeyFrame] = ... + updateRefKeyFrameAndLocalPoints(mapPoints, vSetKeyFrames, mapPointIdx); +end + +% Project the map into the frame and search for more map point correspondences +newMapPointIdx = setdiff(localPointsIndices, mapPointIdx, 'stable'); +localFeatures = getFeatures(mapPoints, vSetKeyFrames.Views, newMapPointIdx); +[projectedPoints, inlierIndex, predictedScales, viewAngles] = removeOutlierMapPoints(mapPoints, ... + currPose, intrinsics, newMapPointIdx, scaleFactor, numLevels); + +newMapPointIdx = newMapPointIdx(inlierIndex); +localFeatures = localFeatures(inlierIndex,:); + +unmatchedfeatureIdx = setdiff(cast((1:size( currFeatures.Features, 1)).', 'uint32'), ... + featureIdx,'stable'); +unmatchedFeatures = currFeatures.Features(unmatchedfeatureIdx, :); +unmatchedValidPoints= currPoints(unmatchedfeatureIdx); + +% Search radius depends on scale and view direction +searchRadius = 4*ones(size(localFeatures, 1), 1); +searchRadius(viewAngles<3) = 2.5; +searchRadius = searchRadius.*predictedScales; + +indexPairs = matchFeaturesInRadius(binaryFeatures(localFeatures),... + binaryFeatures(unmatchedFeatures), unmatchedValidPoints, projectedPoints, ... + searchRadius, 'MatchThreshold', 40, 'MaxRatio', 0.9, 'Unique', true); + +% Filter by scales +isGoodScale = currPoints.Scale(indexPairs(:, 2)) >= ... + max(1, predictedScales(indexPairs(:, 1))/scaleFactor) & ... + currPoints.Scale(indexPairs(:, 2)) <= predictedScales(indexPairs(:, 1)); +indexPairs = indexPairs(isGoodScale, :); + +% Refine camera pose with more 3D-to-2D correspondences +mapPointIdx = [newMapPointIdx(indexPairs(:,1)); mapPointIdx]; +featureIdx = [unmatchedfeatureIdx(indexPairs(:,2)); featureIdx]; +matchedMapPoints = mapPoints.WorldPoints(mapPointIdx,:); +matchedImagePoints = currPoints.Location(featureIdx,:); + +isKeyFrame = checkKeyFrame(numPointsRefKeyFrame, lastKeyFrameIndex, ... + currFrameIndex, mapPointIdx, numSkipFrames, numPointsKeyFrame); + +localKeyFrameIds = localKeyFrameIdsInternal; + +if isKeyFrame + % Refine camera pose only if the current frame is a key frame + currPose = bundleAdjustmentMotion(matchedMapPoints, matchedImagePoints, ... + currPose, intrinsics, 'PointsUndistorted', true, ... + 'AbsoluteTolerance', 1e-7, 'RelativeTolerance', 1e-16,'MaxIteration', 20); +end +end + +function [localPointsIndices, localKeyFrameIds, numPointsRefKeyFrame] = ... + updateRefKeyFrameAndLocalPoints(mapPoints, vSetKeyFrames, pointIndices) + +if vSetKeyFrames.NumViews == 1 + localKeyFrameIds = vSetKeyFrames.Views.ViewId; + localPointsIndices = (1:mapPoints.Count)'; + numPointsRefKeyFrame = mapPoints.Count; + return +end + +% The reference key frame has the most covisible map points +viewIds = findViewsOfWorldPoint(mapPoints, pointIndices); +refKeyFrameId = mode(vertcat(viewIds{:})); + +localKeyFrames = connectedViews(vSetKeyFrames, refKeyFrameId, "MaxDistance", 2); +localKeyFrameIds = [localKeyFrames.ViewId; refKeyFrameId]; + +pointIdx = findWorldPointsInView(mapPoints, localKeyFrameIds); +if iscell(pointIdx) + numPointsRefKeyFrame = numel(pointIdx{localKeyFrameIds==refKeyFrameId}); + localPointsIndices = sort(vertcat(pointIdx{:})); +else + numPointsRefKeyFrame = numel(pointIdx); + localPointsIndices = sort(pointIdx); +end +end + +function features = getFeatures(mapPoints, views, mapPointIdx) + +% Efficiently retrieve features and image points corresponding to map points +% denoted by mapPointIdx +allIndices = zeros(1, numel(mapPointIdx)); + +% ViewId and offset pair +count = []; % (ViewId, NumFeatures) +viewsFeatures = views.Features; + +for i = 1:numel(mapPointIdx) + index3d = mapPointIdx(i); + + viewId = double(mapPoints.RepresentativeViewId(index3d)); + + if isempty(count) + count = [viewId, size(viewsFeatures{viewId},1)]; + elseif ~any(count(:,1) == viewId) + count = [count; viewId, size(viewsFeatures{viewId},1)]; + end + + idx = find(count(:,1)==viewId); + + if idx > 1 + offset = sum(count(1:idx-1,2)); + else + offset = 0; + end + allIndices(i) = mapPoints.RepresentativeFeatureIndex(index3d) + offset; +end + +uIds = count(:,1); + +% Concatenating features and indexing once is faster than accessing via a for loop +allFeatures = vertcat(viewsFeatures{uIds}); +features = allFeatures(allIndices, :); +end + +function [projectedPoints, inliers, predictedScales, viewAngles] = removeOutlierMapPoints(... + mapPoints, pose, intrinsics, localPointsIndices, scaleFactor, ... + numLevels) + +% 1) Points within the image bounds +xyzPoints = mapPoints.WorldPoints(localPointsIndices, :); +[projectedPoints, isInImage] = world2img(xyzPoints, pose2extr(pose), intrinsics); + +if isempty(projectedPoints) + error('Tracking failed. Try inserting new key frames more frequently.') +end + +% 2) Parallax less than 60 degrees +cameraNormVector = [0 0 1] * pose.Rotation; +cameraToPoints = xyzPoints - pose.Translation; +viewDirection = mapPoints.ViewingDirection(localPointsIndices, :); +validByView = sum(viewDirection.*cameraToPoints, 2) > ... + cosd(60)*(vecnorm(cameraToPoints, 2, 2)); + +% 3) Distance from map point to camera center is in the range of scale +% invariant depth +minDist = mapPoints.DistanceLimits(localPointsIndices,1)/scaleFactor; +maxDist = mapPoints.DistanceLimits(localPointsIndices,2)*scaleFactor; +dist = vecnorm(xyzPoints - pose.Translation, 2, 2); + +validByDistance = dist > minDist & dist < maxDist; + +inliers = isInImage & validByView & validByDistance; + +% Predicted scales +level= ceil(log(maxDist ./ dist)./log(scaleFactor)); +level(level<0) = 0; +level(level>=numLevels-1) = numLevels-1; +predictedScales = scaleFactor.^level; + +% View angles +viewAngles = acosd(sum(cameraNormVector.*cameraToPoints, 2) ./ ... + vecnorm(cameraToPoints, 2, 2)); + +predictedScales = predictedScales(inliers); +viewAngles = viewAngles(inliers); + +projectedPoints = projectedPoints(inliers, :); +end + +function isKeyFrame = checkKeyFrame(numPointsRefKeyFrame, lastKeyFrameIndex, ... + currFrameIndex, mapPointsIndices, numSkipFrames, numPointsKeyFrame) + +% More than numSkipFrames frames have passed from last key frame insertion +tooManyNonKeyFrames = currFrameIndex > lastKeyFrameIndex + numSkipFrames; + +% Track less than numPointsKeyFrame map points +tooFewMapPoints = numel(mapPointsIndices) < numPointsKeyFrame; + +% Tracked map points are fewer than 90% of points tracked by +% the reference key frame +tooFewTrackedPoints = numel(mapPointsIndices) < 0.9 * numPointsRefKeyFrame; + +isKeyFrame = (tooManyNonKeyFrames || tooFewMapPoints) && tooFewTrackedPoints; +end \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMatchedFeaturesRGBD.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMatchedFeaturesRGBD.m new file mode 100644 index 0000000000000000000000000000000000000000..5aec70402a9a02803db91acb4e292a4e577e49cb --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMatchedFeaturesRGBD.m @@ -0,0 +1,56 @@ +classdef helperVisualizeMatchedFeaturesRGBD < handle +%helperVisualizeMatchedFeaturesRGBD show the matched features in a frame +% +% This is an example helper class that is subject to change or removal +% in future releases. + +% Copyright 2021 The MathWorks, Inc. + + properties (Access = private) + Image + + Feature + end + + methods (Access = public) + + function obj = helperVisualizeMatchedFeaturesRGBD(I1, I2, points) + + % Plot image + hFig = figure; + hAxes = newplot(hFig); + + % Set figure visibility and position + hFig.Visible = 'on'; + movegui(hFig, [200 200]); + + % Show the image and features + obj.Image = showMatchedFeatures(I1, I2, points, ... + points, 'montage', 'Parent', hAxes, ... + 'PlotOptions', {'g+','g+',''}); + title(hAxes, 'Matched Features in Current Frame'); + hold(hAxes, 'on'); + + obj.Feature = findobj(hAxes.Parent,'Type','Line'); + end + + function updatePlot(obj, I1, I2, points) + + % Color and depth image + obj.Image.CData = imfuse(I1, I2, 'montage'); + + % Connecting lines + obj.Feature(1).XData = NaN; + obj.Feature(1).YData = NaN; + + % Right image + obj.Feature(2).XData = points.Location(:,1) + size(I1, 2); + obj.Feature(2).YData = points.Location(:,2); + + % Left image + obj.Feature(3).XData = points.Location(:,1); + obj.Feature(3).YData = points.Location(:,2); + drawnow limitrate + end + end +end \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMotionAndStructure.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMotionAndStructure.m new file mode 100644 index 0000000000000000000000000000000000000000..b064c0480c02a1f23f6c64ff7d6a4dfe3c723953 --- /dev/null +++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMotionAndStructure.m @@ -0,0 +1,156 @@ +classdef helperVisualizeMotionAndStructure < handle +%helperVisualizeMatchedFeatures show map points and camera trajectory +% +% This is an example helper class that is subject to change or removal +% in future releases. + +% Copyright 2019-2022 The MathWorks, Inc. + + properties + XLim = [-1.5 1.5] + + YLim = [-1 0.5] + + ZLim = [-0.5 2] + + Axes + end + + properties (Access = private) + MapPointsPlot + + EstimatedTrajectory + + OptimizedTrajectory + + CameraPlot + end + + methods (Access = public) + function obj = helperVisualizeMotionAndStructure(vSetKeyFrames, mapPoints, varargin) + + if nargin > 2 + obj.XLim = varargin{1}; + obj.YLim = varargin{2}; + obj.ZLim = varargin{3}; + end + + [xyzPoints, currPose, trajectory] = retrievePlottedData(obj, vSetKeyFrames, mapPoints); + + obj.MapPointsPlot = pcplayer(obj.XLim, obj.YLim, obj.ZLim, ... + 'VerticalAxis', 'y', 'VerticalAxisDir', 'down'); + + obj.Axes = obj.MapPointsPlot.Axes; + obj.MapPointsPlot.view(xyzPoints); + obj.Axes.Children.DisplayName = 'Map points'; + + hold(obj.Axes, 'on'); + + % Set figure position on the screen + movegui(obj.Axes.Parent, [1000 200]); + + % Plot camera trajectory + obj.EstimatedTrajectory = plot3(obj.Axes, trajectory(:,1), trajectory(:,2), ... + trajectory(:,3), 'r', 'LineWidth', 2 , 'DisplayName', 'Estimated trajectory'); + + % Plot the current cameras + obj.CameraPlot = plotCamera(currPose, 'Parent', obj.Axes, 'Size', 0.05); + end + + function updatePlot(obj, vSetKeyFrames, mapPoints) + + [xyzPoints, currPose, trajectory] = retrievePlottedData(obj, vSetKeyFrames, mapPoints); + + % Update the point cloud + obj.MapPointsPlot.view(xyzPoints); + + % Update the camera trajectory + set(obj.EstimatedTrajectory, 'XData', trajectory(:,1), 'YData', ... + trajectory(:,2), 'ZData', trajectory(:,3)); + + % Update the current camera pose since the first camera is fixed + obj.CameraPlot.AbsolutePose = currPose.AbsolutePose; + obj.CameraPlot.Label = num2str(currPose.ViewId); + + drawnow limitrate + end + + function plotOptimizedTrajectory(obj, poses) + + % Delete the camera plot + delete(obj.CameraPlot); + + % Plot the optimized trajectory + trans = vertcat(poses.AbsolutePose.Translation); + obj.OptimizedTrajectory = plot3(obj.Axes, trans(:, 1), trans(:, 2), trans(:, 3), 'm', ... + 'LineWidth', 2, 'DisplayName', 'Optimized trajectory'); + end + + function plotActualTrajectory(obj, gTruth, optimizedPoses) + estimatedCams = vertcat(optimizedPoses.AbsolutePose.Translation); + actualCams = vertcat(gTruth.Translation); + scale = median(vecnorm(actualCams, 2, 2))/ median(vecnorm(estimatedCams, 2, 2)); + + % Update the plot based on the ground truth + updatePlotScale(obj, scale); + + % Plot the ground truth + plot3(obj.Axes, actualCams(:,1), actualCams(:,2), actualCams(:,3), ... + 'g','LineWidth',2, 'DisplayName', 'Actual trajectory'); + + drawnow limitrate + end + + function showLegend(obj) + % Add a legend to the axes + hLegend = legend(obj.Axes, 'Location', 'northeast', ... + 'TextColor', [1 1 1], 'FontWeight', 'bold'); + end + end + + methods (Access = private) + function [xyzPoints, currPose, trajectory] = retrievePlottedData(obj, vSetKeyFrames, mapPoints) + camPoses = poses(vSetKeyFrames); + currPose = camPoses(end,:); % Contains both ViewId and Pose + + % Ensure the rotation matrix is a rigid transformation + R = double(currPose.AbsolutePose.R); + t = double(currPose.AbsolutePose.Translation); + [U, ~, V] = svd(R); + currPose.AbsolutePose.A = eye(4); + currPose.AbsolutePose.A(1:3, 4) = t; + currPose.AbsolutePose.A(1:3, 1:3) = U * V'; + + trajectory = vertcat(camPoses.AbsolutePose.Translation); + xyzPoints = mapPoints.WorldPoints; + + % Only plot the points within the limit + inPlotRange = xyzPoints(:, 1) > obj.XLim(1) & ... + xyzPoints(:, 1) < obj.XLim(2) & xyzPoints(:, 2) > obj.YLim(1) & ... + xyzPoints(:, 2) < obj.YLim(2) & xyzPoints(:, 3) > obj.ZLim(1) & ... + xyzPoints(:, 3) < obj.ZLim(2); + xyzPoints = xyzPoints(inPlotRange, :); + end + + function updatePlotScale(obj, scale) + % Update the map points and camera trajectory based on the + % ground truth scale + obj.Axes.XLim = obj.Axes.XLim * scale; + obj.Axes.YLim = obj.Axes.YLim * scale; + obj.Axes.ZLim = obj.Axes.ZLim * scale; + + % Map points + obj.Axes.Children(end).XData = obj.Axes.Children(end).XData * scale; + obj.Axes.Children(end).YData = obj.Axes.Children(end).YData * scale; + obj.Axes.Children(end).ZData = obj.Axes.Children(end).ZData * scale; + + % Estiamted and optimized Camera trajectory + obj.EstimatedTrajectory.XData = obj.EstimatedTrajectory.XData * scale; + obj.EstimatedTrajectory.YData = obj.EstimatedTrajectory.YData * scale; + obj.EstimatedTrajectory.ZData = obj.EstimatedTrajectory.ZData * scale; + obj.OptimizedTrajectory.XData = obj.OptimizedTrajectory.XData * scale; + obj.OptimizedTrajectory.YData = obj.OptimizedTrajectory.YData * scale; + obj.OptimizedTrajectory.ZData = obj.OptimizedTrajectory.ZData * scale; + end + end +end \ No newline at end of file diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/orbslamGroundTruth.mat b/target/classes/vslam/Mathworks_VSLAM_RGBD/orbslamGroundTruth.mat new file mode 100644 index 0000000000000000000000000000000000000000..ea1360e39c14cb70268bf6d6d4202b51eaf02014 Binary files /dev/null and b/target/classes/vslam/Mathworks_VSLAM_RGBD/orbslamGroundTruth.mat differ diff --git a/target/classes/vslam/README.md b/target/classes/vslam/README.md new file mode 100644 index 0000000000000000000000000000000000000000..3a958ebcebb9cd8a0278721e6c043284b4e5cad3 --- /dev/null +++ b/target/classes/vslam/README.md @@ -0,0 +1,18 @@ + +## Notes + +Notes from Rohan: +- could use MATLAB coder to move MATLAB code to C/C++ code + - not sure if this is possible for Java code as well + - Prof. mentioned wanting Java code s.t. other students can read and critique codebase +- use MATLAB functions, create new MATLAB objects for data structures / database system +- dataset used by MATLAB example: https://cvg.cit.tum.de/data/datasets/rgbd-dataset + + +#### Performing VSLAM using online dataset + +- Open up MATLAB console +- Install necessary Mathworks Library: Vision, Visual SLAM (users will be queried to download necessary packages) +- In MATLAB console, set imagesPath to 'rgbd_dataset_freiburg3_long_office_household/rgb' +- Run the vslam_implementation.m script with the imagesPath as input +- Use output of worldPointSet for figuring out which key features belong to which objects diff --git a/target/classes/vslam/extractPointsByViewId.m b/target/classes/vslam/extractPointsByViewId.m new file mode 100644 index 0000000000000000000000000000000000000000..a48481586db5295c8e093d4ae17afbe866b42f11 --- /dev/null +++ b/target/classes/vslam/extractPointsByViewId.m @@ -0,0 +1,41 @@ +function extractPointsByViewId(viewId, worldPointSet) + % Define directories and file paths + % keyFramesDir = './KeyFrames'; + keyFramePointsDir = './KeyFramePoints'; + + % Construct filename for the image + % imageFilename = sprintf('%s/KeyFrame_%04d.png', keyFramesDir, viewId); + + % Load and display the image + % currImage = imread(imageFilename); + % figure; + % imshow(currImage); + % title(['Image for View ID: ', num2str(viewId)]); + % hold on; + + % Load corresponding CSV file for world point indices and pixel locations + csvFilename = sprintf('%s/KeyFramePoints_%04d.csv', keyFramePointsDir, viewId); + dataMatrix = readmatrix(csvFilename); + + % Extract pixel locations and indices of world points + % pixelLocations = dataMatrix(:, 1:2); % Assuming first two columns are pixel X, Y + mapPointsIdx = dataMatrix(:, 3); % Assuming third column is mapPointsIdx + + % Extract world points using the indices + worldPoints = worldPointSet.WorldPoints(mapPointsIdx, :); + + % Append world points to the CSV + updatedDataMatrix = [dataMatrix, worldPoints]; % Concatenate world points + writematrix(updatedDataMatrix, csvFilename); % Write it back + + % % Overlay features on the image + % plot(pixelLocations(:,1), pixelLocations(:,2), 'yo', 'MarkerSize', 5, 'LineWidth', 2); + % + % % Optionally save or display the image + % figure; + % imshow(currImage); + % hold on; + % plot(pixelLocations(:,1), pixelLocations(:,2), 'yo', 'MarkerSize', 5, 'LineWidth', 2); + % title('Features Overlayed on Image'); +end + diff --git a/target/classes/vslam/imperial_london/.DS_Store b/target/classes/vslam/imperial_london/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..500c87f9c4fd0368a46724d25cfbce39dcd42e55 Binary files /dev/null and b/target/classes/vslam/imperial_london/.DS_Store differ diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0002.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0002.csv new file mode 100644 index 0000000000000000000000000000000000000000..decf51081a53aef401e97f9e9a0b0edbd4b23460 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0002.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.952328,54,305,439,174 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0003.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0003.csv new file mode 100644 index 0000000000000000000000000000000000000000..88e4b192a091c35d764e96a34e9c1f84ca6a32b8 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0003.csv @@ -0,0 +1,3 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.965473,-12,307,437,171 +sofa,0.592514,576,322,64,156 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0004.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0004.csv new file mode 100644 index 0000000000000000000000000000000000000000..1570a6d50894d8e33b799fe10c04b13f25ddf77a --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0004.csv @@ -0,0 +1,3 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.982908,-5,315,358,164 +sofa,0.981918,456,338,185,141 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0005.