def _runImp(self):
normal_data = loadNormal(self._data_file)
if normal_data is None:
return
N0_32F, A_8U = normal_data
#N0_32F = cv2.resize(N0_32F, (64, 64))
#A_8U = cv2.resize(A_8U, N0_32F.shape[:2])
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)
sfs_method = Wu08SFS(L, C0_32F, A_8U)
sfs_method.run()
N_32F = sfs_method.normal()
saveNormal(self.resultFile(self._data_file_name, result_name="Wu08"), N_32F, A_8U)
C_error = sfs_method.shadingError()
I_32F = sfs_method.brightness()
I_32F = gray2rgb(I_32F)
C_32F = sfs_method.shading()
N0_32F = trim(N0_32F, A_8U)
C0_32F = trim(C0_32F, A_8U)
C_32F = trim(C_32F, A_8U)
N_32F = trim(N_32F, A_8U)
C_error = trim(C_error, A_8U)
I_32F = trim(I_32F, A_8U)
A_32F = trim(A_32F, A_8U)
A_8U = trim(A_8U, A_8U)
h, w = N_32F.shape[:2]
N_error = angleErros(N_32F.reshape(-1, 3), N0_32F.reshape(-1, 3)).reshape(h, w)
N_error[A_8U < np.max(A_8U)] = 0.0
fig, axes = plt.subplots(figsize=(11, 5))
font_size = 15
fig.subplots_adjust(left=0.05, right=0.95, top=0.9, hspace=0.12, wspace=0.05)
fig.suptitle(self.name(), fontsize=font_size)
num_rows = 2
num_cols = 3
plot_grid = SubplotGrid(num_rows, num_cols)
plot_grid.showImage(normalToColor(N0_32F, A_8U), r'Ground Truth Normal: $N_g$')
plot_grid.showImage(normalToColor(N_32F, A_8U), r'Estimated Normal: $N$')
plot_grid.showColorMap(N_error, r'Angle Error: $N_g, N$', v_min=0, v_max=30.0)
plot_grid.showImage(setAlpha(C0_32F, A_32F), r'Shading: $C$')
plot_grid.showImage(setAlpha(C_32F, A_32F), r'Estimated Shading: $C$')
plot_grid.showColorMap(C_error, r'Shading Error: $C_g, C$', v_min=0, v_max=0.1)
showMaximize()
def _runImp(self):
normal_data = loadNormal(self._data_file)
if normal_data is None:
return
N0_32F, A_8U = normal_data
# N0_32F = cv2.resize(N0_32F, (64, 64))
# A_8U = cv2.resize(A_8U, N0_32F.shape[:2])
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)
sfs_method = Wu08SFS(L, C0_32F, A_8U)
sfs_method.run()
N_32F = sfs_method.normal()
saveNormal(self.resultFile(self._data_file_name, result_name="Wu08"), N_32F, A_8U)
C_error = sfs_method.shadingError()
I_32F = sfs_method.brightness()
I_32F = gray2rgb(I_32F)
C_32F = sfs_method.shading()
N0_32F = trim(N0_32F, A_8U)
C0_32F = trim(C0_32F, A_8U)
C_32F = trim(C_32F, A_8U)
N_32F = trim(N_32F, A_8U)
C_error = trim(C_error, A_8U)
I_32F = trim(I_32F, A_8U)
A_32F = trim(A_32F, A_8U)
A_8U = trim(A_8U, A_8U)
h, w = N_32F.shape[:2]
N_error = angleErros(N_32F.reshape(-1, 3), N0_32F.reshape(-1, 3)).reshape(h, w)
N_error[A_8U < np.max(A_8U)] = 0.0
fig, axes = plt.subplots(figsize=(11, 5))
font_size = 15
fig.subplots_adjust(left=0.05, right=0.95, top=0.9, hspace=0.12, wspace=0.05)
fig.suptitle(self.name(), fontsize=font_size)
num_rows = 2
num_cols = 3
plot_grid = SubplotGrid(num_rows, num_cols)
plot_grid.showImage(normalToColor(N0_32F, A_8U), r"Ground Truth Normal: $N_g$")
plot_grid.showImage(normalToColor(N_32F, A_8U), r"Estimated Normal: $N$")
plot_grid.showColorMap(N_error, r"Angle Error: $N_g, N$", v_min=0, v_max=30.0)
plot_grid.showImage(setAlpha(C0_32F, A_32F), r"Shading: $C$")
plot_grid.showImage(setAlpha(C_32F, A_32F), r"Estimated Shading: $C$")
plot_grid.showColorMap(C_error, r"Shading Error: $C_g, C$", v_min=0, v_max=0.1)
showMaximize()
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 computeErrors(L, C0_32F, C_32F, Ng_32F, N_32F, A_8U):
