vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e

modules/surface_matching/samples/ppf_load_match.py

@@ -0,0 +1,32 @@
+import cv2 as cv
+
+N = 2
+modelname = "parasaurolophus_6700"
+scenename = "rs1_normals"
+
+detector = cv.ppf_match_3d_PPF3DDetector(0.025, 0.05)
+
+print('Loading model...')
+pc = cv.ppf_match_3d.loadPLYSimple("data/%s.ply" % modelname, 1)
+
+
+print('Training...')
+detector.trainModel(pc)
+
+print('Loading scene...')
+pcTest = cv.ppf_match_3d.loadPLYSimple("data/%s.ply" % scenename, 1)
+
+print('Matching...')
+results = detector.match(pcTest, 1.0/40.0, 0.05)
+
+print('Performing ICP...')
+icp = cv.ppf_match_3d_ICP(100)
+_, results = icp.registerModelToScene(pc, pcTest, results[:N])
+
+print("Poses: ")
+for i, result in enumerate(results):
+    #result.printPose()
+    print("\n-- Pose to Model Index %d: NumVotes = %d, Residual = %f\n%s\n" % (result.modelIndex, result.numVotes, result.residual, result.pose))
+    if i == 0:
+        pct = cv.ppf_match_3d.transformPCPose(pc, result.pose)
+        cv.ppf_match_3d.writePLY(pct, "%sPCTrans.ply" % modelname)