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0005.csv new file mode 100644 index 0000000000000000000000000000000000000000..f9d8d81e0ac1cc595c2a899fa4138c8aeccfdc42 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0005.csv @@ -0,0 +1,3 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.988577,-4,315,313,163 +sofa,0.982338,403,332,238,149 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0006.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0006.csv new file mode 100644 index 0000000000000000000000000000000000000000..14f564513c5156ec49d0ba5c640ff7cf77a56224 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0006.csv @@ -0,0 +1,3 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.986512,-5,323,282,154 +sofa,0.969826,383,327,255,151 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0007.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0007.csv new file mode 100644 index 0000000000000000000000000000000000000000..276428057c9688cda616e999a9ca9a84b67264a9 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0007.csv @@ -0,0 +1,3 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.975408,325,327,314,150 +sofa,0.912207,1,332,220,146 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0008.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0008.csv new file mode 100644 index 0000000000000000000000000000000000000000..f777bec8e3a8c5c15c0f824b54dbad597147bfb3 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0008.csv @@ -0,0 +1,3 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.886575,297,272,338,149 +sofa,0.845557,0,268,195,209 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0009.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0009.csv new file mode 100644 index 0000000000000000000000000000000000000000..794da973557e21d080c2499d876950cec538c4b3 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0009.csv @@ -0,0 +1,3 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.965334,267,213,370,144 +sofa,0.519108,0,207,155,272 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0010.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0010.csv new file mode 100644 index 0000000000000000000000000000000000000000..6041f1ef5fb7cfb131b6989cc3050c8668af9545 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0010.csv @@ -0,0 +1,3 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.972942,229,199,395,152 +diningtable,0.634724,353,337,288,143 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0011.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0011.csv new file mode 100644 index 0000000000000000000000000000000000000000..b47a62f52c0115ec2177fee8fb9dadd6cd6f1e53 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0011.csv @@ -0,0 +1,3 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.978026,232,181,393,170 +diningtable,0.623284,389,315,249,168 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0012.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0012.csv new file mode 100644 index 0000000000000000000000000000000000000000..a7e6b4160b7b05f757aaedad5e28283afb5e3103 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0012.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.976634,231,199,391,180 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0013.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0013.csv new file mode 100644 index 0000000000000000000000000000000000000000..b0e23079a1f06d0182ff90241c83e5e1c368e5ce --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0013.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.962698,346,202,293,186 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0014.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0014.csv new file mode 100644 index 0000000000000000000000000000000000000000..0cd4e477267128e14370db98897abef072ec6e16 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0014.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.869272,478,191,160,208 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0015.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0015.csv new file mode 100644 index 0000000000000000000000000000000000000000..0921044a1f6a5bad072afcd19a6221f1326025fd --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0015.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.786228,510,187,130,210 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0016.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0016.csv new file mode 100644 index 0000000000000000000000000000000000000000..768bb469a95b331765bfc70d62b9f38acb5a11ed --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0016.csv @@ -0,0 +1,3 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.710312,535,181,104,211 +sofa,0.671818,-11,171,481,303 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0017.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0017.csv new file mode 100644 index 0000000000000000000000000000000000000000..a6288b9c3d838387be183e49b90b61ddd3dfbd27 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0017.csv @@ -0,0 +1 @@ +Class,Confidence,X,Y,Width,Height diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0018.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0018.csv new file mode 100644 index 0000000000000000000000000000000000000000..d9cf9595171a0bee47e09ed42afb010c29a02df5 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0018.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.567392,-9,183,539,304 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0019.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0019.csv new file mode 100644 index 0000000000000000000000000000000000000000..a6288b9c3d838387be183e49b90b61ddd3dfbd27 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0019.csv @@ -0,0 +1 @@ +Class,Confidence,X,Y,Width,Height diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0020.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0020.csv new file mode 100644 index 0000000000000000000000000000000000000000..99439e02160fab5eaede65bbed9d2f3ae1041c03 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0020.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +bed,0.544073,7,187,566,299 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0021.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0021.csv new file mode 100644 index 0000000000000000000000000000000000000000..a6288b9c3d838387be183e49b90b61ddd3dfbd27 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0021.csv @@ -0,0 +1 @@ +Class,Confidence,X,Y,Width,Height diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0022.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0022.csv new file mode 100644 index 0000000000000000000000000000000000000000..a6288b9c3d838387be183e49b90b61ddd3dfbd27 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0022.csv @@ -0,0 +1 @@ +Class,Confidence,X,Y,Width,Height diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0023.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0023.csv new file mode 100644 index 0000000000000000000000000000000000000000..a6288b9c3d838387be183e49b90b61ddd3dfbd27 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0023.csv @@ -0,0 +1 @@ +Class,Confidence,X,Y,Width,Height diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0024.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0024.csv new file mode 100644 index 0000000000000000000000000000000000000000..6c65d03305c31cd2e77f55ff47813bc23d8fe719 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0024.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.639918,-6,152,308,328 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0025.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0025.csv new file mode 100644 index 0000000000000000000000000000000000000000..a6288b9c3d838387be183e49b90b61ddd3dfbd27 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0025.csv @@ -0,0 +1 @@ +Class,Confidence,X,Y,Width,Height diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0026.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0026.csv new file mode 100644 index 0000000000000000000000000000000000000000..1a771f1ff124e92a92265c3fcc121da0132b9e17 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0026.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.716166,532,198,108,225 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0027.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0027.csv new file mode 100644 index 0000000000000000000000000000000000000000..3ba73b2950cd2fa027ed40183c342a85c817b01a --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0027.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.675142,511,210,129,200 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0028.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0028.csv new file mode 100644 index 0000000000000000000000000000000000000000..89c06f1b64ee26e0aa05ac5f9ed6f6b888c1e493 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0028.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.895447,455,205,183,200 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0029.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0029.csv new file mode 100644 index 0000000000000000000000000000000000000000..551ce0a525c239a103d39bf5867d3d0f1fc16120 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0029.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.974082,250,211,369,179 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0030.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0030.csv new file mode 100644 index 0000000000000000000000000000000000000000..8570b2b7d886f6e7b4922037d272505f842706ed --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0030.csv @@ -0,0 +1,4 @@ +Class,Confidence,X,Y,Width,Height +chair,0.995655,425,254,85,93 +sofa,0.952357,-1,244,376,210 +diningtable,0.642641,312,340,326,139 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0031.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0031.csv new file mode 100644 index 0000000000000000000000000000000000000000..f8ea73b4b0adb0388f643c1a01e29324c1d046d7 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0031.csv @@ -0,0 +1,4 @@ +Class,Confidence,X,Y,Width,Height +sofa,0.992697,-2,251,278,225 +chair,0.991532,323,252,85,101 +diningtable,0.789564,224,344,413,135 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0032.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0032.csv new file mode 100644 index 0000000000000000000000000000000000000000..85fcc835e323bd7b44a06582685ce60d65f17e50 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0032.csv @@ -0,0 +1,5 @@ +Class,Confidence,X,Y,Width,Height +chair,0.996181,242,257,88,122 +sofa,0.987450,0,256,189,223 +diningtable,0.893306,154,361,470,123 +bowl,0.761200,310,383,150,55 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0033.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0033.csv new file mode 100644 index 0000000000000000000000000000000000000000..49d9bde1de61f8177ce6e5e2cea4a1594ce7278b --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0033.csv @@ -0,0 +1,4 @@ +Class,Confidence,X,Y,Width,Height +chair,0.991804,110,296,104,134 +diningtable,0.866755,50,409,584,71 +chair,0.813645,541,294,99,155 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0034.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0034.csv new file mode 100644 index 0000000000000000000000000000000000000000..77c6264e95339b8dc35ee4c3f0ee37133a3f79b7 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0034.csv @@ -0,0 +1,4 @@ +Class,Confidence,X,Y,Width,Height +chair,0.964840,6,299,125,149 +chair,0.964839,462,284,126,148 +diningtable,0.740993,1,407,624,72 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0035.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0035.csv new file mode 100644 index 0000000000000000000000000000000000000000..f0eb6525685a8e521f4a00418082cee7e704372b --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0035.csv @@ -0,0 +1,3 @@ +Class,Confidence,X,Y,Width,Height +chair,0.987398,384,273,121,139 +diningtable,0.748576,1,397,616,83 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0036.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0036.csv new file mode 100644 index 0000000000000000000000000000000000000000..f56bace50f3d56535bffaff195368144f5dcff99 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0036.csv @@ -0,0 +1,4 @@ +Class,Confidence,X,Y,Width,Height +chair,0.990667,314,277,116,143 +vase,0.990550,571,289,68,77 +tvmonitor,0.921570,508,133,132,146 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0037.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0037.csv new file mode 100644 index 0000000000000000000000000000000000000000..9361cd97c6529588295a5e137489ed80304a8bb0 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0037.csv @@ -0,0 +1,4 @@ +Class,Confidence,X,Y,Width,Height +vase,0.994073,516,285,65,76 +chair,0.985533,256,276,118,149 +tvmonitor,0.833849,450,119,188,158 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0038.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0038.csv new file mode 100644 index 0000000000000000000000000000000000000000..080cfdcc0119ce77f4270e2bd1ccc40c75585f02 --- /dev/null +++ b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0038.csv @@ -0,0 +1,4 @@ +Class,Confidence,X,Y,Width,Height +vase,0.993365,454,287,62,74 +chair,0.981193,184,282,127,157 +tvmonitor,0.701652,397,135,196,140 diff --git a/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0039.csv b/target/classes/vslam/imperial_london/BoundedInfo/KeyFrame_0039.csv new file mode 100644 index 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+Class,Confidence,X,Y,Width,Height +chair,0.991244,151,270,183,204 +chair,0.977068,427,218,173,186 +bottle,0.936772,341,34,19,78 +book,0.903235,314,208,54,36 +bottle,0.901248,240,42,24,72 +bottle,0.894778,329,35,15,73 +bottle,0.880812,402,136,18,50 +book,0.807948,249,147,21,71 +bottle,0.806649,421,142,12,38 +bottle,0.784035,374,133,15,57 +bottle,0.747702,215,39,19,70 +book,0.698251,236,146,17,70 +book,0.649110,273,146,15,70 +cup,0.636067,562,189,23,25 +bottle,0.550091,383,121,14,54 +sports ball,0.540607,207,200,46,52 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0006.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0006.csv new file mode 100644 index 0000000000000000000000000000000000000000..5472f02470111e4ca5b7f64534e4e37b8bd078e2 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0006.csv @@ -0,0 +1,12 @@ +Class,Confidence,X,Y,Width,Height +chair,0.975160,226,268,176,205 +bottle,0.953051,376,6,20,78 +bottle,0.945507,391,5,23,84 +bottle,0.941225,289,12,26,80 +bottle,0.899972,455,115,18,54 +chair,0.861566,481,200,158,199 +bottle,0.835486,471,124,11,41 +bottle,0.788429,260,8,21,78 +bottle,0.737901,428,101,25,64 +book,0.704844,373,195,54,36 +book,0.678914,294,125,37,80 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0007.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0007.csv new file mode 100644 index 0000000000000000000000000000000000000000..cba5486bad94b2fe160fddcbbe6f4a3227f41413 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0007.csv @@ -0,0 +1,12 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.979044,378,8,25,96 +bottle,0.967433,267,21,30,94 +bottle,0.964849,359,10,24,91 +chair,0.908203,236,341,182,136 +book,0.863367,369,221,67,42 +bottle,0.850949,233,16,23,88 +chair,0.705046,479,216,162,211 +bottle,0.698702,418,114,21,81 +book,0.612678,280,150,31,87 +book,0.537183,316,149,17,84 +bottle,0.533482,436,133,14,50 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0008.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0008.csv new file mode 100644 index 0000000000000000000000000000000000000000..ebc46983014ea8d5d4c43ded15f76429c3260445 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0008.csv @@ -0,0 +1,10 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.991148,342,34,27,104 +bottle,0.990311,318,37,27,96 +book,0.934545,349,267,87,52 +bottle,0.920227,222,55,38,105 +bottle,0.790026,412,160,23,64 +bottle,0.775506,176,49,32,97 +book,0.692979,253,199,59,92 +book,0.654873,243,200,34,96 +book,0.514031,229,209,28,93 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0009.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0009.csv new file mode 100644 index 0000000000000000000000000000000000000000..48edfd1a8e6d5cdbbd50da3b0b1795aa7a1e4a28 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0009.csv @@ -0,0 +1,10 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.982832,168,36,49,125 +bottle,0.965569,267,21,31,107 +bottle,0.948319,298,16,30,115 +book,0.944805,322,273,110,66 +book,0.819436,222,204,56,126 +bottle,0.732490,368,159,26,64 +chair,0.669043,426,219,203,234 +book,0.638524,190,221,38,120 +book,0.573994,258,200,32,110 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0010.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0010.csv new file mode 100644 index 0000000000000000000000000000000000000000..d07542a4e20d36d6c25d19914ce5289451bc4ae5 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0010.csv @@ -0,0 +1,8 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.991636,306,7,32,120 +bottle,0.991530,341,3,31,126 +bottle,0.982920,217,24,53,136 +book,0.943158,376,273,126,70 +book,0.710189,285,200,58,138 +scissors,0.679922,447,243,25,29 +book,0.628074,254,220,47,127 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0011.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0011.csv new file mode 100644 index 0000000000000000000000000000000000000000..74cc45c45ad44dccd301d51f52d2ddcb0906fa21 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0011.csv @@ -0,0 +1,7 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.966262,330,-1,34,113 +bottle,0.965202,266,14,47,135 +book,0.880435,411,252,124,64 +bottle,0.784961,367,0,31,117 +book,0.726390,324,190,62,137 +book,0.585340,304,207,46,120 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0012.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0012.csv new file mode 100644 index 0000000000000000000000000000000000000000..9f7642e31c90f2a4d33da90d425e028a3c27bb7d --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0012.csv @@ -0,0 +1,8 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.984907,369,25,34,105 +bottle,0.962553,400,25,38,109 +book,0.875409,439,259,105,58 +bottle,0.859166,341,39,32,119 +book,0.807379,376,194,40,128 +book,0.617287,359,211,32,115 +chair,0.506381,425,410,215,69 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0013.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0013.csv new file mode 100644 index 0000000000000000000000000000000000000000..fb35e5f156b72ba4076740253ac39d0a6a4478c0 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0013.csv @@ -0,0 +1,6 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.935593,428,12,34,106 +book,0.856403,413,177,31,113 +bottle,0.832295,408,15,21,93 +book,0.624023,429,171,31,104 +chair,0.533993,482,355,157,124 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0014.