h, w = A_8U.shape
N_error = angleErros(N_32F.reshape(-1, 3), Ng_32F.reshape(-1, 3)).reshape(h, w)
N_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
N_error = trim(N_error, A_8U)
C_error = normVectors(C0_32F.reshape(-1, 3) - C_32F.reshape(-1, 3)).reshape(h, w)
C_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
C_error = trim(C_error, A_8U)
I_32F = np.clip(LdotN(L, N_32F), 0.0, 1.0)
Ig_32F = np.clip(LdotN(L, Ng_32F), 0.0, 1.0)
I_error = np.abs(I_32F - Ig_32F)
I_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
I_error = trim(I_error, A_8U)
return C_error, N_error, I_error
def computeLambertShadingError():
shape_names = shapeNames()
L = normalizeVector(np.array([-0.2, 0.3, 0.6]))
C_errors = np.zeros(len(shape_names))
N_errors = np.zeros(len(shape_names))
for si, shape_name in enumerate(shape_names):
Ng_data = shapeFile(shape_name)
Ng_data = loadNormal(Ng_data)
Ng_32F, A_8U = Ng_data
N0_file = shapeResultFile(result_name="InitialNormal",
data_name=shape_name)
N0_data = loadNormal(N0_file)
N0_32F, A_8U = N0_data
C0_32F = LambertShader().diffuseShading(L, Ng_32F)
sfs_method = ToonSFS(L, C0_32F, A_8U)
sfs_method.setInitialNormal(N0_32F)
sfs_method.setNumIterations(iterations=60)
sfs_method.run()
N_32F = sfs_method.normal()
C_32F = sfs_method.shading()
C_error = sfs_method.shadingError()
C_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
C_errors[si] = np.average(C_error[A_8U > 0.5 * np.max(A_8U)])
h, w = A_8U.shape[:2]
N_error = angleErros(N_32F.reshape(-1, 3),
Ng_32F.reshape(-1, 3)).reshape(h, w)
N_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
N_errors[si] = np.average(N_error[A_8U > 0.5 * np.max(A_8U)])
file_path = shapeResultFile("ShapeEstimation",
"ShadingError",
file_ext=".npy")
np.save(file_path, C_errors)
file_path = shapeResultFile("ShapeEstimation",
"NormalError",
file_ext=".npy")
np.save(file_path, N_errors)
def computeErrors(L, C0_32F, C_32F, Ng_32F, N_32F, A_8U):
h, w = A_8U.shape
N_error = angleErros(N_32F.reshape(-1, 3),
Ng_32F.reshape(-1, 3)).reshape(h, w)
N_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
N_error = trim(N_error, A_8U)
C_error = normVectors(C0_32F.reshape(-1, 3) -
C_32F.reshape(-1, 3)).reshape(h, w)
C_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
C_error = trim(C_error, A_8U)
I_32F = np.clip(LdotN(L, N_32F), 0.0, 1.0)
Ig_32F = np.clip(LdotN(L, Ng_32F), 0.0, 1.0)
I_error = np.abs(I_32F - Ig_32F)
I_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
I_error = trim(I_error, A_8U)
return C_error, N_error, I_error
def computeLambertShadingError():
shape_names = shapeNames()
L = normalizeVector(np.array([-0.2, 0.3, 0.6]))
C_errors = np.zeros(len(shape_names))
N_errors = np.zeros(len(shape_names))
for si, shape_name in enumerate(shape_names):
Ng_data = shapeFile(shape_name)
Ng_data = loadNormal(Ng_data)
Ng_32F, A_8U = Ng_data
N0_file = shapeResultFile(result_name="InitialNormal", data_name=shape_name)
N0_data = loadNormal(N0_file)
N0_32F, A_8U = N0_data
C0_32F = LambertShader().diffuseShading(L, Ng_32F)
sfs_method = ToonSFS(L, C0_32F, A_8U)
sfs_method.setInitialNormal(N0_32F)
sfs_method.setNumIterations(iterations=60)
sfs_method.run()
N_32F = sfs_method.normal()
C_32F = sfs_method.shading()
C_error = sfs_method.shadingError()
