def _runImp(self):
image = self._scene.image()
D_32F = self._scene.depth()
if D_32F is None:
return
N_32F = depthToNormal(D_32F)
self._scene.setNormal(N_32F)
def _runImp(self):
image = self._scene.image()
D_32F = self._scene.depth()
if D_32F is None:
return
N_32F = depthToNormal(D_32F)
self._scene.setNormal(N_32F)
def _runImp(self):
# file_path = self._data_file
file_path = self.resultFile(self._data_file_name, result_name="Wu08")
normal_data = loadNormal(file_path)
if normal_data is None:
return
N0_32F, A_8U = normal_data
D_32F = depthFromNormal(N0_32F, A_8U)
fig, axes = plt.subplots(figsize=(11, 5))
font_size = 15
fig.subplots_adjust(left=0.05,
right=0.95,
top=0.9,
hspace=0.05,
wspace=0.05)
fig.suptitle("Depth From Normal", fontsize=font_size)
plt.subplot(1, 4, 1)
plt.title(r'Initial Normal: $N_0$')
plt.imshow(normalToColor(N0_32F, A_8U))
plt.axis('off')
plt.subplot(1, 4, 2)
plt.title(r'Estimated Depth: $D$')
plt.gray()
plt.imshow(D_32F)
plt.axis('off')
N_32F = depthToNormal(D_32F)
plt.subplot(1, 4, 3)
plt.title(r'Recovered Normal: $N$')
plt.imshow(normalToColor(N_32F, A_8U))
plt.axis('off')
h, w = N_32F.shape[:2]
N_diff = angleErros(N_32F.reshape(-1, 3),
N0_32F.reshape(-1, 3)).reshape(h, w)
N_diff[A_8U < np.max(A_8U)] = 0.0
plt.subplot(1, 4, 4)
plt.title(r'Angle Error: $N, N_0$')
plt.imshow(N_diff, cmap=plt.cm.jet, vmin=0, vmax=30.0)
plt.axis('off')
plt.colorbar()
#out_file_path = self.resultFile(self._data_file_name)
out_file_path = self.resultFile(self._data_file_name,
result_name="Wu08Depth")
plt.savefig(out_file_path)
def _runImp(self):
# file_path = self._data_file
file_path = self.resultFile(self._data_file_name, result_name="Wu08")
normal_data = loadNormal(file_path)
if normal_data is None:
return
N0_32F, A_8U = normal_data
D_32F = depthFromNormal(N0_32F, A_8U)
fig, axes = plt.subplots(figsize=(11, 5))
font_size = 15
fig.subplots_adjust(left=0.05, right=0.95, top=0.9, hspace=0.05, wspace=0.05)
fig.suptitle("Depth From Normal", fontsize=font_size)
plt.subplot(1, 4, 1)
plt.title(r'Initial Normal: $N_0$')
plt.imshow(normalToColor(N0_32F, A_8U))
plt.axis('off')
plt.subplot(1, 4, 2)
plt.title(r'Estimated Depth: $D$')
plt.gray()
plt.imshow(D_32F)
plt.axis('off')
N_32F = depthToNormal(D_32F)
plt.subplot(1, 4, 3)
plt.title(r'Recovered Normal: $N$')
plt.imshow(normalToColor(N_32F, A_8U))
plt.axis('off')
h, w = N_32F.shape[:2]
N_diff = angleErros(N_32F.reshape(-1, 3), N0_32F.reshape(-1, 3)).reshape(h, w)
N_diff[A_8U < np.max(A_8U)] = 0.0
plt.subplot(1, 4, 4)
plt.title(r'Angle Error: $N, N_0$')
plt.imshow(N_diff, cmap=plt.cm.jet, vmin=0, vmax=30.0)
plt.axis('off')
plt.colorbar()
#out_file_path = self.resultFile(self._data_file_name)
out_file_path = self.resultFile(self._data_file_name, result_name="Wu08Depth")
plt.savefig(out_file_path)
def _runImp(self):
normal_data = loadNormal(self._data_file)
if normal_data is None:
return
N0_32F, A_8U = normal_data
A_32F = to32F(A_8U)
L = normalizeVector(np.array([-0.2, 0.3, 0.7]))
#C0_32F = ToonShader().diffuseShading(L, N0_32F)
C0_32F = LambertShader().diffuseShading(L, N0_32F)
I0_32F = luminance(C0_32F)
I0_low_32F = cv2.resize(I0_32F, (256, 256))
A_low_8U = cv2.resize(A_8U, I0_low_32F.shape)
D_32F = depthFromGradient(I0_low_32F, A_low_8U)
D_32F = cv2.resize(D_32F, I0_32F.shape)
N_32F = depthToNormal(D_32F)
self._view.setRGBAD(setAlpha(C0_32F, A_32F), D_32F)
def _runImp(self):
normal_data = loadNormal(self._data_file)
if normal_data is None:
return
N0_32F, A_8U = normal_data
A_32F = to32F(A_8U)
L = normalizeVector(np.array([-0.2, 0.3, 0.7]))
#C0_32F = ToonShader().diffuseShading(L, N0_32F)
C0_32F = LambertShader().diffuseShading(L, N0_32F)
I0_32F = luminance(C0_32F)
I0_low_32F = cv2.resize(I0_32F, (256, 256))
A_low_8U = cv2.resize(A_8U, I0_low_32F.shape)
D_32F = depthFromGradient(I0_low_32F, A_low_8U)
D_32F = cv2.resize(D_32F, I0_32F.shape)
N_32F = depthToNormal(D_32F)
self._view.setRGBAD(setAlpha(C0_32F, A_32F), D_32F)