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0014.csv new file mode 100644 index 0000000000000000000000000000000000000000..d0d75f423d1b8fae45a53da560aac94910a24ae8 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0014.csv @@ -0,0 +1,3 @@ +Class,Confidence,X,Y,Width,Height +book,0.748623,410,152,41,118 +chair,0.728600,498,319,139,161 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0015.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0015.csv new file mode 100644 index 0000000000000000000000000000000000000000..25b75d4065fe78caf8431468ba262161ff743e82 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0015.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +chair,0.915603,470,260,171,216 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0016.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0016.csv new file mode 100644 index 0000000000000000000000000000000000000000..6c9f3ad141fc237f510f84bb02aadcf4a5b7e286 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0016.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +chair,0.915032,476,245,166,233 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0017.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0017.csv new file mode 100644 index 0000000000000000000000000000000000000000..0d3251f8d4f84f801fc447d2b0fc294a0b630173 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0017.csv @@ -0,0 +1,3 @@ +Class,Confidence,X,Y,Width,Height +chair,0.867054,479,241,164,234 +teddy bear,0.759920,114,85,76,99 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0018.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0018.csv new file mode 100644 index 0000000000000000000000000000000000000000..7fd311c7f7d7ae5cf19bf9213f09f74e9e285064 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0018.csv @@ -0,0 +1,5 @@ +Class,Confidence,X,Y,Width,Height +teddy bear,0.921366,70,83,77,108 +chair,0.870267,464,165,176,249 +book,0.618901,129,166,62,26 +tvmonitor,0.506349,185,79,55,121 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0019.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0019.csv new file mode 100644 index 0000000000000000000000000000000000000000..a95976954f01e2f4dd1f38b60cecd4278455a534 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0019.csv @@ -0,0 +1,7 @@ +Class,Confidence,X,Y,Width,Height +teddy bear,0.918642,42,78,85,124 +chair,0.908298,469,139,171,240 +tvmonitor,0.861915,193,69,46,117 +mouse,0.610153,102,253,34,20 +book,0.517391,122,164,69,29 +book,0.507250,153,195,102,41 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0020.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0020.csv new file mode 100644 index 0000000000000000000000000000000000000000..7a35bd4f52ff4ba64c712072154ceccf0380559f --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0020.csv @@ -0,0 +1,4 @@ +Class,Confidence,X,Y,Width,Height +teddy bear,0.928609,-1,92,77,115 +chair,0.893634,431,138,185,223 +mouse,0.684753,69,265,40,22 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0021.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0021.csv new file mode 100644 index 0000000000000000000000000000000000000000..c3fd4dc128c6377be157d7421548f16c7a416c26 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0021.csv @@ -0,0 +1,4 @@ +Class,Confidence,X,Y,Width,Height +mouse,0.988700,95,271,36,20 +chair,0.700106,431,144,157,212 +teddy bear,0.587217,-1,100,61,117 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0022.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0022.csv new file mode 100644 index 0000000000000000000000000000000000000000..89b7782fe8cd05ef6121dd881f5d9a621eb39dd7 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0022.csv @@ -0,0 +1,7 @@ +Class,Confidence,X,Y,Width,Height +mouse,0.992161,190,274,36,21 +teddy bear,0.940446,14,101,99,119 +chair,0.867481,-1,283,167,197 +keyboard,0.862832,174,215,73,55 +book,0.592142,213,182,53,25 +chair,0.523947,499,153,136,208 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0023.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0023.csv new file mode 100644 index 0000000000000000000000000000000000000000..5f82a6f3e9530523e5fd5d6c60b781acd49ba6d1 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0023.csv @@ -0,0 +1,12 @@ +Class,Confidence,X,Y,Width,Height +mouse,0.977467,238,251,36,20 +keyboard,0.950393,201,195,84,53 +keyboard,0.938995,178,131,40,30 +chair,0.930092,4,258,210,221 +tvmonitor,0.753839,274,66,70,115 +teddy bear,0.742930,15,84,111,123 +chair,0.659686,534,117,105,209 +book,0.646415,231,159,60,30 +book,0.579811,175,163,60,37 +cup,0.576244,370,165,32,20 +tvmonitor,0.566574,203,61,38,74 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0024.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0024.csv new file mode 100644 index 0000000000000000000000000000000000000000..ffbec9a190c372bc19567facf42a74d118109f59 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0024.csv @@ -0,0 +1,9 @@ +Class,Confidence,X,Y,Width,Height +mouse,0.992864,188,272,39,23 +tvmonitor,0.914497,89,69,56,91 +keyboard,0.829594,127,218,101,51 +tvmonitor,0.764003,179,73,105,124 +chair,0.738410,473,85,85,202 +keyboard,0.636108,74,156,52,30 +mouse,0.611088,216,202,29,31 +chair,0.546050,1,307,167,172 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0025.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0025.csv new file mode 100644 index 0000000000000000000000000000000000000000..eccbd69d54cc1a16e29a2b8d208e4771e0e0668c --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0025.csv @@ -0,0 +1,9 @@ +Class,Confidence,X,Y,Width,Height +mouse,0.986098,150,298,39,29 +keyboard,0.975784,59,237,126,59 +book,0.919274,1,211,91,51 +tvmonitor,0.821281,104,75,136,164 +bottle,0.787676,201,205,29,65 +chair,0.785182,426,73,68,198 +tvmonitor,0.766901,-1,79,58,91 +book,0.536501,74,184,79,42 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0026.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0026.csv new file mode 100644 index 0000000000000000000000000000000000000000..3dabc0044f38fb70f8c36d2c15b89a824cab6aa0 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0026.csv @@ -0,0 +1,4 @@ +Class,Confidence,X,Y,Width,Height +mouse,0.973950,52,373,52,42 +bottle,0.883179,108,254,36,81 +chair,0.663597,362,99,23,76 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0027.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0027.csv new file mode 100644 index 0000000000000000000000000000000000000000..2c8d94d4b2d778dce155bd02fda2c30295a3aa8a --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0027.csv @@ -0,0 +1,5 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.967445,60,262,47,94 +mouse,0.948472,5,404,64,63 +refrigerator,0.662003,328,-1,90,87 +book,0.646098,193,186,112,67 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0028.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0028.csv new file mode 100644 index 0000000000000000000000000000000000000000..b76d943d61f5637e485e9f85fc60ffb826af02a4 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0028.csv @@ -0,0 +1,4 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.969635,157,257,48,112 +mouse,0.734208,110,415,57,63 +keyboard,0.631240,0,323,130,98 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0029.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0029.csv new file mode 100644 index 0000000000000000000000000000000000000000..0bcb922238dae5fd7445d5e3e041d2ba405490be --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0029.csv @@ -0,0 +1,6 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.987263,285,281,42,115 +keyboard,0.975372,1,302,242,148 +tvmonitor,0.967129,64,29,282,304 +book,0.866326,0,211,117,73 +book,0.578921,463,226,177,86 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0030.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0030.csv new file mode 100644 index 0000000000000000000000000000000000000000..154b5788d0e8b8c4e83b92870d6dff3b9d61a0e6 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0030.csv @@ -0,0 +1,9 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.995250,426,273,63,135 +keyboard,0.977495,97,251,280,198 +mouse,0.968501,26,168,67,26 +book,0.934197,113,150,130,73 +book,0.922402,-3,175,156,119 +tvmonitor,0.886913,219,-4,359,320 +tvmonitor,0.862711,0,-1,88,110 +keyboard,0.679393,0,84,61,77 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0031.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0031.csv new file mode 100644 index 0000000000000000000000000000000000000000..1acba5f731d2766511c52b18de3a078d52652946 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0031.csv @@ -0,0 +1,11 @@ +Class,Confidence,X,Y,Width,Height +mouse,0.995033,74,149,51,23 +keyboard,0.940059,209,245,287,210 +book,0.929667,104,161,161,102 +keyboard,0.901127,67,67,113,72 +tvmonitor,0.890707,331,-8,306,348 +book,0.846032,225,138,128,74 +tvmonitor,0.782391,119,-2,88,90 +bottle,0.761804,553,299,86,145 +mouse,0.711269,152,312,47,50 +mouse,0.593742,145,147,59,24 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0032.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0032.csv new file mode 100644 index 0000000000000000000000000000000000000000..500a5370b6764fb938a17ec03579b9a1d65e0f9d --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0032.csv @@ -0,0 +1,10 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.983317,193,114,100,68 +mouse,0.981905,200,192,47,23 +keyboard,0.978130,327,302,311,177 +book,0.938540,231,209,157,100 +book,0.914894,346,192,130,75 +tvmonitor,0.738426,458,4,182,363 +tvmonitor,0.712951,239,1,108,133 +chair,0.588148,-1,86,171,359 +mouse,0.509890,266,194,57,24 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0033.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0033.csv new file mode 100644 index 0000000000000000000000000000000000000000..e88374395b272386a91024e9ac66016589243fa4 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0033.csv @@ -0,0 +1,11 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.997562,212,137,111,68 +keyboard,0.996383,410,308,229,170 +mouse,0.992464,241,218,47,22 +book,0.947921,286,227,160,99 +tvmonitor,0.859953,503,3,136,323 +book,0.806508,361,170,110,49 +book,0.805319,395,199,123,76 +tvmonitor,0.666292,258,8,103,147 +book,0.539590,314,291,135,49 +mouse,0.505975,312,213,51,27 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0034.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0034.csv new file mode 100644 index 0000000000000000000000000000000000000000..377754835c367b11e6da34ed0e5a91385957ce07 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0034.csv @@ -0,0 +1,8 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.996964,188,154,123,63 +mouse,0.992975,244,231,44,24 +keyboard,0.987773,440,296,200,131 +book,0.963011,307,225,153,114 +tvmonitor,0.926246,496,6,143,311 +book,0.790831,399,194,105,73 +tvmonitor,0.775170,225,26,112,130 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0035.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0035.csv new file mode 100644 index 0000000000000000000000000000000000000000..8cdd79148d894016875b1b5a217bd1d22995fe22 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0035.csv @@ -0,0 +1,10 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.997949,147,156,136,59 +mouse,0.996970,236,228,42,28 +keyboard,0.990181,462,264,176,96 +book,0.965534,313,205,149,111 +tvmonitor,0.956561,166,19,126,137 +tvmonitor,0.930411,469,-3,171,276 +mouse,0.815282,307,208,38,27 +book,0.785083,383,169,96,63 +chair,0.520709,0,211,208,258 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0036.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0036.csv new file mode 100644 index 0000000000000000000000000000000000000000..4b70357de2f272797735dccfb5be7b24e0b29dcd --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0036.csv @@ -0,0 +1,8 @@ +Class,Confidence,X,Y,Width,Height +mouse,0.997674,204,214,41,29 +keyboard,0.996554,80,146,156,55 +keyboard,0.987407,451,230,189,80 +tvmonitor,0.934023,431,-1,209,219 +book,0.928793,295,182,142,106 +tvmonitor,0.851107,80,3,160,129 +cell phone,0.581624,278,188,33,38 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0037.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0037.csv new file mode 100644 index 0000000000000000000000000000000000000000..744ad122c3b5f1843c7fc8a6b62b7aef39dc092c --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0037.csv @@ -0,0 +1,8 @@ +Class,Confidence,X,Y,Width,Height +mouse,0.998367,207,246,47,40 +keyboard,0.991541,48,166,186,64 +keyboard,0.984209,500,255,141,81 +book,0.869997,324,210,154,120 +tvmonitor,0.668058,457,-1,185,223 +tvmonitor,0.656260,14,0,223,173 +cell phone,0.645459,293,211,31,42 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0038.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0038.csv new file mode 100644 index 0000000000000000000000000000000000000000..367ffe7acf81c1ac590c72fe3b0f01269cc58fe7 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0038.csv @@ -0,0 +1,8 @@ +Class,Confidence,X,Y,Width,Height +mouse,0.998042,132,306,53,52 +keyboard,0.992938,448,276,190,88 +keyboard,0.990395,1,225,151,64 +tvmonitor,0.954444,390,1,250,213 +tvmonitor,0.867936,-1,15,149,191 +book,0.712787,266,247,160,139 +cell phone,0.527076,226,254,29,65 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0039.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0039.csv new file mode 100644 index 0000000000000000000000000000000000000000..9fbb6f7383bf4fa1fe16433504d41cbb8bcdfaf1 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0039.csv @@ -0,0 +1,7 @@ +Class,Confidence,X,Y,Width,Height +mouse,0.993252,32,330,72,70 +keyboard,0.983607,423,295,217,113 +keyboard,0.958430,0,227,68,78 +tvmonitor,0.934154,350,1,288,219 +tvmonitor,0.864281,0,2,59,221 +book,0.538316,265,265,130,160 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0040.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0040.csv new file mode 100644 index 0000000000000000000000000000000000000000..b08f031a5f7483fb4e781508a345add6a3282a34 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0040.csv @@ -0,0 +1,5 @@ +Class,Confidence,X,Y,Width,Height +mouse,0.996772,93,321,77,72 +keyboard,0.988262,-1,155,164,129 +tvmonitor,0.902315,-2,-1,170,171 +book,0.683100,343,310,166,168 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0041.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0041.csv new file mode 100644 index 0000000000000000000000000000000000000000..9370653d4ab8be62e8bf3d1ea2d0f25f314ac51e --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0041.csv @@ -0,0 +1,4 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.997031,114,116,230,149 +mouse,0.995179,259,309,75,60 +tvmonitor,0.868870,171,-1,232,158 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0042.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0042.csv new file mode 100644 index 0000000000000000000000000000000000000000..6bd0f82e111476005f4a18637a786ff57a7ebed1 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0042.csv @@ -0,0 +1,4 @@ +Class,Confidence,X,Y,Width,Height +mouse,0.841598,496,423,98,57 +tvmonitor,0.770743,433,-2,207,291 +teddy bear,0.646202,0,-6,251,493 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0043.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0043.csv new file mode 100644 index 0000000000000000000000000000000000000000..87ebd380ee3419d689979a9b24ea337240e704c1 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0043.csv @@ -0,0 +1,3 @@ +Class,Confidence,X,Y,Width,Height +teddy bear,0.953503,13,-7,396,484 +keyboard,0.577163,557,170,83,148 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0044.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0044.csv new file mode 100644 index 0000000000000000000000000000000000000000..16d190c72012e6e429bbf6f5d9cc2bce3d7a5020 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0044.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +teddy bear,0.921151,151,-5,349,483 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0045.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0045.csv new file mode 100644 index 0000000000000000000000000000000000000000..d158871dcc810dbb794bbdb604877cb57c73ddb7 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0045.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +teddy bear,0.970806,231,11,379,464 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0046.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0046.csv new file mode 100644 index 0000000000000000000000000000000000000000..2b85834a9a5c0a87f1b8f9098695ccc103fb91ba --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0046.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +teddy bear,0.943422,220,102,340,370 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0047.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0047.csv new file mode 100644 index 0000000000000000000000000000000000000000..32b12b6f397f167585738324112d521eb8ebb697 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0047.csv @@ -0,0 +1,2 @@ +Class,Confidence,X,Y,Width,Height +teddy bear,0.950549,214,99,337,374 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0048.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0048.csv new file mode 100644 index 0000000000000000000000000000000000000000..3a8c5723e4e33bdb1d9de6e77124a7e7a7c95190 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0048.csv @@ -0,0 +1,4 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.959411,546,182,94,75 +teddy bear,0.912603,253,91,283,355 +tvmonitor,0.677425,586,6,54,204 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0049.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0049.csv new file mode 100644 index 0000000000000000000000000000000000000000..6e79d6ed3e0482553896f74841b30242f8c66dd7 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0049.csv @@ -0,0 +1,4 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.997796,471,154,166,70 +teddy bear,0.954548,238,101,256,270 +tvmonitor,0.919535,493,11,147,160 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0050.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0050.csv new file mode 100644 index 0000000000000000000000000000000000000000..6b186eac2d83d9e5e11a8f8b5edebc70d236ce54 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0050.csv @@ -0,0 +1,5 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.995139,425,147,156,49 +mouse,0.988544,587,204,30,23 +tvmonitor,0.952972,434,13,168,137 +teddy bear,0.938436,225,109,259,253 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0051.