C_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
C_errors[si] = np.average(C_error[A_8U > 0.5 * np.max(A_8U)])
h, w = A_8U.shape[:2]
N_error = angleErros(N_32F.reshape(-1, 3), Ng_32F.reshape(-1, 3)).reshape(h, w)
N_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
N_errors[si] = np.average(N_error[A_8U > 0.5 * np.max(A_8U)])
file_path = shapeResultFile("ShapeEstimation", "ShadingError", file_ext=".npy")
np.save(file_path, C_errors)
file_path = shapeResultFile("ShapeEstimation", "NormalError", file_ext=".npy")
np.save(file_path, N_errors)
def materialShapeVariationFigure():
target_colormaps = [23, 3, 12]
#target_colormaps = [3, 17]
colormap_files = [colorMapFile(cmap_id) for cmap_id in target_colormaps]
target_shapes = ["Blob1", "ThreeBox"]
shape_names = target_shapes
#shape_names = shapeNames()[4:5]
num_shapes = len(shape_names)
num_colormaps = len(colormap_files)
num_rows = num_colormaps
num_cols = 6
w = 20
h = w * num_rows / num_cols
fig, axes = plt.subplots(figsize=(w, h))
font_size = 15
fig.subplots_adjust(left=0.02,
right=0.98,
top=0.96,
bottom=0.02,
hspace=0.15,
wspace=0.1)
fig.suptitle("", fontsize=font_size)
plot_grid = SubplotGrid(num_rows, num_cols)
L = normalizeVector(np.array([-0.4, 0.5, 0.6]))
shape_name = "Blob1"
Ng_data = shapeFile(shape_name)
Ng_data = loadNormal(Ng_data)
Ng_32F, A_8U = Ng_data
N0_file = shapeResultFile(result_name="InitialNormal",
data_name=shape_name)
N0_data = loadNormal(N0_file)
N0_32F, A_8U = N0_data
for mi, colormap_file in enumerate(colormap_files):
M_32F = loadColorMap(colormap_file)
C0_32F = ColorMapShader(M_32F).diffuseShading(L, Ng_32F)
sfs_method = ToonSFS(L, C0_32F, A_8U)
sfs_method.setInitialNormal(N0_32F)
sfs_method.setNumIterations(iterations=40)
sfs_method.setWeights(w_lap=5.0)
sfs_method.run()
N_32F = sfs_method.normal()
C_32F = sfs_method.shading()
#C_32F = cv2.bilateralFilter(C_32F, 0, 0.1, 3)
C_error = sfs_method.shadingError()
C_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
C_error = trim(C_error, A_8U)
h, w = A_8U.shape
N_error = angleErros(N_32F.reshape(-1, 3),
Ng_32F.reshape(-1, 3)).reshape(h, w)
N_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
N_error = trim(N_error, A_8U)
title = ""
if mi == 0:
title = "Ground-truth"
plot_grid.showImage(setAlpha(C0_32F, to32F(A_8U)), title)
title = ""
if mi == 0:
title = "Our result"
plot_grid.showImage(setAlpha(C_32F, to32F(A_8U)), title)
title = ""
if mi == 0:
title = "Error (shading)"
plot_grid.showColorMap(C_error,
title,
v_min=0,
v_max=0.1,
with_colorbar=True)
title = ""
if mi == 0:
title = "Ground-truth"
plot_grid.showImage(normalToColor(Ng_32F, A_8U), title)
title = ""
if mi == 0:
title = "Our result"
plot_grid.showImage(normalToColor(N_32F, A_8U), title)
title = ""
if mi == 0:
title = "Error (shape)"
plot_grid.showColorMap(N_error,
title,
v_min=0,
v_max=50.0,
with_colorbar=True)
#showMaximize()
file_path = shapeResultFile("ShapeEstimation",
"MaterialShapeEvaluation",
file_ext=".pdf")
fig.savefig(file_path, transparent=False)
def LambertShadingFigure():
target_shapes = [
"Sphere", "Cone", "Blob1", "Man", "Cone", "OctaFlower", "Pulley",
"Grog", "Lucy", "Raptor"
]
target_shapes = ["Blob1", "Pulley", "Lucy"]
shape_names = target_shapes
num_rows = len(shape_names)
num_cols = 6
w = 20
