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 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 _runImp(self):
normal_data = loadNormal(self._data_file)
if normal_data is None:
return
N_32F, A_8U = normal_data
N_32F = trim(N_32F, A_8U)
A_8U = trim(A_8U, A_8U)
A_32F = to32F(A_8U)
L = normalizeVector(np.array([-0.2, 0.3, 0.7]))
I_half = half_lambert.diffuse(N_32F, L)
I_half = setAlpha(gray2rgb(I_half), A_32F)
I_lambert = lambert.diffuse(N_32F, L)
I_lambert = setAlpha(gray2rgb(I_lambert), A_32F)
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'Normal: $N$')
plt.imshow(normalToColor(N_32F, A_8U))
plt.axis('off')
plt.subplot(1, 4, 2)
plt.title(r'Half Lambert: $I_h$')
plt.imshow(I_half)
plt.axis('off')
plt.subplot(1, 4, 3)
plt.title(r'Lambert: $I_l$')
plt.imshow(I_lambert)
plt.axis('off')
showMaximize()
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 _runImp(self):
normal_data = loadNormal(self._data_file)
if normal_data is None:
return
N_32F, A_8U = normal_data
N_32F = trim(N_32F, A_8U)
A_8U = trim(A_8U, A_8U)
A_32F = to32F(A_8U)
L = normalizeVector(np.array([-0.2, 0.3, 0.7]))
I_half = half_lambert.diffuse(N_32F, L)
I_half = setAlpha(gray2rgb(I_half), A_32F)
I_lambert = lambert.diffuse(N_32F, L)
I_lambert = setAlpha(gray2rgb(I_lambert), A_32F)
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'Normal: $N$')
plt.imshow(normalToColor(N_32F, A_8U))
plt.axis('off')
plt.subplot(1, 4, 2)
plt.title(r'Half Lambert: $I_h$')
plt.imshow(I_half)
plt.axis('off')
plt.subplot(1, 4, 3)
plt.title(r'Lambert: $I_l$')
plt.imshow(I_lambert)
plt.axis('off')
showMaximize()
def showImage(self, image, title, alpha_clip=True, font_size=15):
plt.subplot(self._num_rows, self._num_cols, self._plot_id)
plt.title(title, fontsize=font_size)
if len(image.shape) == 2:
plt.gray()
show_image = image
if alpha_clip:
if len(image.shape) == 3:
if image.shape[2] == 4:
show_image = trim(image, alpha(image))
plt.imshow(show_image)
plt.axis('off')
self._plot_id += 1
def showImage(self, image, title, alpha_clip=True, font_size=15):
plt.subplot(self._num_rows, self._num_cols, self._plot_id)
plt.title(title, fontsize=font_size)
if len(image.shape) == 2:
plt.gray()
show_image = image
if alpha_clip:
if len(image.shape) == 3:
if image.shape[2] == 4:
show_image = trim(image, alpha(image))
plt.imshow(show_image)
plt.axis('off')
self._plot_id += 1
def computeIllumination(L, N_32F, A_8U):
I_32F = np.clip(LdotN(L, N_32F), 0.0, 1.0)
I_32F[A_8U < 0.5 * np.max(A_8U)] = 0.0
I_32F = setAlpha(gray2rgb(to8U(I_32F)), A_8U)
I_32F = trim(I_32F, A_8U)
return I_32F
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 _runLayer(self, layer_file):
C0_8U = loadRGBA(layer_file)
if C0_8U is None:
return
A_8U = alpha(C0_8U)
if A_8U is None:
return
A_32F = to32F(A_8U)
C0_32F = to32F(rgb(C0_8U))
I0_32F = luminance(C0_32F)
initial_normals = ["N_lumo.png", "N0_d.png"]
layer_name = os.path.splitext(os.path.basename(layer_file))[0]
