def init(self, InputArgs=None):
self.Parser = argparse.ArgumentParser(description='NOCSMapModule to visualize NOCS maps and camera poses.', fromfile_prefix_chars='@')
ArgGroup = self.Parser.add_argument_group()
ArgGroup.add_argument('--nocs-maps', nargs='+', help='Specify input NOCS maps. * globbing is supported.', required=True)
ArgGroup.add_argument('--colors', nargs='+', help='Specify RGB images corresponding to the input NOCS maps. * globbing is supported.', required=False)
ArgGroup.add_argument('--intrinsics', help='Specify the intrinsics file to estimate camera pose.', required=False, default=None)
ArgGroup.add_argument('--poses', nargs='+',
help='Specify the camera extrinsics corresponding to the input NOCS maps. * globbing is supported.',
required=False)
ArgGroup.add_argument('--models', nargs='+',
help='Specify OBJ models to load additionally. * globbing is supported.',
required=False)
ArgGroup.add_argument('--num-points', help='Specify the number of pixels to use for camera pose registration.', default=1000, type=int, required=False)
ArgGroup.add_argument('--error-viz', help='Specify error wrto Nth NOCS map. If multiple NOCS maps are provided. Will compute the L2 errors between the Nth NOCS map and the rest. Will render this instead of RGB or colors.', default=-1, type=int, required=False)
ArgGroup.add_argument('--est-pose', help='Choose to estimate pose.', action='store_true')
self.Parser.set_defaults(est_pose=False)
ArgGroup.add_argument('--pose-scale', help='Specify the (inverse) scale of the camera positions in the ground truth pose files.', default=1.0, type=float, required=False)
self.Args, _ = self.Parser.parse_known_args(InputArgs)
if len(sys.argv) <= 1:
self.Parser.print_help()
exit()
self.NOCSMaps = []
self.NOCS = []
self.Cameras = []
self.CamRots = []
self.CamPos = []
self.CamIntrinsics = []
self.CamFlip = [] # This is a hack
# Extrinsics, if provided
self.PosesRots = []
self.PosesPos = []
self.OBJModels = []
self.PointSize = 3
self.Intrinsics = None
if self.Args.intrinsics is not None:
self.Intrinsics = ds.CameraIntrinsics()
self.Intrinsics.init_with_file(self.Args.intrinsics)
self.ImageSize = (self.Intrinsics.Width, self.Intrinsics.Height)
print('[ INFO ]: Intrinsics provided. Will re-size all images to', self.ImageSize)
if self.Intrinsics is None:
self.ImageSize = None
print('[ INFO ]: No intrinsics provided. Will use NOCS map size.')
sys.stdout.flush()
self.nNM = 0
self.SSCtr = 0
self.takeSS = False
self.showNOCS = True
self.showBB = False
self.showPoints = False
self.showWireFrame = False
self.isVizError = False
self.showOBJModels = True
self.loadData()
self.generateDiffMap()
def loadData(self):
Palette = ColorBlind_10
NMFiles = self.getFileNames(self.Args.nocs_maps)
ColorFiles = [None] * len(NMFiles)
PoseFiles = [None] * len(NMFiles)
if self.Args.colors is not None:
ColorFiles = self.getFileNames(self.Args.colors)
if self.Args.poses is not None:
PoseFiles = self.getFileNames(self.Args.poses)
for (NMF, Color, CF, PF) in zip(NMFiles, Palette.colors, ColorFiles, PoseFiles):
NOCSMap = cv2.imread(NMF, -1)
NOCSMap = NOCSMap[:, :, :3] # Ignore alpha if present
NOCSMap = cv2.cvtColor(NOCSMap, cv2.COLOR_BGR2RGB) # IMPORTANT: OpenCV loads as BGR, so convert to RGB
if self.Intrinsics is None:
self.ImageSize = (NOCSMap.shape[1], NOCSMap.shape[0])
else:
NOCSMap = self.resizeAndPad(NOCSMap)
CFIm = None
if CF is not None:
CFIm = cv2.imread(CF)
CFIm = cv2.cvtColor(CFIm, cv2.COLOR_BGR2RGB) # IMPORTANT: OpenCV loads as BGR, so convert to RGB
if CFIm.shape != NOCSMap.shape: # Re-size only if not the same size as NOCSMap
CFIm = cv2.resize(CFIm, (NOCSMap.shape[1], NOCSMap.shape[0]), interpolation=cv2.INTER_CUBIC) # Ok to use cubic interpolation for RGB
NOCS = ds.NOCSMap(NOCSMap, RGB=CFIm)
self.NOCSMaps.append(NOCSMap)
self.NOCS.append(NOCS)
if self.Args.no_pose == False:
_, K, R, C, Flip = self.estimateCameraPoseFromNM(NOCSMap, NOCS, N=self.Args.num_points, Intrinsics=self.Intrinsics) # The rotation and translation are about the NOCS origin
self.CamIntrinsics.append(K)
self.CamRots.append(R)
self.CamPos.append(C)
self.CamFlip.append(Flip)
self.Cameras.append(ds.Camera(ds.CameraExtrinsics(self.CamRots[-1], self.CamPos[-1]), ds.CameraIntrinsics(self.CamIntrinsics[-1])))
if PF is not None:
with open(PF) as f:
data = json.load(f)
# Loading convention: Flip sign of x postiion, flip signs of quaternion z, w
P = np.array([data['position']['x'], data['position']['y'], data['position']['z']])
Quat = np.array([data['rotation']['w'], data['rotation']['x'], data['rotation']['y'], data['rotation']['z']]) # NOTE: order is w, x, y, z
# Cajole transforms to work
P[0] *= -1
P += 0.5
Quat = np.array([Quat[0], Quat[1], -Quat[2], -Quat[3]])
self.PosesPos.append(P)
R = quaternions.quat2mat(Quat).T
self.PosesRots.append(R)
else:
self.PosesPos.append(None)
self.PosesRots.append(None)
self.nNM = len(NMFiles)
self.activeNMIdx = self.nNM # len(NMFiles) will show all