h = w * num_rows / num_cols
fig, axes = plt.subplots(figsize=(w, h))
font_size = 15
fig.subplots_adjust(left=0.02,
right=0.98,
top=0.96,
bottom=0.02,
hspace=0.15,
wspace=0.1)
fig.suptitle("", fontsize=font_size)
plot_grid = SubplotGrid(num_rows, num_cols)
L = normalizeVector(np.array([-0.2, 0.3, 0.6]))
for si, shape_name in enumerate(shape_names):
Ng_data = shapeFile(shape_name)
Ng_data = loadNormal(Ng_data)
Ng_32F, A_8U = Ng_data
N0_file = shapeResultFile(result_name="InitialNormal",
data_name=shape_name)
N0_data = loadNormal(N0_file)
N0_32F, A_8U = N0_data
C0_32F = LambertShader().diffuseShading(L, Ng_32F)
sfs_method = ToonSFS(L, C0_32F, A_8U)
sfs_method.setInitialNormal(N0_32F)
sfs_method.setNumIterations(iterations=70)
sfs_method.setWeights(w_lap=1.0)
sfs_method.run()
N_32F = sfs_method.normal()
C_32F = sfs_method.shading()
C_error = sfs_method.shadingError()
C_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
C_error = trim(C_error, A_8U)
h, w = A_8U.shape
N_error = angleErros(N_32F.reshape(-1, 3),
Ng_32F.reshape(-1, 3)).reshape(h, w)
N_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
N_error = trim(N_error, A_8U)
title = ""
if si == 0:
title = "Ground-truth"
plot_grid.showImage(setAlpha(C0_32F, to32F(A_8U)), title)
title = ""
if si == 0:
title = "Our result"
plot_grid.showImage(setAlpha(C_32F, to32F(A_8U)), title)
title = ""
if si == 0:
title = "Error (shading)"
plot_grid.showColorMap(C_error,
title,
v_min=0,
v_max=0.1,
with_colorbar=True)
title = ""
if si == 0:
title = "Ground-truth"
plot_grid.showImage(normalToColor(Ng_32F, A_8U), title)
title = ""
if si == 0:
title = "Our result"
plot_grid.showImage(normalToColor(N_32F, A_8U), title)
title = ""
if si == 0:
title = "Error (shape)"
plot_grid.showColorMap(N_error,
title,
v_min=0,
v_max=30.0,
with_colorbar=True)
file_path = shapeResultFile("ShapeEstimation",
"LambertEstimationError",
file_ext=".pdf")
fig.savefig(file_path, transparent=True)
def materialShapeVariationFigure():
target_colormaps = [23, 3, 12]
#target_colormaps = [3, 17]
colormap_files = [colorMapFile(cmap_id) for cmap_id in target_colormaps]
target_shapes = ["Blob1", "ThreeBox"]
shape_names = target_shapes
#shape_names = shapeNames()[4:5]
num_shapes = len(shape_names)
num_colormaps = len(colormap_files)
num_rows = num_colormaps
num_cols = 6
w = 20
h = w * num_rows / num_cols
fig, axes = plt.subplots(figsize=(w, h))
font_size = 15
fig.subplots_adjust(left=0.02, right=0.98, top=0.96, bottom=0.02, hspace=0.15, wspace=0.1)
fig.suptitle("", fontsize=font_size)
plot_grid = SubplotGrid(num_rows, num_cols)
L = normalizeVector(np.array([-0.4, 0.5, 0.6]))
shape_name = "Blob1"
Ng_data = shapeFile(shape_name)
Ng_data = loadNormal(Ng_data)
Ng_32F, A_8U = Ng_data
N0_file = shapeResultFile(result_name="InitialNormal", data_name=shape_name)
N0_data = loadNormal(N0_file)
N0_32F, A_8U = N0_data
for mi, colormap_file in enumerate(colormap_files):
M_32F = loadColorMap(colormap_file)
C0_32F = ColorMapShader(M_32F).diffuseShading(L, Ng_32F)
sfs_method = ToonSFS(L, C0_32F, A_8U)
sfs_method.setInitialNormal(N0_32F)
sfs_method.setNumIterations(iterations=40)
sfs_method.setWeights(w_lap=5.0)
sfs_method.run()
N_32F = sfs_method.normal()
C_32F = sfs_method.shading()
#C_32F = cv2.bilateralFilter(C_32F, 0, 0.1, 3)
