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- 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)
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