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
def deserialize(self, InJSONFile):
with open(InJSONFile) as f:
data = json.load(f)
# Loading convention: Flip sign of x position, 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 # Hack to offset to NOCS center
Quat = np.array([Quat[0], Quat[1], -Quat[2], -Quat[3]])
self.Translation = P
R = quaternions.quat2mat(Quat).T
self.Rotation = R