예제 #1
0
    def gentubes(self, homomat, elearray=None, type="dumbbell"):
        """

        :param elearray:
        :param tubestand_homomat:
        :param eleconfidencearray: None by default
        :param alpha: only works when eleconfidencearray is None, it renders the array transparently
        :return:

        author: weiwei
        date: 20191229osaka
        """

        if elearray is None:
            elearray = self.pattern
        tubecmlist = []
        for i in range(elearray.shape[0]):
            for j in range(elearray.shape[1]):
                if elearray[i,j] == 1:
                    if type is "dumbbell":
                        tubecm = cm.CollisionModel(p3dh.gendumbbell(spos=np.array([0,0,0]), epos = np.array([0, 0, 100])))
                        tubecm.setColor(.5,0,0,1)
                    elif type is "cad":
                        tubecm = self.tubebigcm
                elif elearray[i,j] == 2:
                    if type is "dumbbell":
                        tubecm = cm.CollisionModel(p3dh.gendumbbell(spos=np.array([0,0,0]), epos = np.array([0, 0, 80])))
                        tubecm.setColor(0,.5,0,1)
                    elif type is "cad":
                        tubecm = self.tubesmall1cm
                elif elearray[i,j] == 3:
                    if type is "dumbbell":
                        tubecm = cm.CollisionModel(p3dh.gendumbbell(spos=np.array([0,0,0]), epos = np.array([0, 0, 70])))
                        tubecm.setColor(0,0,.5,1)
                    elif type is "cad":
                        tubecm = self.tubesmall2cm
                elif elearray[i,j] == -1:
                    tubecm = cm.CollisionModel(p3dh.gendumbbell(spos=np.array([0,0,0]), epos = np.array([0, 0, 70])))
                    tubecm.setColor(1,1,1,1)
                elif elearray[i,j] == -2:
                    tubecm = cm.CollisionModel(p3dh.gendumbbell(spos=np.array([0,0,0]), epos = np.array([0, 0, 70])))
                    tubecm.setColor(0,0,0,1)
                else:
                    continue
                newtubecm = copy.deepcopy(tubecm)
                tubemat = copy.deepcopy(homomat)
                tubepos_normalized = np.array([self.tubeholecenters[i,j][0], self.tubeholecenters[i,j][1], 5])
                tubepos  = rm.homotransformpoint(homomat, tubepos_normalized)
                tubemat[:3, 3] = tubepos
                newtubecm.set_homomat(tubemat)
                tubecmlist.append(newtubecm)

        return tubecmlist
예제 #2
0
    def gentubes(self,
                 elearray,
                 tubestand_homomat,
                 eleconfidencearray=None,
                 alpha=.3):
        """

        :param elearray:
        :param tubestand_homomat:
        :param eleconfidencearray: None by default
        :param alpha: only works when eleconfidencearray is None, it renders the array transparently
        :return:

        author: weiwei
        date: 20191229osaka
        """

        if eleconfidencearray is None:
            eleconfidencearray = np.ones_like(elearray) * alpha

        tubecmlist = []
        for i in range(5):
            for j in range(10):
                if elearray[i, j] == 1:
                    tubecm = self.tubebigcm
                    rgba = np.array([.7, .7, 0, eleconfidencearray[i, j]])
                elif elearray[i, j] == 2:
                    tubecm = self.tubesmallcm
                    rgba = np.array([.7, 0, .7, eleconfidencearray[i, j]])
                else:
                    continue
                newtubecm = copy.deepcopy(tubecm)
                tubemat = copy.deepcopy(tubestand_homomat)
                tubepos_normalized = np.array([
                    self.tubeholecenters[i, j][0],
                    self.tubeholecenters[i, j][1], 5
                ])
                tubepos = rm.homotransformpoint(tubestand_homomat,
                                                tubepos_normalized)
                tubemat[:3, 3] = tubepos
                newtubecm.set_homomat(tubemat)
                newtubecm.setColor(rgba[0], rgba[1], rgba[2], rgba[3])
                tubecmlist.append(newtubecm)

        return tubecmlist
예제 #3
0
    def findtubes(self, tubestand_homomat, tgtpcdnp, toggledebug=False):
        """