for initial_normal in initial_normals:
N0_32F, AN_8U = loadNormal(self.characterResultFile(initial_normal, data_name="BaseDetailSepration"))
N_32F, L, C_32F, M = self._runSFS(C0_32F, A_8U, N0_32F, AN_8U)
L_img = lightSphere(L)
M_img = M.mapImage()
fig, axes = plt.subplots(figsize=(11, 5))
font_size = 15
fig.subplots_adjust(left=0.02, right=0.98, top=0.9, hspace=0.12, wspace=0.02)
fig.suptitle(self.name(), fontsize=font_size)
num_rows = 1
num_cols = 4
plot_grid = SubplotGrid(num_rows, num_cols)
plot_grid.showImage(normalToColor(N0_32F, A_8U), r'Initial Normal: $N_0$')
plot_grid.showImage(normalToColor(N_32F, A_8U), r'Estimated Normal: $N$')
plot_grid.showImage(C0_8U, r'Shading: $C_0$')
plot_grid.showImage(setAlpha(C_32F, A_32F), r'Recovered Shading: $C$')
out_file_path = self.characterResultFile("ToonSFS" + initial_normal, layer_name=layer_name)
plt.savefig(out_file_path)
N_trim = trim(N_32F, A_8U)
N0_trim = trim(N0_32F, A_8U)
C0_trim = trim(C0_32F, A_8U)
A_trim = trim(A_8U, A_8U)
out_file_path = self.characterResultFile(initial_normal, layer_name=layer_name)
saveNormal(out_file_path, N_trim, A_trim)
images = self._relightingImages(N_trim, A_trim, M)
initial_normal_name = os.path.splitext(initial_normal)[0]
video_name = "Relighting" + initial_normal_name + ".wmv"
out_file_path = self.characterResultFile(video_name, layer_name=layer_name)
saveVideo(out_file_path, images)
images = self._relightingOffsetImages(L, C0_trim, N0_trim, A_trim, M)
video_name = "RelightingOffset" + initial_normal_name + ".wmv"
out_file_path = self.characterResultFile(video_name, layer_name=layer_name)
saveVideo(out_file_path, images)
def _runLayer(self, layer_file):
C0_8U = loadRGBA(layer_file)
if C0_8U is None:
return
A_8U = alpha(C0_8U)
if A_8U is None:
return
A_32F = to32F(A_8U)
C0_32F = to32F(rgb(C0_8U))
I0_32F = luminance(C0_32F)
initial_normals = ["N_lumo.png", "N0_d.png"]
layer_name = os.path.splitext(os.path.basename(layer_file))[0]
for initial_normal in initial_normals:
N0_32F, AN_8U = loadNormal(
self.characterResultFile(initial_normal,
data_name="BaseDetailSepration"))
N_32F, L, C_32F, M = self._runSFS(C0_32F, A_8U, N0_32F, AN_8U)
L_img = lightSphere(L)
M_img = M.mapImage()
fig, axes = plt.subplots(figsize=(11, 5))
font_size = 15
fig.subplots_adjust(left=0.02,
right=0.98,
top=0.9,
hspace=0.12,
wspace=0.02)
fig.suptitle(self.name(), fontsize=font_size)
num_rows = 1
num_cols = 4
plot_grid = SubplotGrid(num_rows, num_cols)
plot_grid.showImage(normalToColor(N0_32F, A_8U),
r'Initial Normal: $N_0$')
plot_grid.showImage(normalToColor(N_32F, A_8U),
r'Estimated Normal: $N$')
plot_grid.showImage(C0_8U, r'Shading: $C_0$')
plot_grid.showImage(setAlpha(C_32F, A_32F),
r'Recovered Shading: $C$')
out_file_path = self.characterResultFile("ToonSFS" +
initial_normal,
layer_name=layer_name)
plt.savefig(out_file_path)
N_trim = trim(N_32F, A_8U)
N0_trim = trim(N0_32F, A_8U)
C0_trim = trim(C0_32F, A_8U)
A_trim = trim(A_8U, A_8U)