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0051.csv new file mode 100644 index 0000000000000000000000000000000000000000..ef545f8fa13754a0fbd34626b86955f57156f1ba --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0051.csv @@ -0,0 +1,7 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.997336,347,195,140,31 +mouse,0.975241,508,229,22,20 +tvmonitor,0.956177,344,70,133,120 +chair,0.907744,207,262,246,216 +book,0.609980,595,202,44,45 +teddy bear,0.578413,205,163,246,218 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0052.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0052.csv new file mode 100644 index 0000000000000000000000000000000000000000..32e460a81bc197f0f623f1bedd3abf8f743b7cce --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0052.csv @@ -0,0 +1,5 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.988408,291,198,129,39 +chair,0.955053,166,302,250,173 +tvmonitor,0.827685,267,77,148,118 +book,0.571689,486,181,141,64 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0053.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0053.csv new file mode 100644 index 0000000000000000000000000000000000000000..1abb3e8d203d5210de225a90a6b6fd01b861dee5 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0053.csv @@ -0,0 +1,9 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.986321,505,143,119,38 +keyboard,0.970156,192,162,147,40 +tvmonitor,0.938241,156,31,152,126 +mouse,0.914936,364,187,25,23 +book,0.887403,427,147,91,43 +tvmonitor,0.867441,436,-1,180,137 +teddy bear,0.727997,77,185,290,265 +bottle,0.645256,594,84,30,60 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0054.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0054.csv new file mode 100644 index 0000000000000000000000000000000000000000..1cf1b46f4ab07ecb8d3fb7cab01f5be8bc0c56f6 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0054.csv @@ -0,0 +1,10 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.998075,106,174,170,70 +mouse,0.992344,306,194,32,23 +keyboard,0.980599,439,120,103,45 +tvmonitor,0.967005,356,0,152,123 +book,0.957511,359,136,96,49 +bottle,0.904279,505,56,22,60 +tvmonitor,0.855593,29,28,203,173 +book,0.629848,305,122,86,41 +mouse,0.588135,545,120,33,15 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0055.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0055.csv new file mode 100644 index 0000000000000000000000000000000000000000..560cc0a34a3b068cdf0043e1f95eadf4c62393a3 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0055.csv @@ -0,0 +1,13 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.996552,101,154,171,91 +mouse,0.982217,304,168,33,22 +chair,0.951795,485,57,157,316 +book,0.925306,341,103,98,50 +tvmonitor,0.920464,321,0,133,93 +tvmonitor,0.877540,0,7,215,195 +bottle,0.840664,458,22,20,64 +teddy bear,0.821970,113,200,278,226 +book,0.746269,279,95,88,43 +book,0.743132,341,132,98,31 +mouse,0.740291,501,79,31,15 +keyboard,0.583483,416,80,82,49 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0056.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0056.csv new file mode 100644 index 0000000000000000000000000000000000000000..4f476a15da8fa49d8be237cf62e1d526c9220e75 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0056.csv @@ -0,0 +1,10 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.996385,95,146,170,99 +mouse,0.973729,297,156,37,21 +chair,0.953819,462,42,177,295 +tvmonitor,0.928498,295,-2,124,84 +bottle,0.863727,426,2,19,64 +book,0.849478,327,88,95,48 +tvmonitor,0.772511,-4,0,203,211 +teddy bear,0.713502,173,187,280,217 +keyboard,0.621182,390,63,81,44 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0057.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0057.csv new file mode 100644 index 0000000000000000000000000000000000000000..c9f70368941b853900d85de90dcf597e6afb8a96 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0057.csv @@ -0,0 +1,11 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.996073,123,133,154,103 +mouse,0.992576,312,137,38,21 +chair,0.962427,476,8,164,294 +tvmonitor,0.900902,286,-1,114,70 +tvmonitor,0.815468,-1,1,211,189 +book,0.811682,328,65,97,49 +teddy bear,0.711216,278,162,271,207 +keyboard,0.629492,385,40,69,42 +book,0.610875,329,93,95,33 +bottle,0.515433,408,0,18,37 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0058.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0058.csv new file mode 100644 index 0000000000000000000000000000000000000000..ebdb6b64bc899216c154e95c259c6845fd76e65c --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0058.csv @@ -0,0 +1,8 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.997266,241,139,121,85 +mouse,0.991515,394,140,35,18 +mouse,0.948363,496,53,27,15 +tvmonitor,0.926669,355,-2,88,88 +bottle,0.900493,454,7,17,48 +tvmonitor,0.582670,141,2,155,186 +book,0.570701,407,108,76,25 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0059.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0059.csv new file mode 100644 index 0000000000000000000000000000000000000000..3d44de72b124befa950e45d14242968d710a4529 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0059.csv @@ -0,0 +1,7 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.995426,373,155,106,88 +mouse,0.984117,508,156,39,18 +mouse,0.929485,578,67,29,15 +tvmonitor,0.859698,296,18,114,185 +tvmonitor,0.708192,451,1,73,91 +bottle,0.694783,533,22,18,50 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0060.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0060.csv new file mode 100644 index 0000000000000000000000000000000000000000..12fbae70e91a6a6ab159aa0451543c57d7143e4e --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0060.csv @@ -0,0 +1,8 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.992563,410,139,87,84 +mouse,0.960352,521,138,37,19 +tvmonitor,0.889681,346,4,78,182 +tvmonitor,0.822492,450,0,61,85 +mouse,0.748765,560,56,27,15 +bottle,0.587968,520,13,17,46 +bottle,0.537090,118,107,26,80 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0061.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0061.csv new file mode 100644 index 0000000000000000000000000000000000000000..c23855ca17680460ebfa7983c25c0a325164df4d --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0061.csv @@ -0,0 +1,5 @@ +Class,Confidence,X,Y,Width,Height +mouse,0.980371,472,97,35,16 +keyboard,0.953998,390,100,61,76 +bowl,0.702804,250,378,129,99 +tvmonitor,0.700526,320,1,67,142 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0062.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0062.csv new file mode 100644 index 0000000000000000000000000000000000000000..567ef985c30da1fb764734c431121df44dd9b38f --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0062.csv @@ -0,0 +1,8 @@ +Class,Confidence,X,Y,Width,Height +chair,0.975339,60,16,96,109 +bowl,0.897614,327,372,117,105 +mouse,0.691093,464,86,33,14 +bottle,0.664471,185,171,48,81 +chair,0.662926,29,0,68,39 +tvmonitor,0.606069,333,3,56,148 +bowl,0.536005,30,212,50,35 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0063.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0063.csv new file mode 100644 index 0000000000000000000000000000000000000000..fc8cbf12b9d0b770fad855d7f0ea828ceb77e69c --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0063.csv @@ -0,0 +1,10 @@ +Class,Confidence,X,Y,Width,Height +keyboard,0.939368,367,109,51,51 +bowl,0.907529,321,356,109,111 +chair,0.872639,2,36,93,110 +mouse,0.816080,412,95,29,14 +tvmonitor,0.746171,302,0,52,161 +bottle,0.718847,181,167,47,86 +chair,0.589135,453,5,76,119 +teddy bear,0.542085,520,38,120,194 +bottle,0.520179,347,7,16,46 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0064.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0064.csv new file mode 100644 index 0000000000000000000000000000000000000000..660ab86cbd3fff875c765ddf268886f89aa5d46b --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0064.csv @@ -0,0 +1,10 @@ +Class,Confidence,X,Y,Width,Height +chair,0.940358,11,58,103,114 +bowl,0.920934,358,351,104,118 +keyboard,0.793169,387,121,49,46 +bottle,0.778224,230,129,42,122 +mouse,0.759731,422,108,27,14 +chair,0.653612,447,22,74,113 +chair,0.601762,-1,136,38,101 +bottle,0.597234,206,43,15,25 +tvmonitor,0.590153,323,12,58,146 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0065.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0065.csv new file mode 100644 index 0000000000000000000000000000000000000000..49530d69733f99f8609d5f8924bddc12c0d88dc9 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0065.csv @@ -0,0 +1,8 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.919779,239,113,54,137 +bowl,0.904013,379,341,101,97 +chair,0.794649,0,72,89,98 +chair,0.684401,411,19,77,92 +laptop,0.671250,314,19,127,144 +keyboard,0.530139,375,113,56,46 +teddy bear,0.529551,509,30,133,156 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0066.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0066.csv new file mode 100644 index 0000000000000000000000000000000000000000..53f722a62abcfac969ec2909b73b14254961ec3b --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0066.csv @@ -0,0 +1,8 @@ +Class,Confidence,X,Y,Width,Height +laptop,0.936216,271,42,106,125 +bottle,0.822224,129,72,30,88 +mouse,0.726340,340,109,24,13 +cup,0.675442,39,224,37,41 +bottle,0.606103,218,119,50,125 +teddy bear,0.576097,442,28,134,135 +bowl,0.562613,358,323,86,82 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0067.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0067.csv new file mode 100644 index 0000000000000000000000000000000000000000..87b7747ee0f4eed4090b71b79b5f7199adf8681e --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0067.csv @@ -0,0 +1,5 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.909545,117,69,42,92 +bottle,0.691796,153,95,22,53 +teddy bear,0.592047,441,-1,113,118 +cup,0.507913,69,223,39,40 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0068.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0068.csv new file mode 100644 index 0000000000000000000000000000000000000000..39910412682128a932b89c922da5624cadc6bf24 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0068.csv @@ -0,0 +1,8 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.868912,281,113,46,115 +bottle,0.732050,89,0,43,60 +teddy bear,0.723237,439,12,82,111 +bottle,0.683770,59,-1,51,69 +bottle,0.634657,30,-1,50,73 +bottle,0.617646,150,114,25,55 +bottle,0.537103,110,90,36,83 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0069.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0069.csv new file mode 100644 index 0000000000000000000000000000000000000000..fda90b8754f069a328135c0df1f42e634679d985 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0069.csv @@ -0,0 +1,11 @@ +Class,Confidence,X,Y,Width,Height +cup,0.969409,174,267,31,40 +bottle,0.928067,149,34,33,70 +bottle,0.775592,176,154,29,56 +bottle,0.754805,203,156,22,51 +bottle,0.725004,352,154,40,109 +teddy bear,0.695578,472,76,85,97 +bowl,0.676720,212,292,42,33 +bottle,0.602451,123,34,39,74 +chair,0.552979,-3,261,151,147 +bottle,0.543496,226,160,21,52 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0070.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0070.csv new file mode 100644 index 0000000000000000000000000000000000000000..370c485e51d1245b3b39fdba5997762b1a994f02 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0070.csv @@ -0,0 +1,9 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.941032,86,2,47,82 +knife,0.914250,110,263,60,32 +bottle,0.876633,112,4,37,77 +cup,0.849544,184,245,33,42 +bottle,0.805667,180,133,26,53 +bottle,0.757878,361,124,36,109 +bottle,0.730657,150,128,31,63 +chair,0.678632,2,265,226,213 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0071.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0071.csv new file mode 100644 index 0000000000000000000000000000000000000000..14521e0b6ba47e56ad6d7fe9eb1d98b495a9b75f --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0071.csv @@ -0,0 +1,13 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.912676,89,2,48,81 +knife,0.823033,140,245,52,33 +bottle,0.800369,177,117,28,59 +bottle,0.781677,372,102,33,107 +bottle,0.771924,199,121,15,48 +book,0.761658,21,118,38,71 +cup,0.663716,212,223,32,41 +bottle,0.658701,211,133,19,48 +bottle,0.642427,157,126,30,56 +bottle,0.635608,44,14,35,62 +bowl,0.632454,262,242,41,29 +bottle,0.616369,139,108,30,77 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0072.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0072.csv new file mode 100644 index 0000000000000000000000000000000000000000..51731bef0f9a85facfbd1913369db9d276b431a7 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0072.csv @@ -0,0 +1,11 @@ +Class,Confidence,X,Y,Width,Height +chair,0.932518,3,229,249,244 +bottle,0.911102,375,78,31,107 +bottle,0.900526,200,116,21,51 +cup,0.858831,225,204,32,40 +book,0.809790,0,106,21,73 +bottle,0.798626,183,106,18,49 +bottle,0.719835,142,105,31,63 +bottle,0.695042,162,105,28,57 +bowl,0.634067,279,220,41,28 +bottle,0.538070,132,101,23,68 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0073.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0073.csv new file mode 100644 index 0000000000000000000000000000000000000000..7fb41fd532bc6995de9f889e400a87535cb846b7 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0073.csv @@ -0,0 +1,7 @@ +Class,Confidence,X,Y,Width,Height +cup,0.959012,172,211,34,42 +bottle,0.931839,299,72,35,101 +person,0.599536,515,0,55,43 +cup,0.592651,139,206,35,31 +bottle,0.572120,102,130,29,52 +spoon,0.511327,95,247,42,42 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0074.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0074.csv new file mode 100644 index 0000000000000000000000000000000000000000..c6204501e428cbcee8c9e3febd9b646bf5f140d0 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0074.csv @@ -0,0 +1,11 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.983779,281,70,41,103 +bottle,0.836020,58,153,34,51 +cup,0.832425,175,224,35,47 +cup,0.791209,125,222,35,32 +spoon,0.767191,97,272,33,48 +person,0.719033,423,0,49,36 +cup,0.648319,152,158,35,34 +bottle,0.603458,12,147,22,39 +bottle,0.576179,28,137,27,39 +bottle,0.510712,113,140,36,55 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0075.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0075.csv new file mode 100644 index 0000000000000000000000000000000000000000..e907f5cb89368d7b2c543c92166a58cf21d81f48 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0075.csv @@ -0,0 +1,7 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.993498,217,49,43,115 +cup,0.989619,133,224,41,47 +cup,0.974215,70,230,39,35 +bottle,0.889706,28,137,48,69 +knife,0.826264,62,286,21,57 +cup,0.655175,80,159,39,39 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0076.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0076.csv new file mode 100644 index 0000000000000000000000000000000000000000..88779b9fc8c845f7cd9a35607e0abd852ade7e64 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0076.csv @@ -0,0 +1,9 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.986627,223,49,49,115 +cup,0.939366,167,234,45,55 +cup,0.892030,88,246,45,40 +bottle,0.843273,22,150,53,73 +knife,0.721257,102,310,11,65 +person,0.609807,259,0,42,20 +cup,0.555802,78,168,43,44 +chair,0.538598,0,385,163,94 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0077.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0077.csv new file mode 100644 index 0000000000000000000000000000000000000000..d4782f1194bf0857334cc0e15a7a80a2b7666167 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0077.csv @@ -0,0 +1,5 @@ +Class,Confidence,X,Y,Width,Height +cup,0.978837,182,257,49,61 +bottle,0.970952,190,51,59,122 +knife,0.686071,118,357,30,74 +cup,0.611543,85,287,50,41 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0078.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0078.csv new file mode 100644 index 0000000000000000000000000000000000000000..ba56329f4a7ee2955224170fe087e6efca73711b --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0078.csv @@ -0,0 +1,8 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.975020,56,156,70,98 +knife,0.974880,234,360,58,92 +cup,0.958840,192,275,81,47 +cup,0.943338,311,246,54,69 +bottle,0.869546,301,8,50,147 +cup,0.581817,131,175,49,53 +spoon,0.574316,380,233,74,16 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0079.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0079.csv new file mode 100644 index 0000000000000000000000000000000000000000..fff98cb86b050814af49cd25928446e7890f0851 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0079.csv @@ -0,0 +1,13 @@ +Class,Confidence,X,Y,Width,Height +knife,0.979353,386,305,72,98 +cup,0.962333,275,126,43,55 +cup,0.956638,473,208,61,70 +cup,0.949319,345,227,79,42 +bottle,0.905583,115,130,52,97 +scissors,0.797074,0,339,54,141 +scissors,0.766448,21,269,209,209 +bottle,0.701709,-1,138,46,164 +spoon,0.691452,535,208,89,18 +bottle,0.640640,43,123,67,90 +bottle,0.508092,213,99,49,97 +bottle,0.503067,19,151,87,116 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0080.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0080.csv new file mode 100644 index 0000000000000000000000000000000000000000..45020c4431a14e9a3e4eb89ab9387dd3afb369a1 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0080.csv @@ -0,0 +1,10 @@ +Class,Confidence,X,Y,Width,Height +scissors,0.995203,173,259,87,75 +cup,0.976171,514,181,61,39 +cup,0.962889,429,98,37,49 +bottle,0.950547,239,81,47,127 +bottle,0.947335,162,64,71,160 +book,0.897206,-1,318,132,155 +bottle,0.860015,299,92,31,85 +scissors,0.822301,280,211,156,102 +bottle,0.681953,-1,0,66,57 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0081.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0081.csv new file mode 100644 index 0000000000000000000000000000000000000000..6a91dbd0d4b4556ced971cc5dd024d3e6ae77f65 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0081.csv @@ -0,0 +1,9 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.985833,238,121,53,153 +bottle,0.947099,299,143,44,111 +cup,0.935909,558,227,51,39 +scissors,0.911014,255,304,72,70 +book,0.639325,33,362,184,118 +bottle,0.589223,68,0,93,115 +bottle,0.575294,347,145,29,80 +cell phone,0.516686,322,250,50,40 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0082.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0082.csv new file mode 100644 index 0000000000000000000000000000000000000000..e38c4b4fc822f3373f20ffb81dfdd56ed13f9573 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0082.csv @@ -0,0 +1,10 @@ +Class,Confidence,X,Y,Width,Height +scissors,0.986961,341,317,57,61 +bottle,0.874087,179,0,77,142 +bottle,0.841351,405,173,26,76 +book,0.829093,156,365,148,114 +bottle,0.753484,374,173,32,97 +bottle,0.738448,318,156,41,128 +cup,0.713853,512,181,30,40 +book,0.575512,44,252,77,161 +bottle,0.512976,357,169,23,83 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0083.