        :param tgtpcdnp:
        :return:

        author: weiwei
        date: 20200317
        """

        elearray = np.zeros((5, 10))
        eleconfidencearray = np.zeros((5, 10))

        tgtpcdnp = o3dh.remove_outlier(tgtpcdnp,
                                       downsampling_voxelsize=None,
                                       nb_points=90,
                                       radius=5)
        # transform back to the local frame of the tubestand
        tgtpcdnp_normalized = rm.homotransformpointarray(
            rm.homoinverse(tubestand_homomat), tgtpcdnp)
        if toggledebug:
            cm.CollisionModel(tgtpcdnp_normalized).reparentTo(base.render)
            tscm2 = copy.deepcopy(self.tubestandcm)
            tscm2.reparentTo(base.render)
        for i in range(5):
            for j in range(10):
                holepos = self.tubeholecenters[i][j]
                tmppcd = self._crop_pcd_overahole(tgtpcdnp_normalized,
                                                  holepos[0], holepos[1])
                if len(tmppcd) > 50:
                    if toggledebug:
                        print(
                            "------more than 50 raw points, start a new test------"
                        )
                    tmppcdover100 = tmppcd[tmppcd[:, 2] > 100]
                    tmppcdbelow90 = tmppcd[tmppcd[:, 2] < 90]
                    tmppcdlist = [tmppcdover100, tmppcdbelow90]
                    if toggledebug:
                        print("rotate around...")
                    rejflaglist = [False, False]
                    allminstdlist = [[], []]
                    newtmppcdlist = [None, None]
                    minstdlist = [None, None]
                    for k in range(2):
                        if toggledebug:
                            print("checking over 100 and below 90, now: ", j)
                        if len(tmppcdlist[k]) < 10:
                            rejflaglist[k] = True
                            continue
                        for angle in np.linspace(0, 180, 10):
                            tmphomomat = np.eye(4)
                            tmphomomat[:3, :3] = rm.rodrigues(
                                tubestand_homomat[:3, 2], angle)
                            newtmppcdlist[k] = rm.homotransformpointarray(
                                tmphomomat, tmppcdlist[k])
                            minstdlist[k] = np.min(
                                np.std(newtmppcdlist[k][:, :2], axis=0))
                            if toggledebug:
                                print(minstdlist[k])
                            allminstdlist[k].append(minstdlist[k])
                            if minstdlist[k] < 1.5:
                                rejflaglist[k] = True
                        if toggledebug:
                            print("rotate round done")
                            print("minstd ",
                                  np.min(np.asarray(allminstdlist[k])))
                    if all(item for item in rejflaglist):
                        continue
                    elif all(not item for item in rejflaglist):
                        print("CANNOT tell if the tube is big or small")
                        raise ValueError()
                    else:
                        tmppcd = tmppcdbelow90 if rejflaglist[
                            0] else tmppcdover100
                        candidatetype = 2 if rejflaglist[0] else 1
                        tmpangles = np.arctan2(tmppcd[:, 1], tmppcd[:, 0])
                        tmpangles[
                            tmpangles < 0] = 360 + tmpangles[tmpangles < 0]
                        if toggledebug:
                            print(np.std(tmpangles))
                            print("ACCEPTED! ID: ", i, j)
                        elearray[i][j] = candidatetype
                        eleconfidencearray[i][j] = 1
                        if toggledebug:
                            # normalized
                            objnp = p3dh.genpointcloudnodepath(tmppcd,
                                                               pntsize=5)
                            rgb = np.random.rand(3)
                            objnp.setColor(rgb[0], rgb[1], rgb[2], 1)
                            objnp.reparentTo(base.render)
                            stick = p3dh.gendumbbell(
                                spos=np.array([holepos[0], holepos[1], 10]),
                                epos=np.array([holepos[0], holepos[1], 60]))
                            stick.setColor(rgb[0], rgb[1], rgb[2], 1)
                            stick.reparentTo(base.render)
                            # original
                            tmppcd_tr = rm.homotransformpointarray(
                                tubestand_homomat, tmppcd)
                            objnp_tr = p3dh.genpointcloudnodepath(tmppcd_tr,
                                                                  pntsize=5)
                            objnp_tr.setColor(rgb[0], rgb[1], rgb[2], 1)
                            objnp_tr.reparentTo(base.render)
                            spos_tr = rm.homotransformpoint(
                                tubestand_homomat,
                                np.array([holepos[0], holepos[1], 0]))
                            stick_tr = p3dh.gendumbbell(
                                spos=np.array([spos_tr[0], spos_tr[1], 10]),
                                epos=np.array([spos_tr[0], spos_tr[1], 60]))
                            stick_tr.setColor(rgb[0], rgb[1], rgb[2], 1)
                            stick_tr.reparentTo(base.render)
                            # box normalized
                            center, bounds = rm.get_aabb(tmppcd)
                            boxextent = np.array([
                                bounds[0, 1] - bounds[0, 0],
                                bounds[1, 1] - bounds[1, 0],
                                bounds[2, 1] - bounds[2, 0]
                            ])
                            boxhomomat = np.eye(4)
                            boxhomomat[:3, 3] = center
                            box = p3dh.genbox(
                                extent=boxextent,
                                homomat=boxhomomat,
                                rgba=np.array([rgb[0], rgb[1], rgb[2], .3]))
                            box.reparentTo(base.render)
                            # box original
                            center_r = rm.homotransformpoint(
                                tubestand_homomat, center)
                            boxhomomat_tr = copy.deepcopy(tubestand_homomat)
                            boxhomomat_tr[:3, 3] = center_r
                            box_tr = p3dh.genbox(
                                extent=boxextent,
                                homomat=boxhomomat_tr,
                                rgba=np.array([rgb[0], rgb[1], rgb[2], .3]))
                            box_tr.reparentTo(base.render)
                    if toggledebug:
                        print("------the new test is done------")
        return elearray, eleconfidencearray
예제 #4
0
파일: locator.py 프로젝트: wanweiwei07/wrs
    def findtubes(self, tubestand_homomat, tgtpcdnp, toggledebug=False):
        """