out_file_path = self.characterResultFile(initial_normal,
layer_name=layer_name)
saveNormal(out_file_path, N_trim, A_trim)
images = self._relightingImages(N_trim, A_trim, M)
initial_normal_name = os.path.splitext(initial_normal)[0]
video_name = "Relighting" + initial_normal_name + ".wmv"
out_file_path = self.characterResultFile(video_name,
layer_name=layer_name)
saveVideo(out_file_path, images)
images = self._relightingOffsetImages(L, C0_trim, N0_trim, A_trim,
M)
video_name = "RelightingOffset" + initial_normal_name + ".wmv"
out_file_path = self.characterResultFile(video_name,
layer_name=layer_name)
saveVideo(out_file_path, images)
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)
N0_32F = trim(N0_32F, A_8U)
A_32F = trim(A_32F, A_8U)
A_8U = trim(A_8U, A_8U)
L = normalizeVector(np.array([0.5, -0.2, 0.7]))
C0_32F = ToonShader().diffuseShading(L, N0_32F)
I0_32F = luminance(C0_32F)
I_min, I_max = np.min(I0_32F), np.max(I0_32F)
I_scale = (I0_32F - I_min) / (I_max - I_min)
I_L = cv2.Laplacian(cv2.GaussianBlur(I_scale, (0, 0), 31.0), cv2.CV_32F, ksize=1)
I_L_avg = np.average(np.abs(I_L))
Ix = cv2.Sobel(I0_32F, cv2.CV_64F, 1, 0, ksize=1)
Ix = cv2.GaussianBlur(Ix, (0, 0), 3.0)
Ixx = cv2.Sobel(Ix, cv2.CV_64F, 1, 0, ksize=1)
Ixx = cv2.GaussianBlur(Ixx, (0, 0), 5.0)
Iy = -cv2.Sobel(I0_32F, cv2.CV_64F, 0, 1, ksize=1)
Iy = cv2.GaussianBlur(Iy, (0, 0), 3.0)
Iyy = -cv2.Sobel(Iy, cv2.CV_64F, 0, 1, ksize=1)
Iyy = cv2.GaussianBlur(Iyy, (0, 0), 5.0)
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 = 5
plot_grid = SubplotGrid(num_rows, num_cols)
Nx = cv2.Sobel(N0_32F[:, :, 0], cv2.CV_64F, 1, 0, ksize=1)
Nx = cv2.GaussianBlur(Nx, (0, 0), 3.0)
Nxx = cv2.Sobel(Nx, cv2.CV_64F, 1, 0, ksize=1)
Nxx = cv2.GaussianBlur(Nxx, (0, 0), 5.0)
Ny = -cv2.Sobel(N0_32F[:, :, 1], cv2.CV_64F, 0, 1, ksize=1)
Ny = cv2.GaussianBlur(Ny, (0, 0), 3.0)
Nyy = -cv2.Sobel(Ny, cv2.CV_64F, 0, 1, ksize=1)
Nyy = cv2.GaussianBlur(Nyy, (0, 0), 5.0)
Nz_L = cv2.Laplacian(cv2.GaussianBlur(N0_32F[:, :, 2], (0, 0), 5.0), cv2.CV_32F, ksize=5)
Nz_L_avg = np.average(np.abs(Nz_L))
Nz_L *= 1.0 / Nz_L_avg
I_L *= 1.0 / I_L_avg
print I_L_avg, Nz_L_avg
Nz_L = np.clip(Nz_L, -5.0, 5.0)
I_L = np.clip(I_L, -5.0, 5.0)
plot_grid.showColorMap(N0_32F[:, :, 0], r'$N_{x}$', v_min=-0.01, v_max=0.01)
plot_grid.showColorMap(N0_32F[:, :, 1], r'$N_{y}$', v_min=-0.01, v_max=0.01)
plot_grid.showColorMap(Nx, r'$N_{xx}$', v_min=-0.01, v_max=0.01)
plot_grid.showColorMap(Ny, r'$N_{yy}$', v_min=-0.01, v_max=0.01)
plot_grid.showColorMap(Nz_L, r'$Nz_L$')
#plot_grid.showColorMap(Nx + Ny, r'$N_{xx} + N_{yy}$', v_min=-0.01, v_max=0.01)
# Ixx[Ixx>0] = 1.0
# Ixx[Ixx<0] = -1.0
# Iyy[Iyy>0] = 1.0
# Iyy[Iyy<0] = -1.0
plot_grid.showColorMap(-Ix, r'$I_{x}$', v_min=-0.001, v_max=0.001)
plot_grid.showColorMap(-Iy, r'$I_{y}$', v_min=-0.001, v_max=0.001)
plot_grid.showColorMap(-Ixx, r'$I_{xx}$', v_min=-0.001, v_max=0.001)
plot_grid.showColorMap(-Iyy, r'$I_{yy}$', v_min=-0.001, v_max=0.001)