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0083.csv new file mode 100644 index 0000000000000000000000000000000000000000..0a5f5db52321335cf00d7b156e1c7569bda213d2 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0083.csv @@ -0,0 +1,11 @@ +Class,Confidence,X,Y,Width,Height +scissors,0.955194,492,289,54,48 +book,0.891456,335,313,122,115 +bottle,0.829451,377,2,49,103 +bottle,0.678437,502,153,24,77 +bottle,0.661043,357,0,32,103 +chair,0.654496,154,191,137,158 +bottle,0.639039,141,0,88,132 +bottle,0.568850,453,142,26,92 +clock,0.568327,0,0,122,135 +bottle,0.565356,553,158,21,71 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0084.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0084.csv new file mode 100644 index 0000000000000000000000000000000000000000..b24446eff69a4f4af60affcc10b829a61b6613bc --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0084.csv @@ -0,0 +1,6 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.988348,344,-1,49,146 +bottle,0.960537,293,-2,46,132 +bottle,0.954284,523,0,43,125 +chair,0.947201,318,213,122,143 +bottle,0.870651,552,0,55,137 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0085.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0085.csv new file mode 100644 index 0000000000000000000000000000000000000000..3359dcbb15ee0377355e8d0afa8c829cd1b538b8 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0085.csv @@ -0,0 +1,5 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.951186,465,43,67,140 +bottle,0.847318,422,37,51,122 +book,0.632008,563,410,77,71 +book,0.552315,405,241,124,165 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0086.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0086.csv new file mode 100644 index 0000000000000000000000000000000000000000..bac84178d14db33874e80cffd9dfc5b581a681d1 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0086.csv @@ -0,0 +1,7 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.899552,276,12,46,100 +bottle,0.808870,300,21,54,123 +bottle,0.708675,534,254,55,81 +bottle,0.667095,454,49,57,119 +bottle,0.630533,491,215,66,108 +book,0.558406,328,328,126,102 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0087.csv b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0087.csv new file mode 100644 index 0000000000000000000000000000000000000000..44f1b2511844a16a0a8f185381822e8b58e2fba4 --- /dev/null +++ b/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0087.csv @@ -0,0 +1,13 @@ +Class,Confidence,X,Y,Width,Height +bottle,0.970868,272,2,33,128 +bottle,0.964375,97,5,45,122 +bottle,0.930590,59,1,43,115 +bottle,0.876013,258,8,21,117 +book,0.830113,194,283,113,73 +bottle,0.810374,367,173,33,73 +bottle,0.640560,331,148,32,101 +bottle,0.627324,398,182,23,56 +scissors,0.600947,335,275,45,29 +book,0.599429,82,180,80,116 +book,0.551116,146,179,28,116 +bottle,0.524740,386,169,15,49 diff --git a/target/classes/vslam/tum_rgbd/BoundedInfo/KeyFrame_0088.csv 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b/target/classes/vslam/tum_rgbd/pointcloud.csv differ diff --git a/target/classes/vslam/vslam_implementation.m b/target/classes/vslam/vslam_implementation.m new file mode 100644 index 0000000000000000000000000000000000000000..3751f844577eef317246f2c361525dff4e1c3008 --- /dev/null +++ b/target/classes/vslam/vslam_implementation.m @@ -0,0 +1,576 @@ +function vslam_implementation(dataset_name) + % Import dependencies + addpath('./Mathworks_VSLAM_Example/'); + + % Define the base folder for datasets + datasetFolder = [dataset_name, '/']; + + imageFolder = [datasetFolder, 'images/']; + imds = imageDatastore(imageFolder); + + % Process the image sequence + [worldPointSetOutput] = ProcessImageSequence(imds); + + % Save the outputs to .mat files + save('worldPointSetOutput.mat', 'worldPointSetOutput'); + + % Iterate over KeyFrames and execute extractPointsByViewId + keyFramesDir = './KeyFrames'; + keyFrameFiles = dir(fullfile(keyFramesDir, 'KeyFrame_*.png')); + + for i = 1:length(keyFrameFiles) + filename = keyFrameFiles(i).name; + viewId = str2double(regexp(filename, '\d+', 'match', 'once')); % Extracting the numeric part from filename + extractPointsByViewId(viewId, worldPointSetOutput); + end +end + + + +function worldPointSetOutput = ProcessImageSequence(imds) + currFrameIdx = 1; + currI = readimage(imds, currFrameIdx); + + %% Map Initilization + % Set random seed for reproducibility + rng(0); + + % Create a cameraIntrinsics object to store the camera intrinsic parameters. + % The intrinsics for the dataset can be found at the following page: + % https://vision.in.tum.de/data/datasets/rgbd-dataset/file_formats + % Note that the images in the dataset are already undistorted, hence there + % is no need to specify the distortion coefficients. + focalLength = [535.4, 539.2]; % in units of pixels + principalPoint = [320.1, 247.6]; % in units of pixels + imageSize = size(currI,[1 2]); % in units of pixels + intrinsics = cameraIntrinsics(focalLength, principalPoint, imageSize); + + % Detect and extract ORB features + scaleFactor = 1.2; + numLevels = 8; + numPoints = 1000; + [preFeatures, prePoints] = helperDetectAndExtractFeatures(currI, scaleFactor, numLevels, numPoints); + + currFrameIdx = currFrameIdx + 1; + firstI = currI; % Preserve the first frame + + isMapInitialized = false; + + % Map initialization loop + while ~isMapInitialized && currFrameIdx < numel(imds.Files) + currI = readimage(imds, currFrameIdx); + + [currFeatures, currPoints] = helperDetectAndExtractFeatures(currI, scaleFactor, numLevels, numPoints); + + currFrameIdx = currFrameIdx + 1; + + % Find putative feature matches + indexPairs = matchFeatures(preFeatures, currFeatures, Unique=true, ... + MaxRatio=0.9, MatchThreshold=40); + + preMatchedPoints = prePoints(indexPairs(:,1),:); + currMatchedPoints = currPoints(indexPairs(:,2),:); + + % If not enough matches are found, check the next frame + minMatches = 100; + if size(indexPairs, 1) < minMatches + continue + end + + preMatchedPoints = prePoints(indexPairs(:,1),:); + currMatchedPoints = currPoints(indexPairs(:,2),:); + + % Compute homography and evaluate reconstruction + [tformH, scoreH, inliersIdxH] = helperComputeHomography(preMatchedPoints, currMatchedPoints); + + % Compute fundamental matrix and evaluate reconstruction + [tformF, scoreF, inliersIdxF] = helperComputeFundamentalMatrix(preMatchedPoints, currMatchedPoints); + + % Select the model based on a heuristic + ratio = scoreH/(scoreH + scoreF); + ratioThreshold = 0.45; + if ratio > ratioThreshold + inlierTformIdx = inliersIdxH; + tform = tformH; + else + inlierTformIdx = inliersIdxF; + tform = tformF; + end + + % Computes the camera location up to scale. Use half of the + % points to reduce computation + inlierPrePoints = preMatchedPoints(inlierTformIdx); + inlierCurrPoints = currMatchedPoints(inlierTformIdx); + [relPose, validFraction] = estrelpose(tform, intrinsics, ... + inlierPrePoints(1:2:end), inlierCurrPoints(1:2:end)); + + % If not enough inliers are found, move to the next frame + if validFraction < 0.9 || numel(relPose)==3 + continue + end + + % Triangulate two views to obtain 3-D map points + minParallax = 1; % In degrees + [isValid, xyzWorldPoints, inlierTriangulationIdx] = helperTriangulateTwoFrames(... + rigidtform3d, relPose, inlierPrePoints, inlierCurrPoints, intrinsics, minParallax); + + if ~isValid + continue + end + + % Get the original index of features in the two key frames + indexPairs = indexPairs(inlierTformIdx(inlierTriangulationIdx),:); + + isMapInitialized = true; + + disp(['Map initialized with frame 1 and frame ', num2str(currFrameIdx-1)]) + end % End of map initialization loop + + %% Store initial key frames and map points + % Create an empty imageviewset object to store key frames + vSetKeyFrames = imageviewset; + + % Create an empty worldpointset object to store 3-D map points + mapPointSet = worldpointset; + + % Add the first key frame. Place the camera associated with the first + % key frame at the origin, oriented along the Z-axis + preViewId = 1; + vSetKeyFrames = addView(vSetKeyFrames, preViewId, rigidtform3d, Points=prePoints,... + Features=preFeatures.Features); + + % Add the second key frame + currViewId = 2; + vSetKeyFrames = addView(vSetKeyFrames, currViewId, relPose, Points=currPoints,... + Features=currFeatures.Features); + + % Add connection between the first and the second key frame + vSetKeyFrames = addConnection(vSetKeyFrames, preViewId, currViewId, relPose, Matches=indexPairs); + + % Add 3-D map points + [mapPointSet, newPointIdx] = addWorldPoints(mapPointSet, xyzWorldPoints); + + % Add observations of the map points + preLocations = prePoints.Location; + currLocations = currPoints.Location; + preScales = prePoints.Scale; + currScales = currPoints.Scale; + + % Add image points corresponding to the map points in the first key frame + mapPointSet = addCorrespondences(mapPointSet, preViewId, newPointIdx, indexPairs(:,1)); + + % Add image points corresponding to the map points in the second key frame + mapPointSet = addCorrespondences(mapPointSet, currViewId, newPointIdx, indexPairs(:,2)); + + % Initialize place recognition database + % Load the bag of features data created offline + bofData = load("bagOfFeaturesDataSLAM.mat"); + + % Initialize the place recognition database + loopDatabase = invertedImageIndex(bofData.bof,SaveFeatureLocations=false); + + % Add features of the first two key frames to the database + addImageFeatures(loopDatabase, preFeatures, preViewId); + addImageFeatures(loopDatabase, currFeatures, currViewId); + + %% Refine and visualize initial reconstruction + % Run full bundle adjustment on the first two key frames + tracks = findTracks(vSetKeyFrames); + cameraPoses = poses(vSetKeyFrames); + + [refinedPoints, refinedAbsPoses] = bundleAdjustment(xyzWorldPoints, tracks, ... + cameraPoses, intrinsics, FixedViewIDs=1, ... + PointsUndistorted=true, AbsoluteTolerance=1e-7,... + RelativeTolerance=1e-15, MaxIteration=20, ... + Solver="preconditioned-conjugate-gradient"); + + % Scale the map and the camera pose using the median depth of map points + medianDepth = median(vecnorm(refinedPoints.')); + refinedPoints = refinedPoints / medianDepth; + + refinedAbsPoses.AbsolutePose(currViewId).Translation = ... + refinedAbsPoses.AbsolutePose(currViewId).Translation / medianDepth; + relPose.Translation = relPose.Translation/medianDepth; + + % Update key frames with the refined poses + vSetKeyFrames = updateView(vSetKeyFrames, refinedAbsPoses); + vSetKeyFrames = updateConnection(vSetKeyFrames, preViewId, currViewId, relPose); + + % Update map points with the refined positions + mapPointSet = updateWorldPoints(mapPointSet, newPointIdx, refinedPoints); + + % Update view direction and depth + mapPointSet = updateLimitsAndDirection(mapPointSet, newPointIdx, vSetKeyFrames.Views); + + % Update representative view + mapPointSet = updateRepresentativeView(mapPointSet, newPointIdx, vSetKeyFrames.Views); + + % Visualize matched features in the current frame + % close(hfeature.Parent.Parent); + featurePlot = helperVisualizeMatchedFeatures(currI, currPoints(indexPairs(:,2))); + + % Visualize initial map points and camera trajectory + mapPlot = helperVisualizeMotionAndStructure(vSetKeyFrames, mapPointSet); + + % Show legend + showLegend(mapPlot); + + %% Tracking + % ViewId of the current key frame + currKeyFrameId = currViewId; + + % ViewId of the last key frame + lastKeyFrameId = currViewId; + + % Index of the last key frame in the input image sequence + lastKeyFrameIdx = currFrameIdx - 1; + + % Indices of all the key frames in the input image sequence + addedFramesIdx = [1; lastKeyFrameIdx]; + + isLoopClosed = false; + + % Main loop (attempt to close loop while iterating over all images in + % dataset) + isLastFrameKeyFrame = true; + while ~isLoopClosed && currFrameIdx < numel(imds.Files) + currI = readimage(imds, currFrameIdx); + + [currFeatures, currPoints] = helperDetectAndExtractFeatures(currI, scaleFactor, numLevels, numPoints); + + % Track the last key frame + % mapPointsIdx: Indices of the map points observed in the current frame + % featureIdx: Indices of the corresponding feature points in the + % current frame + [currPose, mapPointsIdx, featureIdx] = helperTrackLastKeyFrame(mapPointSet, ... + vSetKeyFrames.Views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor); + + % Track the local map and check if the current frame is a key frame. + % A frame is a key frame if both of the following conditions are satisfied: + % + % 1. At least 20 frames have passed since the last key frame or the + % current frame tracks fewer than 100 map points. + % 2. The map points tracked by the current frame are fewer than 90% of + % points tracked by the reference key frame. + % + % Tracking performance is sensitive to the value of numPointsKeyFrame. + % If tracking is lost, try a larger value. + % + % localKeyFrameIds: ViewId of the connected key frames of the current frame + numSkipFrames = 20; + numPointsKeyFrame = 80; + [localKeyFrameIds, currPose, mapPointsIdx, featureIdx, isKeyFrame] = ... + helperTrackLocalMap(mapPointSet, vSetKeyFrames, mapPointsIdx, ... + featureIdx, currPose, currFeatures, currPoints, intrinsics, scaleFactor, numLevels, ... + isLastFrameKeyFrame, lastKeyFrameIdx, currFrameIdx, numSkipFrames, numPointsKeyFrame); + + + % Visualize matched features + updatePlot(featurePlot, currI, currPoints(featureIdx)); + + if ~isKeyFrame + currFrameIdx = currFrameIdx + 1; + isLastFrameKeyFrame = false; + continue + else + isLastFrameKeyFrame = true; + end + + % Update current key frame ID + currKeyFrameId = currKeyFrameId + 1; + + %% Local mapping + % Add the new key frame + [mapPointSet, vSetKeyFrames] = helperAddNewKeyFrame(mapPointSet, vSetKeyFrames, ... + currPose, currFeatures, currPoints, mapPointsIdx, featureIdx, localKeyFrameIds); + + % Remove outlier map points that are observed in fewer than 3 key frames + outlierIdx = setdiff(newPointIdx, mapPointsIdx); + if ~isempty(outlierIdx) + mapPointSet = removeWorldPoints(mapPointSet, outlierIdx); + end + + % Create new map points by triangulation + minNumMatches = 10; + minParallax = 3; + [mapPointSet, vSetKeyFrames, newPointIdx] = helperCreateNewMapPoints(mapPointSet, vSetKeyFrames, ... + currKeyFrameId, intrinsics, scaleFactor, minNumMatches, minParallax); + + % Local bundle adjustment + [refinedViews, dist] = connectedViews(vSetKeyFrames, currKeyFrameId, MaxDistance=2); + refinedKeyFrameIds = refinedViews.ViewId; + fixedViewIds = refinedKeyFrameIds(dist==2); + fixedViewIds = fixedViewIds(1:min(10, numel(fixedViewIds))); + + % Refine local key frames and map points + [mapPointSet, vSetKeyFrames, mapPointIdx] = bundleAdjustment(... + mapPointSet, vSetKeyFrames, [refinedKeyFrameIds; currKeyFrameId], intrinsics, ... + FixedViewIDs=fixedViewIds, PointsUndistorted=true, AbsoluteTolerance=1e-7,... + RelativeTolerance=1e-16, Solver="preconditioned-conjugate-gradient", ... + MaxIteration=10); + + % Update view direction and depth + mapPointSet = updateLimitsAndDirection(mapPointSet, mapPointIdx, vSetKeyFrames.Views); + + % Update representative view + mapPointSet = updateRepresentativeView(mapPointSet, mapPointIdx, vSetKeyFrames.Views); + + % Check if the KeyFrames directory exists; if not, create it + keyFramesDir = './KeyFrames_Mono'; + if ~exist(keyFramesDir, 'dir') + mkdir(keyFramesDir); + end + + % Store feature locations for this key frame + keyFramePointsDir = './KeyFramePoints_Mono'; + if ~exist(keyFramePointsDir, 'dir') + mkdir(keyFramePointsDir); + end + + % Save the current key frame image using currKeyFrameId + filename = sprintf('%s/KeyFrame_%04d.png', keyFramesDir, currKeyFrameId); + imwrite(currI, filename); + + % Save feature points information + saveKeyFramePoints(keyFramePointsDir, currKeyFrameId, currPoints(featureIdx), mapPointsIdx); + + + % Visualize 3D world points and camera trajectory + updatePlot(mapPlot, vSetKeyFrames, mapPointSet); + + %% Loop closure + % Check loop closure after some key frames have been created + if currKeyFrameId > 20 + + % Minimum number of feature matches of loop edges + loopEdgeNumMatches = 50; + + % Detect possible loop closure key frame candidates + [isDetected, validLoopCandidates] = helperCheckLoopClosure(vSetKeyFrames, currKeyFrameId, ... + loopDatabase, currI, loopEdgeNumMatches); + + if isDetected + % Add loop closure connections + [isLoopClosed, mapPointSet, vSetKeyFrames] = helperAddLoopConnections(... + mapPointSet, vSetKeyFrames, validLoopCandidates, currKeyFrameId, ... + currFeatures, loopEdgeNumMatches); + end + end + + % If no loop closure is detected, add current features into the database + if ~isLoopClosed + addImageFeatures(loopDatabase, currFeatures, currKeyFrameId); + end + + % Update IDs and indices + lastKeyFrameId = currKeyFrameId; + lastKeyFrameIdx = currFrameIdx; + addedFramesIdx = [addedFramesIdx; currFrameIdx]; %#ok + currFrameIdx = currFrameIdx + 1; + end % End of main loop + + %% Optimizing + if isLoopClosed + % Optimize the poses + minNumMatches = 20; + vSetKeyFramesOptim = optimizePoses(vSetKeyFrames, minNumMatches, Tolerance=1e-16); + + % Update map points after optimizing the poses + mapPointSet = helperUpdateGlobalMap(mapPointSet, vSetKeyFrames, vSetKeyFramesOptim); + + updatePlot(mapPlot, vSetKeyFrames, mapPointSet); + + % Plot the optimized camera trajectory + optimizedPoses = poses(vSetKeyFramesOptim); + plotOptimizedTrajectory(mapPlot, optimizedPoses) + + % Update legend + showLegend(mapPlot); + + worldPointSetOutput = mapPointSet; + end + +end + + +%% Helper functions +% The following funciton definitions are provied in the +% Mathworks_VSLAM_Example Directory +% helperAddLoopConnections add connections between the current keyframe and the valid loop candidate. +% helperAddNewKeyFrame add key frames to the key frame set. +% helperCheckLoopClosure detect loop candidates key frames by retrieving visually similar images from the database. +% helperCreateNewMapPoints create new map points by triangulation. +% helperORBFeatureExtractorFunction implements the ORB feature extraction used in bagOfFeatures. +% helperTrackLastKeyFrame estimate the current camera pose by tracking the last key frame. +% helperTrackLocalMap refine the current camera pose by tracking the local map. +% helperVisualizeMatchedFeatures show the matched features in a frame. +% helperVisualizeMotionAndStructure show map points and camera trajectory. +% helperImportGroundTruth import camera pose ground truth from the downloaded data. + +% helperDetectAndExtractFeatures detect and extract and ORB features from the image. +function [features, validPoints] = helperDetectAndExtractFeatures(Irgb, ... + scaleFactor, numLevels, numPoints, varargin) + + % In this example, the images are already undistorted. In a general + % workflow, uncomment the following code to undistort the images. + % + % if nargin > 4 + % intrinsics = varargin{1}; + % end + % Irgb = undistortImage(Irgb, intrinsics); + + % Detect ORB features + Igray = im2gray(Irgb); + + points = detectORBFeatures(Igray, ScaleFactor=scaleFactor, NumLevels=numLevels); + + % Select a subset of features, uniformly distributed throughout the image + points = selectUniform(points, numPoints, size(Igray, 1:2)); + + % Extract features + [features, validPoints] = extractFeatures(Igray, points); +end + +% helperComputeHomography compute homography and evaluate reconstruction. +function [H, score, inliersIndex] = helperComputeHomography(matchedPoints1, matchedPoints2) + + [H, inliersLogicalIndex] = estgeotform2d( ... + matchedPoints1, matchedPoints2, "projective", ... + MaxNumTrials=1e3, MaxDistance=4, Confidence=90); + + inlierPoints1 = matchedPoints1(inliersLogicalIndex); + inlierPoints2 = matchedPoints2(inliersLogicalIndex); + + inliersIndex = find(inliersLogicalIndex); + + locations1 = inlierPoints1.Location; + locations2 = inlierPoints2.Location; + xy1In2 = transformPointsForward(H, locations1); + xy2In1 = transformPointsInverse(H, locations2); + error1in2 = sum((locations2 - xy1In2).