        :param tubestand_homomat:
        :param tgtpcdnp:
        :return:
        """

        elearray = np.zeros((5, 10))
        eleconfidencearray = np.zeros((5, 10))

        tgtpcdo3d = o3dh.nparray_to_o3dpcd(tgtpcdnp)
        tgtpcdo3d_removed = o3dh.remove_outlier(tgtpcdo3d,
                                                downsampling_voxelsize=None,
                                                nb_points=90,
                                                radius=5)
        tgtpcdnp = o3dh.o3dpcd_to_parray(tgtpcdo3d_removed)
        # transform tgtpcdnp back
        tgtpcdnp_normalized = rm.homotransformpointarray(
            rm.homoinverse(tubestand_homomat), tgtpcdnp)
        if toggledebug:
            cm.CollisionModel(tgtpcdnp_normalized).reparentTo(base.render)
            tscm2 = cm.CollisionModel("../objects/tubestand.stl")
            tscm2.reparentTo(base.render)
        for i in range(5):
            for j in range(10):
                holepos = self.tubeholecenters[i][j]
                # squeeze the hole size by half
                tmppcd = tgtpcdnp_normalized[
                    tgtpcdnp_normalized[:, 0] < holepos[0] +
                    self.tubeholesize[0] / 1.9]
                tmppcd = tmppcd[tmppcd[:, 0] > holepos[0] -
                                self.tubeholesize[0] / 1.9]
                tmppcd = tmppcd[tmppcd[:, 1] < holepos[1] +
                                self.tubeholesize[1] / 1.9]
                tmppcd = tmppcd[tmppcd[:, 1] > holepos[1] -
                                self.tubeholesize[1] / 1.9]
                tmppcd = tmppcd[tmppcd[:, 2] > 70]
                if len(tmppcd) > 100:
                    print(
                        "------more than 100 raw points, start a new test------"
                    )
                    # use core tmppcd to decide tube types (avoid noises)
                    coretmppcd = tmppcd[tmppcd[:, 0] < holepos[0] +
                                        self.tubeholesize[0] / 4]
                    coretmppcd = coretmppcd[coretmppcd[:, 0] > holepos[0] -
                                            self.tubeholesize[0] / 4]
                    coretmppcd = coretmppcd[coretmppcd[:, 1] < holepos[1] +
                                            self.tubeholesize[1] / 4]
                    coretmppcd = coretmppcd[coretmppcd[:, 1] > holepos[1] -
                                            self.tubeholesize[1] / 4]
                    print("testing the number of core points...")
                    print(len(coretmppcd[:, 2]))
                    if len(coretmppcd[:, 2]) < 10:
                        print("------the new test is done------")
                        continue
                    if np.max(tmppcd[:, 2]) > 100:
                        candidatetype = 1
                        tmppcd = tmppcd[tmppcd[:, 2] >
                                        100]  # crop tmppcd for better charge
                    else:
                        candidatetype = 2
                        tmppcd = tmppcd[tmppcd[:, 2] < 90]
                    if len(tmppcd) < 10:
                        continue
                    print("passed the core points test, rotate around...")
                    rejflag = False
                    for angle in np.linspace(0, 180, 20):
                        tmphomomat = np.eye(4)
                        tmphomomat[:3, :3] = rm.rodrigues(
                            tubestand_homomat[:3, 2], angle)
                        newtmppcd = rm.homotransformpointarray(
                            tmphomomat, tmppcd)
                        minstd = np.min(np.std(newtmppcd[:, :2], axis=0))