C_error = sfs_method.shadingError()
C_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
C_error = trim(C_error, A_8U)
h, w = A_8U.shape
N_error = angleErros(N_32F.reshape(-1, 3), Ng_32F.reshape(-1, 3)).reshape(h, w)
N_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
N_error = trim(N_error, A_8U)
title = ""
if mi == 0:
title = "Ground-truth"
plot_grid.showImage(setAlpha(C0_32F, to32F(A_8U)), title)
title = ""
if mi == 0:
title = "Our result"
plot_grid.showImage(setAlpha(C_32F, to32F(A_8U)), title)
title = ""
if mi == 0:
title = "Error (shading)"
plot_grid.showColorMap(C_error, title, v_min=0, v_max=0.1, with_colorbar=True)
title = ""
if mi == 0:
title = "Ground-truth"
plot_grid.showImage(normalToColor(Ng_32F, A_8U), title)
title = ""
if mi == 0:
title = "Our result"
plot_grid.showImage(normalToColor(N_32F, A_8U), title)
title = ""
if mi == 0:
title = "Error (shape)"
plot_grid.showColorMap(N_error, title, v_min=0, v_max=50.0, with_colorbar=True)
#showMaximize()
file_path = shapeResultFile("ShapeEstimation", "MaterialShapeEvaluation", file_ext=".pdf")
fig.savefig(file_path, transparent=False)
def LambertShadingFigure():
target_shapes = ["Sphere", "Cone", "Blob1", "Man", "Cone", "OctaFlower", "Pulley", "Grog", "Lucy", "Raptor"]
target_shapes = ["Blob1", "Pulley", "Lucy"]
shape_names = target_shapes
num_rows = len(shape_names)
num_cols = 6
w = 20
h = w * num_rows / num_cols
fig, axes = plt.subplots(figsize=(w, h))
font_size = 15
fig.subplots_adjust(left=0.02, right=0.98, top=0.96, bottom=0.02, hspace=0.15, wspace=0.1)
fig.suptitle("", fontsize=font_size)
plot_grid = SubplotGrid(num_rows, num_cols)
L = normalizeVector(np.array([-0.2, 0.3, 0.6]))
for si, shape_name in enumerate(shape_names):
Ng_data = shapeFile(shape_name)
Ng_data = loadNormal(Ng_data)
Ng_32F, A_8U = Ng_data
N0_file = shapeResultFile(result_name="InitialNormal", data_name=shape_name)
N0_data = loadNormal(N0_file)
N0_32F, A_8U = N0_data
C0_32F = LambertShader().diffuseShading(L, Ng_32F)
sfs_method = ToonSFS(L, C0_32F, A_8U)
sfs_method.setInitialNormal(N0_32F)
sfs_method.setNumIterations(iterations=70)
sfs_method.setWeights(w_lap=1.0)
sfs_method.run()
N_32F = sfs_method.normal()
C_32F = sfs_method.shading()
C_error = sfs_method.shadingError()
C_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
C_error = trim(C_error, A_8U)
h, w = A_8U.shape
N_error = angleErros(N_32F.reshape(-1, 3), Ng_32F.reshape(-1, 3)).reshape(h, w)
N_error[A_8U < 0.5 * np.max(A_8U)] = 0.0
N_error = trim(N_error, A_8U)
title = ""
if si == 0:
title = "Ground-truth"
plot_grid.showImage(setAlpha(C0_32F, to32F(A_8U)), title)
title = ""
if si == 0:
title = "Our result"
plot_grid.showImage(setAlpha(C_32F, to32F(A_8U)), title)
title = ""
if si == 0:
title = "Error (shading)"
plot_grid.showColorMap(C_error, title, v_min=0, v_max=0.1, with_colorbar=True)
title = ""
if si == 0:
title = "Ground-truth"
plot_grid.showImage(normalToColor(Ng_32F, A_8U), title)
title = ""
if si == 0:
title = "Our result"
plot_grid.showImage(normalToColor(N_32F, A_8U), title)
title = ""
if si == 0:
title = "Error (shape)"
plot_grid.showColorMap(N_error, title, v_min=0, v_max=30.0, with_colorbar=True)
file_path = shapeResultFile("ShapeEstimation", "LambertEstimationError", file_ext=".pdf")
fig.savefig(file_path, transparent=True)