^2, 2); + error2in1 = sum((locations1 - xy2In1).^2, 2); + + outlierThreshold = 6; + + score = sum(max(outlierThreshold-error1in2, 0)) + ... + sum(max(outlierThreshold-error2in1, 0)); +end + +% helperComputeFundamentalMatrix compute fundamental matrix and evaluate reconstruction. +function [F, score, inliersIndex] = helperComputeFundamentalMatrix(matchedPoints1, matchedPoints2) + + [F, inliersLogicalIndex] = estimateFundamentalMatrix( ... + matchedPoints1, matchedPoints2, Method="RANSAC",... + NumTrials=1e3, DistanceThreshold=4); + + inlierPoints1 = matchedPoints1(inliersLogicalIndex); + inlierPoints2 = matchedPoints2(inliersLogicalIndex); + + inliersIndex = find(inliersLogicalIndex); + + locations1 = inlierPoints1.Location; + locations2 = inlierPoints2.Location; + + % Distance from points to epipolar line + lineIn1 = epipolarLine(F', locations2); + error2in1 = (sum([locations1, ones(size(locations1, 1),1)].* lineIn1, 2)).^2 ... + ./ sum(lineIn1(:,1:2).^2, 2); + lineIn2 = epipolarLine(F, locations1); + error1in2 = (sum([locations2, ones(size(locations2, 1),1)].* lineIn2, 2)).^2 ... + ./ sum(lineIn2(:,1:2).^2, 2); + + outlierThreshold = 4; + + score = sum(max(outlierThreshold-error1in2, 0)) + ... + sum(max(outlierThreshold-error2in1, 0)); +end + +% helperTriangulateTwoFrames triangulate two frames to initialize the map. +function [isValid, xyzPoints, inlierIdx] = helperTriangulateTwoFrames(... + pose1, pose2, matchedPoints1, matchedPoints2, intrinsics, minParallax) + + camMatrix1 = cameraProjection(intrinsics, pose2extr(pose1)); + camMatrix2 = cameraProjection(intrinsics, pose2extr(pose2)); + + [xyzPoints, reprojectionErrors, isInFront] = triangulate(matchedPoints1, ... + matchedPoints2, camMatrix1, camMatrix2); + + % Filter points by view direction and reprojection error + minReprojError = 1; + inlierIdx = isInFront & reprojectionErrors < minReprojError; + xyzPoints = xyzPoints(inlierIdx ,:); + + % A good two-view with significant parallax + ray1 = xyzPoints - pose1.Translation; + ray2 = xyzPoints - pose2.Translation; + cosAngle = sum(ray1 .* ray2, 2) ./ (vecnorm(ray1, 2, 2) .* vecnorm(ray2, 2, 2)); + + % Check parallax + isValid = all(cosAngle < cosd(minParallax) & cosAngle>0); +end + +% helperEstimateTrajectoryError calculate the tracking error. +function rmse = helperEstimateTrajectoryError(gTruth, cameraPoses) + locations = vertcat(cameraPoses.AbsolutePose.Translation); + gLocations = vertcat(gTruth.Translation); + scale = median(vecnorm(gLocations, 2, 2))/ median(vecnorm(locations, 2, 2)); + scaledLocations = locations * scale; + + rmse = sqrt(mean( sum((scaledLocations - gLocations).^2, 2) )); + disp(['Absolute RMSE for key frame trajectory (m): ', num2str(rmse)]); +end + +% helperUpdateGlobalMap update 3-D locations of map points after pose graph optimization +function mapPointSet = helperUpdateGlobalMap(... + mapPointSet, vSetKeyFrames, vSetKeyFramesOptim) + %helperUpdateGlobalMap update map points after pose graph optimization + posesOld = vSetKeyFrames.Views.AbsolutePose; + posesNew = vSetKeyFramesOptim.Views.AbsolutePose; + positionsOld = mapPointSet.WorldPoints; + positionsNew = positionsOld; + indices = 1:mapPointSet.Count; + + % Update world location of each map point based on the new absolute pose of + % the corresponding major view + for i = indices + majorViewIds = mapPointSet.RepresentativeViewId(i); + poseNew = posesNew(majorViewIds).A; + tform = affinetform3d(poseNew/posesOld(majorViewIds).A); + positionsNew(i, :) = transformPointsForward(tform, positionsOld(i, :)); + end + mapPointSet = updateWorldPoints(mapPointSet, indices, positionsNew); +end + +% function saveKeyFramePoints(dirPath, frameIndex, featurePoints) +% % Extract locations and corresponding point indices +% locations = featurePoints.Location; +% indices = (1:size(locations, 1))'; % Create an index array +% dataMatrix = [indices, locations]; +% +% % Define filename for CSV +% csvFilename = sprintf('%s/KeyFramePoints_%04d.csv', dirPath, frameIndex); +% +% % Write matrix to CSV +% writematrix(dataMatrix, csvFilename); +% end + +function saveKeyFramePoints(dirPath, keyFrameId, featurePoints, mapPointsIdx) + % Ensure the directory exists + if ~exist(dirPath, 'dir') + mkdir(dirPath); + end + + % Define the filename for the CSV file + csvFilename = sprintf('%s/KeyFramePoints_%04d.csv', dirPath, keyFrameId); + + % Extract pixel locations from the feature points + pixelLocations = featurePoints.Location; % This should be an Nx2 matrix + + % Combine the indices, pixel locations, and corresponding world points indices into one matrix + dataMatrix = [pixelLocations, mapPointsIdx]; % Concatenate horizontally + + % Write the combined data to a CSV file + writematrix(dataMatrix, csvFilename); +end + + diff --git a/target/classes/vslam/vslam_implementation_rgbd.m b/target/classes/vslam/vslam_implementation_rgbd.m new file mode 100755 index 0000000000000000000000000000000000000000..b32fa8d4700cd7be40e269ab25361ddb6aaf16e6 --- /dev/null +++ b/target/classes/vslam/vslam_implementation_rgbd.m @@ -0,0 +1,657 @@ +function vslam_implementation_rgbd(dataset_name) + + % Import dependencies + addpath('./Mathworks_VSLAM_RGBD/'); + + % Define the base folder for datasets + datasetFolder = [dataset_name, '/']; + + % Check if the dataset exists, if not download and prepare it + if ~exist(datasetFolder, 'dir') + if strcmp(dataset_name, 'tum_rgbd_dataset') + % Define the URL and local folder for download + baseDownloadURL = "https://cvg.cit.tum.de/rgbd/dataset/freiburg3/rgbd_dataset_freiburg3_long_office_household.tgz"; + dataFolder = fullfile('tum_rgbd_dataset', filesep); + tgzFileName = [dataFolder, 'fr3_office.tgz']; + + % Create a folder to save the downloaded file + if ~exist(dataFolder, 'dir') + mkdir(dataFolder); + disp('Downloading fr3_office.tgz (1.38 GB). This download can take a few minutes.'); + h = waitbar(0, 'Downloading Dataset... Please wait.', 'Name', 'Downloading fr3_office'); + websave(tgzFileName, baseDownloadURL, weboptions('Timeout', Inf)); + % Update and close waitbar after download completes + waitbar(1, h, 'Download Complete. Extracting...'); + pause(1); % Pause to show complete message + close(h); + + % Extract contents of the downloaded file + disp('Extracting fr3_office.tgz (1.38 GB) ...'); + h = waitbar(0, 'Extracting files... This may take a while.', 'Name', 'Extracting Data'); + untar(tgzFileName, dataFolder); + + % Close waitbar after extraction completes + waitbar(1, h, 'Extraction Complete.'); + pause(1); % Pause to show complete message + close(h); + end + + imageFolder = [dataFolder, 'rgbd_dataset_freiburg3_long_office_household/']; + + % Initialize image dataset stores for color and depth images + imgFolderColor = [imageFolder, 'rgb/']; + imgFolderDepth = [imageFolder, 'depth/']; + imdsColor = imageDatastore(imgFolderColor); + imdsDepth = imageDatastore(imgFolderDepth); + + % Note that the color and depth images are generated in an un-synchronized way in the dataset. Therefore, we need to associate color images to depth images based on the time stamp. + % Load time stamp data of color images + timeColor = helperImportTimestampFile([imageFolder, 'rgb.txt']); + + % Load time stamp data of depth images + timeDepth = helperImportTimestampFile([imageFolder, 'depth.txt']); + + % Align the time stamp + indexPairs = helperAlignTimestamp(timeColor, timeDepth); + + % Select the synchronized image data + imdsColor = subset(imdsColor, indexPairs(:, 1)); + imdsDepth = subset(imdsDepth, indexPairs(:, 2)); + + elseif strcmp(dataset_name, 'imperial_college_london') + % Define the URL and local folder for download + baseDownloadURL = "http://www.doc.ic.ac.uk/~ahanda/living_room_traj2_frei_png.tar.gz"; + dataFolder = fullfile('imperial_college_london', filesep); + tgzFileName = [dataFolder, 'living_room_traj2_frei_png.tar.gz']; + + % Create a folder to save the downloaded file + if ~exist(dataFolder, 'dir') + mkdir(dataFolder); + disp('Downloading living_room_traj2_frei_png.tar.gz (486 MB). This download can take a few minutes.'); + h = waitbar(0, 'Downloading Dataset... Please wait.', 'Name', 'Downloading living_room_traj2'); + websave(tgzFileName, baseDownloadURL, weboptions('Timeout', Inf)); + % Update and close waitbar after download completes + waitbar(1, h, 'Download Complete. Extracting...'); + pause(1); % Pause to show complete message + close(h); + + % Extract contents of the downloaded file + disp('Extracting living_room_traj2 (486 MB) ...'); + h = waitbar(0, 'Extracting files... This may take a while.', 'Name', 'Extracting Data'); + untar(tgzFileName, dataFolder); + + % Close waitbar after extraction completes + waitbar(1, h, 'Extraction Complete.'); + pause(1); % Pause to show complete message + close(h); + end + + imageFolder = [dataFolder]; + + % Initialize image dataset stores for color and depth images + imgFolderColor = [imageFolder, 'rgb/']; + imgFolderDepth = [imageFolder, 'depth/']; + imdsColor = imageDatastore(imgFolderColor); + imdsDepth = imageDatastore(imgFolderDepth); + else + error('Dataset name not recognized or dataset-specific download steps not defined.'); + end + else + % If dataset is already present, set the image folder path + if strcmp(dataset_name, 'tum_rgbd_dataset') + imageFolder = [datasetFolder, 'rgbd_dataset_freiburg3_long_office_household/']; + % Initialize image dataset stores for color and depth images + imgFolderColor = [imageFolder, 'rgb/']; + imgFolderDepth = [imageFolder, 'depth/']; + imdsColor = imageDatastore(imgFolderColor); + imdsDepth = imageDatastore(imgFolderDepth); + + % Note that the color and depth images are generated in an un-synchronized way in the dataset. Therefore, we need to associate color images to depth images based on the time stamp. + % Load time stamp data of color images + timeColor = helperImportTimestampFile([imageFolder, 'rgb.txt']); + + % Load time stamp data of depth images + timeDepth = helperImportTimestampFile([imageFolder, 'depth.txt']); + + % Align the time stamp + indexPairs = helperAlignTimestamp(timeColor, timeDepth); + + % Select the synchronized image data + imdsColor = subset(imdsColor, indexPairs(:, 1)); + imdsDepth = subset(imdsDepth, indexPairs(:, 2)); + elseif strcmp(dataset_name, 'imperial_college_london') + imageFolder = [datasetFolder]; + + % Initialize image dataset stores for color and depth images + imgFolderColor = [imageFolder, 'rgb/']; + imgFolderDepth = [imageFolder, 'depth/']; + imdsColor = imageDatastore(imgFolderColor); + imdsDepth = imageDatastore(imgFolderDepth); + end + end + + % Process the image sequence + [worldPointSetOutput, optimizedPoses, pointCloudsAll, intrinsics] = ProcessImageSequence(imdsColor, imdsDepth); + + % Save the outputs to .mat files + % save('worldPointSetOutput.mat', 'worldPointSetOutput'); + % save('optimizedPoses.mat', 'optimizedPoses'); + % save('pointCloudsAll.mat', 'pointCloudsAll'); + % save('cameraIntrinsics.mat', 'intrinsics'); + + % save outputs to CSV files in directories given as name: + savePosesToCSV(optimizedPoses, 'CameraPoses'); + savePointCloudToCSV(pointCloudsAll); + saveIntrinsicsToCSV(intrinsics); + + % Iterate over KeyFrames and execute extractPointsByViewId + keyFramesDir = './KeyFrames'; + keyFrameFiles = dir(fullfile(keyFramesDir, 'KeyFrame_*.png')); + + for i = 1:length(keyFrameFiles) + filename = keyFrameFiles(i).name; + viewId = str2double(regexp(filename, '\d+', 'match', 'once')); % Extracting the numeric part from filename + extractPointsByViewId(viewId, worldPointSetOutput); + end + +end + + +function [worldPointSetOutput, optimizedPoses, pointCloudsAll, intrinsics] = ProcessImageSequence(imdsColor, imdsDepth) + % Inspect the first RGB-D image + currFrameIdx = 1; + currIcolor = readimage(imdsColor, currFrameIdx); + currIdepth = readimage(imdsDepth, currFrameIdx); + % imshowpair(currIcolor, currIdepth, "montage"); + + % Map Initialization: The pipeline starts by initializing the map that holds 3-D world points. + % This step is crucial and has a significant impact on the accuracy of the final SLAM result. + % Initial ORB feature points are extracted from the first color image using helperDetectAndExtractFeatures. + % Their corresponding 3-D world locations can be computed from the pixel coordinates of the feature + % points and the depth value using helperReconstructFromRGBD. + + % Set random seed for reproducibility + rng(0); + + % Create a cameraIntrinsics object to store the camera intrinsic parameters. + % The intrinsics for the dataset can be found at the following page: + % https://vision.in.tum.de/data/datasets/rgbd-dataset/file_formats + focalLength = [535.4, 539.2]; % in units of pixels + principalPoint = [320.1, 247.6]; % in units of pixels + imageSize = size(currIcolor,[1,2]); % in pixels [mrows, ncols] + depthFactor = 5e3; + intrinsics = cameraIntrinsics(focalLength,principalPoint,imageSize); + + % Detect and extract ORB features from the color image + scaleFactor = 1.2; + numLevels = 8; + [currFeatures, currPoints] = helperDetectAndExtractFeatures(currIcolor, scaleFactor, numLevels); + + initialPose = rigidtform3d(); + [xyzPoints, validIndex] = helperReconstructFromRGBD(currPoints, currIdepth, intrinsics, initialPose, depthFactor); + + % Initialize Place Recognition Database + % Loop detection is performed using the bags-of-words approach. A visual vocabulary represented as a bagOfFeatures object is created offline with the ORB descriptors extracted from a large set of images in the dataset by calling: + % bag = bagOfFeatures(imds,CustomExtractor=@helperORBFeatureExtractorFunction, TreeProperties=[5, 10], StrongestFeatures=1); + % where imds is an imageDatastore object storing the training images and helperORBFeatureExtractorFunction is the ORB feature extractor function. See Image Retrieval with Bag of Visual Words for more information. + % The loop closure process incrementally builds a database, represented as an invertedImageIndex object, that stores the visual word-to-image mapping based on the bag of ORB features. + + % Load the bag of features data created offline + bofData = load("bagOfFeaturesDataSLAM.mat"); + + % Initialize the place recognition database + loopDatabase = invertedImageIndex(bofData.bof, SaveFeatureLocations=false); + + % Add features of the first key frame to the database + currKeyFrameId = 1; + addImageFeatures(loopDatabase, currFeatures, currKeyFrameId); + + % Data Management and Visualization + % After the map is initialized using the first pair of color and depth image, you can use imageviewset and worldpointset to store the first key frames and the corresponding map points: + + % Create an empty imageviewset object to store key frames + vSetKeyFrames = imageviewset; + + % Create an empty worldpointset object to store 3-D map points + mapPointSet = worldpointset; + + % Add the first key frame + vSetKeyFrames = addView(vSetKeyFrames, currKeyFrameId, initialPose, Points=currPoints,... + Features=currFeatures.Features); + + % Add 3-D map points + [mapPointSet, rgbdMapPointsIdx] = addWorldPoints(mapPointSet, xyzPoints); + + % Add observations of the map points + mapPointSet = addCorrespondences(mapPointSet, currKeyFrameId, rgbdMapPointsIdx, validIndex); + + % Update view direction and depth + mapPointSet = updateLimitsAndDirection(mapPointSet, rgbdMapPointsIdx, vSetKeyFrames.Views); + + % Update representative view + mapPointSet = updateRepresentativeView(mapPointSet, rgbdMapPointsIdx, vSetKeyFrames.Views); + + % Visualize matched features in the first key frame + featurePlot = helperVisualizeMatchedFeaturesRGBD(currIcolor, currIdepth, currPoints(validIndex)); + + % Visualize initial map points and camera trajectory + xLim = [-4 4]; + yLim = [-3 1]; + zLim = [-1 6]; + mapPlot = helperVisualizeMotionAndStructure(vSetKeyFrames, mapPointSet, xLim, yLim, zLim); + + % Show legend + showLegend(mapPlot); + + % Tracking + % The tracking process is performed using every RGB-D image and determines when to insert a new key frame. + % ViewId of the last key frame + lastKeyFrameId = currKeyFrameId; + + % Index of the last key frame in the input image sequence + lastKeyFrameIdx = currFrameIdx; + + % Indices of all the key frames in the input image sequence + addedFramesIdx = lastKeyFrameIdx; + + currFrameIdx = 2; + isLoopClosed = false; + + % Each frame is processed as follows: + % ORB features are extracted for each new color image and then matched (using matchFeatures), with features in the last key frame that have known corresponding 3-D map points. + % Estimate the camera pose using Perspective-n-Point algorithm, which estimates the pose of a calibrated camera given a set of 3-D points and their corresponding 2-D projections using estworldpose. + % Given the camera pose, project the map points observed by the last key frame into