                        print(minstd)
                        if minstd < 1.3:
                            rejflag = True
                    print("rotate round done")
                    if rejflag:
                        continue
                    else:
                        tmpangles = np.arctan2(tmppcd[:, 1], tmppcd[:, 0])
                        tmpangles[
                            tmpangles < 0] = 360 + tmpangles[tmpangles < 0]
                        print(np.std(tmpangles))
                        print("ACCEPTED! ID: ", i, j)
                        elearray[i][j] = candidatetype
                        eleconfidencearray[i][j] = 1
                    if toggledebug:
                        # normalized
                        objnp = p3dh.genpointcloudnodepath(tmppcd, pntsize=5)
                        rgb = np.random.rand(3)
                        objnp.setColor(rgb[0], rgb[1], rgb[2], 1)
                        objnp.reparentTo(base.render)
                        stick = p3dh.gendumbbell(
                            spos=np.array([holepos[0], holepos[1], 10]),
                            epos=np.array([holepos[0], holepos[1], 60]))
                        stick.setColor(rgb[0], rgb[1], rgb[2], 1)
                        stick.reparentTo(base.render)
                        # original
                        tmppcd_tr = rm.homotransformpointarray(
                            tubestand_homomat, tmppcd)
                        objnp_tr = p3dh.genpointcloudnodepath(tmppcd_tr,
                                                              pntsize=5)
                        objnp_tr.setColor(rgb[0], rgb[1], rgb[2], 1)
                        objnp_tr.reparentTo(base.render)
                        spos_tr = rm.homotransformpoint(
                            tubestand_homomat,
                            np.array([holepos[0], holepos[1], 0]))
                        stick_tr = p3dh.gendumbbell(
                            spos=np.array([spos_tr[0], spos_tr[1], 10]),
                            epos=np.array([spos_tr[0], spos_tr[1], 60]))
                        stick_tr.setColor(rgb[0], rgb[1], rgb[2], 1)
                        stick_tr.reparentTo(base.render)
                        # box normalized
                        center, bounds = rm.get_aabb(tmppcd)
                        boxextent = np.array([
                            bounds[0, 1] - bounds[0, 0],
                            bounds[1, 1] - bounds[1, 0],
                            bounds[2, 1] - bounds[2, 0]
                        ])
                        boxhomomat = np.eye(4)
                        boxhomomat[:3, 3] = center
                        box = p3dh.genbox(extent=boxextent,
                                          homomat=boxhomomat,
                                          rgba=np.array(
                                              [rgb[0], rgb[1], rgb[2], .3]))
                        box.reparentTo(base.render)
                        # box original
                        center_r = rm.homotransformpoint(
                            tubestand_homomat, center)
                        boxhomomat_tr = copy.deepcopy(tubestand_homomat)
                        boxhomomat_tr[:3, 3] = center_r
                        box_tr = p3dh.genbox(extent=boxextent,
                                             homomat=boxhomomat_tr,
                                             rgba=np.array(
                                                 [rgb[0], rgb[1], rgb[2], .3]))
                        box_tr.reparentTo(base.render)
                    print("------the new test is done------")
        return elearray, eleconfidencearray