plot_grid.showColorMap(I_L, r'$I_L$')
#plot_grid.showColorMap(-Ixx - Iyy, r'$I_{xx} + I_{yy}$', v_min=-0.01, v_max=0.01)
#plot_grid.showColorMap(Iy, r'$I_{y}$')
showMaximize()
def computeIllumination(L, N_32F, A_8U):
I_32F = np.clip(LdotN(L, N_32F), 0.0, 1.0)
I_32F[A_8U < 0.5 * np.max(A_8U)] = 0.0
I_32F = setAlpha(gray2rgb(to8U(I_32F)), A_8U)
I_32F = trim(I_32F, A_8U)
return I_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)
N0_32F = trim(N0_32F, A_8U)
A_32F = trim(A_32F, A_8U)
A_8U = trim(A_8U, A_8U)
L = normalizeVector(np.array([0.5, -0.2, 0.7]))
C0_32F = ToonShader().diffuseShading(L, N0_32F)
I0_32F = luminance(C0_32F)
I_min, I_max = np.min(I0_32F), np.max(I0_32F)
I_scale = (I0_32F - I_min) / (I_max - I_min)
I_L = cv2.Laplacian(cv2.GaussianBlur(I_scale, (0, 0), 31.0), cv2.CV_32F, ksize=1)
I_L_avg = np.average(np.abs(I_L))
Ix = cv2.Sobel(I0_32F, cv2.CV_64F, 1, 0, ksize=1)
Ix = cv2.GaussianBlur(Ix, (0, 0), 3.0)
Ixx = cv2.Sobel(Ix, cv2.CV_64F, 1, 0, ksize=1)
Ixx = cv2.GaussianBlur(Ixx, (0, 0), 5.0)
Iy = -cv2.Sobel(I0_32F, cv2.CV_64F, 0, 1, ksize=1)
Iy = cv2.GaussianBlur(Iy, (0, 0), 3.0)
Iyy = -cv2.Sobel(Iy, cv2.CV_64F, 0, 1, ksize=1)
Iyy = cv2.GaussianBlur(Iyy, (0, 0), 5.0)
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 = 5
plot_grid = SubplotGrid(num_rows, num_cols)
Nx = cv2.Sobel(N0_32F[:, :, 0], cv2.CV_64F, 1, 0, ksize=1)
Nx = cv2.GaussianBlur(Nx, (0, 0), 3.0)
Nxx = cv2.Sobel(Nx, cv2.CV_64F, 1, 0, ksize=1)
Nxx = cv2.GaussianBlur(Nxx, (0, 0), 5.0)
Ny = -cv2.Sobel(N0_32F[:, :, 1], cv2.CV_64F, 0, 1, ksize=1)
Ny = cv2.GaussianBlur(Ny, (0, 0), 3.0)
Nyy = -cv2.Sobel(Ny, cv2.CV_64F, 0, 1, ksize=1)
Nyy = cv2.GaussianBlur(Nyy, (0, 0), 5.0)
Nz_L = cv2.Laplacian(cv2.GaussianBlur(N0_32F[:, :, 2], (0, 0), 5.0), cv2.CV_32F, ksize=5)
Nz_L_avg = np.average(np.abs(Nz_L))
Nz_L *= 1.0 / Nz_L_avg
I_L *= 1.0 / I_L_avg
print I_L_avg, Nz_L_avg
Nz_L = np.clip(Nz_L, -5.0, 5.0)
I_L = np.clip(I_L, -5.0, 5.0)
plot_grid.showColorMap(N0_32F[:, :, 0], r"$N_{x}$", v_min=-0.01, v_max=0.01)
plot_grid.showColorMap(N0_32F[:, :, 1], r"$N_{y}$", v_min=-0.01, v_max=0.01)
plot_grid.showColorMap(Nx, r"$N_{xx}$", v_min=-0.01, v_max=0.01)
plot_grid.showColorMap(Ny, r"$N_{yy}$", v_min=-0.01, v_max=0.01)
plot_grid.showColorMap(Nz_L, r"$Nz_L$")
# plot_grid.showColorMap(Nx + Ny, r'$N_{xx} + N_{yy}$', v_min=-0.01, v_max=0.01)
# Ixx[Ixx>0] = 1.0
# Ixx[Ixx<0] = -1.0
# Iyy[Iyy>0] = 1.0
# Iyy[Iyy<0] = -1.0
plot_grid.showColorMap(-Ix, r"$I_{x}$", v_min=-0.001, v_max=0.001)
plot_grid.showColorMap(-Iy, r"$I_{y}$", v_min=-0.001, v_max=0.001)
plot_grid.showColorMap(-Ixx, r"$I_{xx}$", v_min=-0.001, v_max=0.001)
plot_grid.showColorMap(-Iyy, r"$I_{yy}$", v_min=-0.001, v_max=0.001)
plot_grid.showColorMap(I_L, r"$I_L$")
# plot_grid.showColorMap(-Ixx - Iyy, r'$I_{xx} + I_{yy}$', v_min=-0.01, v_max=0.01)
# plot_grid.showColorMap(Iy, r'$I_{y}$')
showMaximize()
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)