the current frame and search for feature correspondences using matchFeaturesInRadius. + % With 3-D to 2-D correspondences in the current frame, refine the camera pose by performing a motion-only bundle adjustment using bundleAdjustmentMotion. + % Project the local map points into the current frame to search for more feature correspondences using matchFeaturesInRadius and refine the camera pose again using bundleAdjustmentMotion. + % The last step of tracking is to decide if the current frame should be a new key frame. A frame is a key frame if both of the following conditions are satisfied: + % At least 20 frames have passed since the last key frame or the current frame tracks fewer than 100 map points or 25% of points tracked by the reference key frame. + % The map points tracked by the current frame are fewer than 90% of points tracked by the reference key frame. + % If the current frame is to become a key frame, continue to the Local Mapping process. Otherwise, start Tracking for the next frame. + + % Main loop + isLastFrameKeyFrame = true; + while ~isLoopClosed && currFrameIdx < numel(imdsColor.Files) + + currIcolor = readimage(imdsColor, currFrameIdx); + currIdepth = readimage(imdsDepth, currFrameIdx); + + [currFeatures, currPoints] = helperDetectAndExtractFeatures(currIcolor, scaleFactor, numLevels); + + % Track the last key frame + % trackedMapPointsIdx: Indices of the map points observed in the current left frame + % trackedFeatureIdx: Indices of the corresponding feature points in the current left frame + [currPose, trackedMapPointsIdx, trackedFeatureIdx] = helperTrackLastKeyFrame(mapPointSet, ... + vSetKeyFrames.Views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor); + + if isempty(currPose) || numel(trackedMapPointsIdx) < 30 + currFrameIdx = currFrameIdx + 1; + continue + end + + % Track the local map and check if the current frame is a key frame. + % A frame is a key frame if both of the following conditions are satisfied: + % + % 1. At least 20 frames have passed since the last key frame or the + % current frame tracks fewer than 100 map points. + % 2. The map points tracked by the current frame are fewer than 90% of + % points tracked by the reference key frame. + % + % localKeyFrameIds: ViewId of the connected key frames of the current frame + numSkipFrames = 20; + numPointsKeyFrame = 100; + [localKeyFrameIds, currPose, trackedMapPointsIdx, trackedFeatureIdx, isKeyFrame] = ... + helperTrackLocalMap(mapPointSet, vSetKeyFrames, trackedMapPointsIdx, ... + trackedFeatureIdx, currPose, currFeatures, currPoints, intrinsics, scaleFactor, numLevels, ... + isLastFrameKeyFrame, lastKeyFrameIdx, currFrameIdx, numSkipFrames, numPointsKeyFrame); + + % Visualize matched features + updatePlot(featurePlot, currIcolor, currIdepth, currPoints(trackedFeatureIdx)); + + if ~isKeyFrame + currFrameIdx = currFrameIdx + 1; + isLastFrameKeyFrame = false; + continue + else + % Match feature points between the stereo images and get the 3-D world positions + [xyzPoints, validIndex] = helperReconstructFromRGBD(currPoints, currIdepth, ... + intrinsics, currPose, depthFactor); + + [untrackedFeatureIdx, ia] = setdiff(validIndex, trackedFeatureIdx); + xyzPoints = xyzPoints(ia, :); + isLastFrameKeyFrame = true; + end + + % Update current key frame ID + currKeyFrameId = currKeyFrameId + 1; + + % Local Mapping + % Local mapping is performed for every key frame. When a new key frame is determined, add it to the key frames and update the attributes of the map points observed by the new key frame. To ensure that mapPointSet contains as few outliers as possible, a valid map point must be observed in at least 3 key frames. + % New map points are created by triangulating ORB feature points in the current key frame and its connected key frames. For each unmatched feature point in the current key frame, search for a match with other unmatched points in the connected key frames using matchFeatures. The local bundle adjustment refines the pose of the current key frame, the poses of connected key frames, and all the map points observed in these key frames. + + % Add the new key frame + [mapPointSet, vSetKeyFrames] = helperAddNewKeyFrame(mapPointSet, vSetKeyFrames, ... + currPose, currFeatures, currPoints, trackedMapPointsIdx, trackedFeatureIdx, localKeyFrameIds); + + % Remove outlier map points that are observed in fewer than 3 key frames + if currKeyFrameId == 2 + triangulatedMapPointsIdx = []; + end + + [mapPointSet, trackedMapPointsIdx] = ... + helperCullRecentMapPoints(mapPointSet, trackedMapPointsIdx, triangulatedMapPointsIdx, ... + rgbdMapPointsIdx); + + % Add new map points computed from disparity + [mapPointSet, rgbdMapPointsIdx] = addWorldPoints(mapPointSet, xyzPoints); + mapPointSet = addCorrespondences(mapPointSet, currKeyFrameId, rgbdMapPointsIdx, ... + untrackedFeatureIdx); + + % Create new map points by triangulation + minNumMatches = 10; + minParallax = 0.35; + [mapPointSet, vSetKeyFrames, triangulatedMapPointsIdx, rgbdMapPointsIdx] = helperCreateNewMapPointsStereo( ... + mapPointSet, vSetKeyFrames, currKeyFrameId, intrinsics, scaleFactor, minNumMatches, minParallax, ... + untrackedFeatureIdx, rgbdMapPointsIdx); + + % Update view direction and depth + mapPointSet = updateLimitsAndDirection(mapPointSet, [triangulatedMapPointsIdx; rgbdMapPointsIdx], ... + vSetKeyFrames.Views); + + % Update representative view + mapPointSet = updateRepresentativeView(mapPointSet, [triangulatedMapPointsIdx; rgbdMapPointsIdx], ... + vSetKeyFrames.Views); + + % Local bundle adjustment + [mapPointSet, vSetKeyFrames, triangulatedMapPointsIdx, rgbdMapPointsIdx] = ... + helperLocalBundleAdjustmentStereo(mapPointSet, vSetKeyFrames, ... + currKeyFrameId, intrinsics, triangulatedMapPointsIdx, rgbdMapPointsIdx); + + % Check if the KeyFrames directory exists; if not, create it + keyFramesDir = './KeyFrames'; + if ~exist(keyFramesDir, 'dir') + mkdir(keyFramesDir); + end + + % Store feature locations for this key frame + keyFramePointsDir = './KeyFramePoints'; + if ~exist(keyFramePointsDir, 'dir') + mkdir(keyFramePointsDir); + end + + % Save the current key frame image using currKeyFrameId + filename = sprintf('%s/KeyFrame_%04d.png', keyFramesDir, currKeyFrameId); + imwrite(currIcolor, filename); + + % Save feature points information + saveKeyFramePoints(keyFramePointsDir, currKeyFrameId, currPoints(trackedFeatureIdx), trackedMapPointsIdx); + + % Visualize 3-D world points and camera trajectory + updatePlot(mapPlot, vSetKeyFrames, mapPointSet); + + % Loop Closure + % The loop closure detection step takes the current key frame processed by the local mapping process and tries to detect and close the loop. Loop candidates are identified by querying images in the database that are visually similar to the current key frame using evaluateImageRetrieval. A candidate key frame is valid if it is not connected to the last key frame and three of its neighbor key frames are loop candidates. + % When a valid loop candidate is found, use estgeotform3d to compute the relative pose between the loop candidate frame and the current key frame. The relative pose represents a 3-D rigid transformation stored in a rigidtform3d object. Then add the loop connection with the relative pose and update mapPointSet and vSetKeyFrames. + % Check loop closure after some key frames have been created + if currKeyFrameId > 20 + + % Minimum number of feature matches of loop edges + loopEdgeNumMatches = 120; + + % Detect possible loop closure key frame candidates + [isDetected, validLoopCandidates] = helperCheckLoopClosure(vSetKeyFrames, currKeyFrameId, ... + loopDatabase, currIcolor, loopEdgeNumMatches); + + if isDetected + % Add loop closure connections + maxDistance = 0.1; + [isLoopClosed, mapPointSet, vSetKeyFrames] = helperAddLoopConnectionsStereo(... + mapPointSet, vSetKeyFrames, validLoopCandidates, currKeyFrameId, ... + currFeatures, currPoints, loopEdgeNumMatches, maxDistance); + end + end + + % If no loop closure is detected, add current features into the database + if ~isLoopClosed + addImageFeatures(loopDatabase, currFeatures, currKeyFrameId); + end + + % Update IDs and indices + lastKeyFrameId = currKeyFrameId; + lastKeyFrameIdx = currFrameIdx; + addedFramesIdx = [addedFramesIdx; currFrameIdx]; %#ok + currFrameIdx = currFrameIdx + 1; + end % End of main loop + + % Finally, apply pose graph optimization over the essential graph in vSetKeyFrames to correct the drift. The essential graph is created internally by removing connections with fewer than minNumMatches matches in the covisibility graph. After pose graph optimization, update the 3-D locations of the map points using the optimized poses. + + % Optimize the poses + minNumMatches = 50; + vSetKeyFramesOptim = optimizePoses(vSetKeyFrames, minNumMatches, Tolerance=1e-16); + + % Update map points after optimizing the poses + mapPointSet = helperUpdateGlobalMap(mapPointSet, vSetKeyFrames, vSetKeyFramesOptim); + + updatePlot(mapPlot, vSetKeyFrames, mapPointSet); + + % Plot the optimized camera trajectory + optimizedPoses = poses(vSetKeyFramesOptim); + plotOptimizedTrajectory(mapPlot, optimizedPoses) + + % Update legend + showLegend(mapPlot); + + worldPointSetOutput = mapPointSet; + + % Dense Reconstruction from Depth Image + % Given the refined camera poses, you can reproject all the valid image points in the associated depth images back to the 3-D space to perform dense reconstruction. + % Create an array of pointCloud objects to store the world points constructed + + % from the key frames + ptClouds = repmat(pointCloud(zeros(1, 3)), numel(addedFramesIdx), 1); + + % Ignore image points at the boundary + offset = 40; + [X, Y] = meshgrid(offset:2:imageSize(2)-offset, offset:2:imageSize(1)-offset); + + for i = 1: numel(addedFramesIdx) + Icolor = readimage(imdsColor, addedFramesIdx(i)); + Idepth = readimage(imdsDepth, addedFramesIdx(i)); + + [xyzPoints, validIndex] = helperReconstructFromRGBD([X(:), Y(:)], ... + Idepth, intrinsics, optimizedPoses.AbsolutePose(i), depthFactor); + + colors = zeros(numel(X), 1, 'like', Icolor); + for j = 1:numel(X) + colors(j, 1:3) = Icolor(Y(j), X(j), :); + end + ptClouds(i) = pointCloud(xyzPoints, Color=colors(validIndex, :)); + end + + % Concatenate the point clouds + pointCloudsAll = pccat(ptClouds); + + figure + pcshow(pointCloudsAll,VerticalAxis="y", VerticalAxisDir="down"); + xlabel('X') + ylabel('Y') + zlabel('Z') +end + +%% Helper functions + +% helperImportTimestampFile Import time stamp file + +function timestamp = helperImportTimestampFile(filename) + % Input handling + dataLines = [4, Inf]; + + %% Set up the Import Options and import the data + opts = delimitedTextImportOptions("NumVariables", 2); + + % Specify range and delimiter + opts.DataLines = dataLines; + opts.Delimiter = " "; + + % Specify column names and types + opts.VariableNames = ["VarName1", "Var2"]; + opts.SelectedVariableNames = "VarName1"; + opts.VariableTypes = ["double", "string"]; + + % Specify file level properties + opts.ExtraColumnsRule = "ignore"; + opts.EmptyLineRule = "read"; + opts.ConsecutiveDelimitersRule = "join"; + opts.LeadingDelimitersRule = "ignore"; + + % Specify variable properties + opts = setvaropts(opts, "Var2", "WhitespaceRule", "preserve"); + opts = setvaropts(opts, "Var2", "EmptyFieldRule", "auto"); + + % Import the data + data = readtable(filename, opts); + + % Convert to output type + timestamp = table2array(data); +end + +% helperAlignTimestamp align time stamp of color and depth images. +function indexPairs = helperAlignTimestamp(timeColor, timeDepth) + idxDepth = 1; + indexPairs = zeros(numel(timeColor), 2); + for i = 1:numel(timeColor) + for j = idxDepth : numel(timeDepth) + if abs(timeColor(i) - timeDepth(j)) < 1e-4 + idxDepth = j; + indexPairs(i, :) = [i, j]; + break + elseif timeDepth(j) - timeColor(i) > 1e-3 + break + end + end + end + indexPairs = indexPairs(indexPairs(:,1)>0, :); +end + +% helperDetectAndExtractFeatures detect and extract and ORB features from the image. +function [features, validPoints] = helperDetectAndExtractFeatures(Irgb, scaleFactor, numLevels) + + numPoints = 1000; + + % Detect ORB features + Igray = rgb2gray(Irgb); + + points = detectORBFeatures(Igray, ScaleFactor=scaleFactor, NumLevels=numLevels); + + % Select a subset of features, uniformly distributed throughout the image + points = selectUniform(points, numPoints, size(Igray, 1:2)); + + % Extract features + [features, validPoints] = extractFeatures(Igray, points); +end + +% helperReconstructFromRGBD reconstruct scene from color and depth image. + +function [xyzPoints, validIndex] = helperReconstructFromRGBD(points, ... + depthMap, intrinsics, currPose, depthFactor) + + ptcloud = pcfromdepth(depthMap,depthFactor,intrinsics,ImagePoints=points, DepthRange=[0.1, 5]); + + isPointValid = ~isnan(ptcloud.Location(:, 1)); + xyzPoints = ptcloud.Location(isPointValid, :); + xyzPoints = transformPointsForward(currPose, xyzPoints); + validIndex = find(isPointValid); +end + +% helperCullRecentMapPoints cull recently added map points. +function [mapPointSet, mapPointsIdx] = ... + helperCullRecentMapPoints(mapPointSet, mapPointsIdx, newPointIdx, rgbdMapPointsIndices) + outlierIdx = setdiff([newPointIdx; rgbdMapPointsIndices], mapPointsIdx); + if ~isempty(outlierIdx) + mapPointSet = removeWorldPoints(mapPointSet, outlierIdx); + mapPointsIdx = mapPointsIdx - arrayfun(@(x) nnz(x>outlierIdx), mapPointsIdx); + end +end + +% helperEstimateTrajectoryError calculate the tracking error. +function rmse = helperEstimateTrajectoryError(gTruth, cameraPoses) + locations = vertcat(cameraPoses.AbsolutePose.Translation); + gLocations = vertcat(gTruth.Translation); + scale = median(vecnorm(gLocations, 2, 2))/ median(vecnorm(locations, 2, 2)); + scaledLocations = locations * scale; + + rmse = sqrt(mean( sum((scaledLocations - gLocations).^2, 2) )); + disp(['Absolute RMSE for key frame trajectory (m): ', num2str(rmse)]); +end + +% helperUpdateGlobalMap update 3-D locations of map points after pose graph optimization +function mapPointSet = helperUpdateGlobalMap(mapPointSet, vSetKeyFrames, vSetKeyFramesOptim) + + posesOld = vSetKeyFrames.Views.AbsolutePose; + posesNew = vSetKeyFramesOptim.Views.AbsolutePose; + positionsOld = mapPointSet.WorldPoints; + positionsNew = positionsOld; + indices = 1:mapPointSet.Count; + + % Update world location of each map point based on the new absolute pose of + % the corresponding major view + for i = 1: mapPointSet.Count + majorViewIds = mapPointSet.RepresentativeViewId(i); + tform = rigidtform3d(posesNew(majorViewIds).A/posesOld(majorViewIds).A); + positionsNew(i, :) = transformPointsForward(tform, positionsOld(i, :)); + end + mapPointSet = updateWorldPoints(mapPointSet, indices, positionsNew); +end + +% CSV file creation for points within keyframe +function saveKeyFramePoints(dirPath, keyFrameId, featurePoints, mapPointsIdx) + % Ensure the directory exists + if ~exist(dirPath, 'dir') + mkdir(dirPath); + end + + % Define the filename for the CSV file + csvFilename = sprintf('%s/KeyFramePoints_%04d.csv', dirPath, keyFrameId); + + % Extract pixel locations from the feature points + pixelLocations = featurePoints.Location; % This should be an Nx2 matrix + + % Combine the indices, pixel locations, and corresponding world points indices into one matrix + dataMatrix = [pixelLocations, mapPointsIdx]; % Concatenate horizontally + + % Write the combined data to a CSV file + writematrix(dataMatrix, csvFilename); +end + + +function savePointCloudToCSV(pointCloudsAll) + mat = [pointCloudsAll.Location, cast(pointCloudsAll.Color, "single")]; + writematrix(mat, "pointcloud.csv"); +end + + +function savePosesToCSV(optimizedPoses, dirPath) + mkdir(dirPath) + + t_size = size(optimizedPoses); + for i=1:t_size(1) + p = optimizedPoses.AbsolutePose(i, 1); + % first row will be translation + % second-fifth row will be rotation + mat = [p.Translation; p.R]; + idx = optimizedPoses.ViewId(i,1); + + % save to directory + fname = sprintf('%s/Pose_%04d.csv', dirPath, idx); + writematrix(mat, fname); + end +end + + +function saveIntrinsicsToCSV(intrinsics) + mat = [intrinsics.FocalLength, 0 ; + intrinsics.PrincipalPoint, 0 ; + intrinsics.ImageSize, 0 ; + intrinsics.K]; + + writematrix(mat, 'CameraIntrinsics.csv') +end \ No newline at end of file diff --git a/target/classes/yolo/YOLODetector.class b/target/classes/yolo/YOLODetector.class new file mode 100644 index 0000000000000000000000000000000000000000..f41919e9d9b3cad23d45df232a6d27cee3bcf620 Binary files /dev/null and b/target/classes/yolo/YOLODetector.class differ diff --git a/target/classes/yolo/YOLONet$ObjectDetectionResult.class b/target/classes/yolo/YOLONet$ObjectDetectionResult.class new file mode 100644 index 0000000000000000000000000000000000000000..2e245f6a78ad2e704f17b4584206c3ab44f8ae4f Binary files /dev/null and b/target/classes/yolo/YOLONet$ObjectDetectionResult.class differ diff --git a/target/classes/yolo/YOLONet.class b/target/classes/yolo/YOLONet.class new file mode 100644 index 0000000000000000000000000000000000000000..98b94c1844a60be367fa060fced89c6fbdc7a52c Binary files /dev/null and b/target/classes/yolo/YOLONet.class differ diff --git a/target/classes/yolo/coco.names b/target/classes/yolo/coco.names new file mode 100644 index 0000000000000000000000000000000000000000..16315f2becec9705017bfaf1b9fb81ca2a83c0b0 --- /dev/null +++ b/target/classes/yolo/coco.names @@ -0,0 +1,80 @@ +person +bicycle +car +motorbike +aeroplane +bus +train +truck +boat +traffic light +fire hydrant +stop sign +parking meter +bench +bird +cat +dog +horse +sheep +cow +elephant +bear +zebra +giraffe +backpack +umbrella +handbag +tie +suitcase +frisbee +skis +snowboard +sports ball +kite +baseball bat +baseball glove +skateboard +surfboard +tennis racket +bottle +wine glass +cup +fork +knife +spoon +bowl +banana +apple +sandwich +orange +broccoli +carrot +hot dog +pizza +donut +cake +chair +sofa +pottedplant +bed +diningtable +toilet +tvmonitor +laptop +mouse +remote +keyboard +cell phone +microwave +oven +toaster +sink +refrigerator +book +clock +vase +scissors +teddy bear +hair drier +toothbrush \ No newline at end of file diff --git a/target/classes/yolo/yolov4.cfg b/target/classes/yolo/yolov4.cfg new file mode 100644 index 0000000000000000000000000000000000000000..2985a313f610e032732e388ca6d0a7729ae7f267 --- /dev/null +++ b/target/classes/yolo/yolov4.cfg @@ -0,0 +1,1157 @@ +[net] +batch=64 +subdivisions=8 +# Training +#width=512 +#height=512 +width=608 +height=608 +channels=3 +momentum=0.949 +decay=0.0005 +angle=0 +saturation = 1.5 +exposure = 1.5 +hue=.1 + +learning_rate=0.0013 +burn_in=1000 +max_batches = 500500 +policy=steps +steps=400000,450000 +scales=.1,.1 + +#cutmix=1 +mosaic=1 + +#:104x104 54:52x52 85:26x26 104:13x13 for 416 + +[convolutional] +batch_normalize=1 +filters=32 +size=3 +stride=1 +pad=1 +activation=mish + +# Downsample + +[convolutional] +batch_normalize=1 +filters=64 +size=3 +stride=2 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=mish + +[route] +layers = -2 + +[convolutional] +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=32 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + +[convolutional] +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=mish + +[route] +layers = -1,-7 + +[convolutional] +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=mish + +# Downsample + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=2 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=mish + +[route] +layers = -2 + +[convolutional] +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + +[convolutional] +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=64 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + +[convolutional] +batch_normalize=1 +filters=64 +size=1 +stride=1 +pad=1 +activation=mish + +[route] +layers = -1,-10 + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=mish + +# Downsample + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=2 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=mish + +[route] +layers = -2 + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=128 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=mish + +[route] +layers = -1,-28 + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=mish + +# Downsample + +[convolutional] +batch_normalize=1 +filters=512 +size=3 +stride=2 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=mish + +[route] +layers = -2 + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=256 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=mish + +[route] +layers = -1,-28 + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=mish + +# Downsample + +[convolutional] +batch_normalize=1 +filters=1024 +size=3 +stride=2 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=mish + +[route] +layers = -2 + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=512 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=512 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=512 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=mish + +[convolutional] +batch_normalize=1 +filters=512 +size=3 +stride=1 +pad=1 +activation=mish + +[shortcut] +from=-3 +activation=linear + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=mish + +[route] +layers = -1,-16 + +[convolutional] +batch_normalize=1 +filters=1024 +size=1 +stride=1 +pad=1 +activation=mish + +########################## + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=leaky + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=1024 +activation=leaky + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=leaky + +### SPP ### +[maxpool] +stride=1 +size=5 + +[route] +layers=-2 + +[maxpool] +stride=1 +size=9 + +[route] +layers=-4 + +[maxpool] +stride=1 +size=13 + +[route] +layers=-1,-3,-5,-6 +### End SPP ### + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=leaky + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=1024 +activation=leaky + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=leaky + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=leaky + +[upsample] +stride=2 + +[route] +layers = 85 + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=leaky + +[route] +layers = -1, -3 + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=leaky + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=512 +activation=leaky + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=leaky + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=512 +activation=leaky + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=leaky + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=leaky + +[upsample] +stride=2 + +[route] +layers = 54 + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=leaky + +[route] +layers = -1, -3 + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=leaky + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=256 +activation=leaky + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=leaky + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=256 +activation=leaky + +[convolutional] +batch_normalize=1 +filters=128 +size=1 +stride=1 +pad=1 +activation=leaky + +########################## + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=256 +activation=leaky + +[convolutional] +size=1 +stride=1 +pad=1 +filters=255 +activation=linear + + +[yolo] +mask = 0,1,2 +anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401 +classes=80 +num=9 +jitter=.3 +ignore_thresh = .7 +truth_thresh = 1 +scale_x_y = 1.2 +iou_thresh=0.213 +cls_normalizer=1.0 +iou_normalizer=0.07 +iou_loss=ciou +nms_kind=greedynms +beta_nms=0.6 +max_delta=5 + + +[route] +layers = -4 + +[convolutional] +batch_normalize=1 +size=3 +stride=2 +pad=1 +filters=256 +activation=leaky + +[route] +layers = -1, -16 + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=leaky + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=512 +activation=leaky + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=leaky + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=512 +activation=leaky + +[convolutional] +batch_normalize=1 +filters=256 +size=1 +stride=1 +pad=1 +activation=leaky + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=512 +activation=leaky + +[convolutional] +size=1 +stride=1 +pad=1 +filters=255 +activation=linear + + +[yolo] +mask = 3,4,5 +anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401 +classes=80 +num=9 +jitter=.3 +ignore_thresh = .7 +truth_thresh = 1 +scale_x_y = 1.1 +iou_thresh=0.213 +cls_normalizer=1.0 +iou_normalizer=0.07 +iou_loss=ciou +nms_kind=greedynms +beta_nms=0.6 +max_delta=5 + + +[route] +layers = -4 + +[convolutional] +batch_normalize=1 +size=3 +stride=2 +pad=1 +filters=512 +activation=leaky + +[route] +layers = -1, -37 + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=leaky + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=1024 +activation=leaky + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=leaky + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=1024 +activation=leaky + +[convolutional] +batch_normalize=1 +filters=512 +size=1 +stride=1 +pad=1 +activation=leaky + +[convolutional] +batch_normalize=1 +size=3 +stride=1 +pad=1 +filters=1024 +activation=leaky + +[convolutional] +size=1 +stride=1 +pad=1 +filters=255 +activation=linear + + +[yolo] +mask = 6,7,8 +anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401 +classes=80 +num=9 +jitter=.3 +ignore_thresh = .7 +truth_thresh = 1 +random=1 +scale_x_y = 1.05 +iou_thresh=0.213 +cls_normalizer=1.0 +iou_normalizer=0.07 +iou_loss=ciou +nms_kind=greedynms +beta_nms=0.6 +max_delta=5 diff --git a/target/classes/yolo/yolov4.weights b/target/classes/yolo/yolov4.weights new file mode 100644 index 0000000000000000000000000000000000000000..921f4406ecaa54a53031dd695e7bcd96f5dd9be2 Binary files /dev/null and b/target/classes/yolo/yolov4.weights differ diff --git a/target/maven-status/maven-compiler-plugin/compile/default-compile/createdFiles.lst b/target/maven-status/maven-compiler-plugin/compile/default-compile/createdFiles.lst new file mode 100644 index 0000000000000000000000000000000000000000..9ed0cd1af0980717fffc73a9f4157439ffba674d --- /dev/null +++ b/target/maven-status/maven-compiler-plugin/compile/default-compile/createdFiles.lst @@ -0,0 +1,2 @@ +yolo/YOLONet$ObjectDetectionResult.class +yolo/YOLONet.class diff --git a/target/maven-status/maven-compiler-plugin/compile/default-compile/inputFiles.lst b/target/maven-status/maven-compiler-plugin/compile/default-compile/inputFiles.lst new file mode 100644 index 0000000000000000000000000000000000000000..aede6fb4c2cff93d65d71f3e57063c7f11326e6c --- /dev/null +++ b/target/maven-status/maven-compiler-plugin/compile/default-compile/inputFiles.lst @@ -0,0 +1,16 @@ +/Users/jack.edelist/Desktop/group8/src/main/java/object_detection/types/ObjectSet.java +/Users/jack.edelist/Desktop/group8/src/main/java/object_detection/types/CameraPose.java +/Users/jack.edelist/Desktop/group8/src/main/java/object_detection/types/Point2D.java +/Users/jack.edelist/Desktop/group8/src/main/java/object_detection/types/BoundingBox2D.java +/Users/jack.edelist/Desktop/group8/src/main/java/top/BackendJava.java +/Users/jack.edelist/Desktop/group8/src/main/java/vid2frames/Vid2Frames.java +/Users/jack.edelist/Desktop/group8/src/main/java/object_detection/types/CameraIntrinsics.java +/Users/jack.edelist/Desktop/group8/src/main/java/object_detection/types/PointSet.java +/Users/jack.edelist/Desktop/group8/src/main/java/database/MongoDBInteraction.java +/Users/jack.edelist/Desktop/group8/src/main/java/object_detection/ObjectDetector.java +/Users/jack.edelist/Desktop/group8/src/main/java/object_detection/types/BoundingBox3D.java +/Users/jack.edelist/Desktop/group8/src/main/java/object_detection/types/Frame.java +/Users/jack.edelist/Desktop/group8/src/main/java/object_detection/types/Point.java +/Users/jack.edelist/Desktop/group8/src/main/java/yolo/YOLODetector.java +/Users/jack.edelist/Desktop/group8/src/main/java/yolo/YOLONet.java +/Users/jack.edelist/Desktop/group8/src/main/java/object_detection/Downsampler.java diff --git a/target/maven-status/maven-compiler-plugin/testCompile/default-testCompile/createdFiles.lst b/target/maven-status/maven-compiler-plugin/testCompile/default-testCompile/createdFiles.lst new file mode 100644 index 0000000000000000000000000000000000000000..9ed0cd1af0980717fffc73a9f4157439ffba674d --- /dev/null +++ b/target/maven-status/maven-compiler-plugin/testCompile/default-testCompile/createdFiles.lst @@ -0,0 +1,2 @@ +yolo/YOLONet$ObjectDetectionResult.class +yolo/YOLONet.class diff --git a/target/maven-status/maven-compiler-plugin/testCompile/default-testCompile/inputFiles.lst b/target/maven-status/maven-compiler-plugin/testCompile/default-testCompile/inputFiles.lst new file mode 100644 index 0000000000000000000000000000000000000000..eeea1718facfff2846db25447deac20997b40825 --- /dev/null +++ b/target/maven-status/maven-compiler-plugin/testCompile/default-testCompile/inputFiles.lst @@ -0,0 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b/target/surefire-reports/TEST-object_detection.BoundingBox2DTests.xml new file mode 100644 index 0000000000000000000000000000000000000000..f5378d5425571c58b99079ff14dce1c5523690c0 --- /dev/null +++ b/target/surefire-reports/TEST-object_detection.BoundingBox2DTests.xml @@ -0,0 +1,65 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/target/surefire-reports/TEST-object_detection.BoundingBox3DTests.xml b/target/surefire-reports/TEST-object_detection.BoundingBox3DTests.xml new file mode 100644 index 0000000000000000000000000000000000000000..6d43e092deb0e41d7f644b31f27b5ee7077efa69 --- /dev/null +++ b/target/surefire-reports/TEST-object_detection.BoundingBox3DTests.xml @@ -0,0 +1,62 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/target/surefire-reports/TEST-object_detection.CameraIntrinsicsTests.xml b/target/surefire-reports/TEST-object_detection.CameraIntrinsicsTests.xml new file mode 100644 index 0000000000000000000000000000000000000000..91120a65e388d949fe5ba1b1e8eab1411fbf702f --- /dev/null +++ b/target/surefire-reports/TEST-object_detection.CameraIntrinsicsTests.xml @@ -0,0 +1,62 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/target/surefire-reports/TEST-object_detection.CameraPoseTests.xml b/target/surefire-reports/TEST-object_detection.CameraPoseTests.xml new file mode 100644 index 0000000000000000000000000000000000000000..b7f6e1fb0570c79f9646d16a0eebaaa9caf6d999 --- /dev/null +++ b/target/surefire-reports/TEST-object_detection.CameraPoseTests.xml @@ -0,0 +1,62 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/target/surefire-reports/TEST-object_detection.ObjectSetTests.xml b/target/surefire-reports/TEST-object_detection.ObjectSetTests.xml new file mode 100644 index 0000000000000000000000000000000000000000..99b94a7e2e689b40c79b68d1a067091b85b7f145 --- /dev/null +++ b/target/surefire-reports/TEST-object_detection.ObjectSetTests.xml @@ -0,0 +1,64 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/target/surefire-reports/TEST-object_detection.Point2DTests.xml b/target/surefire-reports/TEST-object_detection.Point2DTests.xml new file mode 100644 index 0000000000000000000000000000000000000000..44d623d1e005d1016e72b07f6f2b63ba9d808e0e --- /dev/null +++ b/target/surefire-reports/TEST-object_detection.Point2DTests.xml @@ -0,0 +1,64 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/target/surefire-reports/TEST-object_detection.PointSetTests.xml b/target/surefire-reports/TEST-object_detection.PointSetTests.xml new file mode 100644 index 0000000000000000000000000000000000000000..3d3c3f207ee197a5848318204c1ac8b189dcf00f --- /dev/null +++ b/target/surefire-reports/TEST-object_detection.PointSetTests.xml @@ -0,0 +1,64 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/target/surefire-reports/TEST-object_detection.PointTests.xml b/target/surefire-reports/TEST-object_detection.PointTests.xml new file mode 100644 index 0000000000000000000000000000000000000000..8aa3231dfa3a4566206008f958471afb21e69eb8 --- /dev/null +++ b/target/surefire-reports/TEST-object_detection.PointTests.xml @@ -0,0 +1,70 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/target/surefire-reports/object_detection.BoundingBox2DTests.txt b/target/surefire-reports/object_detection.BoundingBox2DTests.txt new file mode 100644 index 0000000000000000000000000000000000000000..f001e8df274646fe8fdf5f134e8d08b8a2645fc2 --- /dev/null +++ b/target/surefire-reports/object_detection.BoundingBox2DTests.txt @@ -0,0 +1,4 @@ +------------------------------------------------------------------------------- +Test set: object_detection.BoundingBox2DTests +------------------------------------------------------------------------------- +Tests run: 4, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 0.004 s -- in object_detection.BoundingBox2DTests diff --git a/target/surefire-reports/object_detection.BoundingBox3DTests.txt b/target/surefire-reports/object_detection.BoundingBox3DTests.txt new file mode 100644 index 0000000000000000000000000000000000000000..d8e3531225fcfc385d3781e5167a7a5c1c21fe68 --- /dev/null +++ b/target/surefire-reports/object_detection.BoundingBox3DTests.txt @@ -0,0 +1,4 @@ +------------------------------------------------------------------------------- +Test set: object_detection.BoundingBox3DTests +------------------------------------------------------------------------------- +Tests run: 1, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 0.006 s -- in object_detection.BoundingBox3DTests diff --git a/target/surefire-reports/object_detection.CameraIntrinsicsTests.txt b/target/surefire-reports/object_detection.CameraIntrinsicsTests.txt new file mode 100644 index 0000000000000000000000000000000000000000..83544e4bfc1fc1757f0a701c39e7204fbb9b9281 --- /dev/null +++ b/target/surefire-reports/object_detection.CameraIntrinsicsTests.txt @@ -0,0 +1,4 @@ +------------------------------------------------------------------------------- +Test set: object_detection.CameraIntrinsicsTests +------------------------------------------------------------------------------- +Tests run: 1, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 0.045 s -- in object_detection.CameraIntrinsicsTests diff --git a/target/surefire-reports/object_detection.CameraPoseTests.txt b/target/surefire-reports/object_detection.CameraPoseTests.txt new file mode 100644 index 0000000000000000000000000000000000000000..cf38e2e144ecbe611037f6c7928fe4cfb5ce7f37 --- /dev/null +++ b/target/surefire-reports/object_detection.CameraPoseTests.txt @@ -0,0 +1,4 @@ +------------------------------------------------------------------------------- +Test set: object_detection.CameraPoseTests +------------------------------------------------------------------------------- +Tests run: 1, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 0.002 s -- in object_detection.CameraPoseTests diff --git a/target/surefire-reports/object_detection.ObjectSetTests.txt b/target/surefire-reports/object_detection.ObjectSetTests.txt new 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+------------------------------------------------------------------------------- +Tests run: 3, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 0.011 s -- in object_detection.Point2DTests diff --git a/target/surefire-reports/object_detection.PointSetTests.txt b/target/surefire-reports/object_detection.PointSetTests.txt new file mode 100644 index 0000000000000000000000000000000000000000..e09b8f5bd7234d2bdd317961e93973926275523a --- /dev/null +++ b/target/surefire-reports/object_detection.PointSetTests.txt @@ -0,0 +1,4 @@ +------------------------------------------------------------------------------- +Test set: object_detection.PointSetTests +------------------------------------------------------------------------------- +Tests run: 3, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 0.002 s -- in object_detection.PointSetTests diff --git a/target/surefire-reports/object_detection.PointTests.txt b/target/surefire-reports/object_detection.PointTests.txt new file mode 100644 index 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b/target/test-classes/yolo/YOLONet$ObjectDetectionResult.class differ diff --git a/target/test-classes/yolo/YOLONet.class b/target/test-classes/yolo/YOLONet.class new file mode 100644 index 0000000000000000000000000000000000000000..76a79f194834c09260c0acc27004d5a953c7a52b Binary files /dev/null and b/target/test-classes/yolo/YOLONet.class differ diff --git a/target/test-classes/yolo/YOLOTest.class b/target/test-classes/yolo/YOLOTest.class new file mode 100644 index 0000000000000000000000000000000000000000..b56a80dd6c76f3dc926ec3a294e6fce2ad14070d Binary files /dev/null and b/target/test-classes/yolo/YOLOTest.class differ diff --git a/target/test-classes/yolo/coco.names b/target/test-classes/yolo/coco.names new file mode 100644 index 0000000000000000000000000000000000000000..16315f2becec9705017bfaf1b9fb81ca2a83c0b0 --- /dev/null +++ b/target/test-classes/yolo/coco.names @@ -0,0 +1,80 @@ +person +bicycle +car +motorbike +aeroplane +bus +train +truck +boat +traffic light +fire hydrant 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