def materialList():
shape_name = "ThreeBox"
num_rows = 1
num_cols = len(colorMapFiles())
w = 24
h = w * num_rows / num_cols
L = normalizeVector(np.array([-0.4, 0.5, 0.6]))
fig, axes = plt.subplots(figsize=(w, h))
font_size = 15
fig.subplots_adjust(left=0.02, right=0.98, top=0.96, bottom=0.04, hspace=0.1, wspace=0.05)
fig.suptitle("", fontsize=font_size)
plot_grid = SubplotGrid(num_rows, num_cols)
Ng_data = shapeFile(shape_name)
Ng_data = loadNormal(Ng_data)
Ng_32F, A_8U = Ng_data
for colormap_file in colorMapFilesSortedReflectanceError():
M_32F = loadColorMap(colormap_file)
C0_32F = ColorMapShader(M_32F).diffuseShading(L, Ng_32F)
plot_grid.showImage(setAlpha(C0_32F, to32F(A_8U)), "")
file_path = shapeResultFile("ShapeEstimation", "MaterialList")
fig.savefig(file_path, transparent=True)
def _runColorMap(self, colormap_file, Ng_32F, N0_32F, A_8U):
M_32F = loadColorMap(colormap_file)
L0 = normalizeVector(np.array([-0.2, 0.3, 0.6]))
L0_img = lightSphere(L0)
L0_txt = 0.01 * np.int32(100 * L0)
C0_32F = ColorMapShader(M_32F).diffuseShading(L0, Ng_32F)
I_32F = luminance(C0_32F)
L = lightEstimation(I_32F, N0_32F, A_8U)
L_txt = 0.01 * np.int32(100 * L)
L_img = lightSphere(L)
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 = 1
num_cols = 4
plot_grid = SubplotGrid(num_rows, num_cols)
plot_grid.showImage(setAlpha(C0_32F, A_8U), r'Input image: $\mathbf{c}$', font_size=font_size)
plot_grid.showImage(normalToColor(N0_32F, A_8U), r'Initial normal: $\mathbf{N}_0$')
plot_grid.showImage(L0_img, r'Ground trugh light: $L_g = (%s, %s, %s)$' %(L0_txt[0], L0_txt[1], L0_txt[2]))
plot_grid.showImage(L_img, r'Estimated light: $L = (%s, %s, %s)$' %(L_txt[0], L_txt[1], L_txt[2]))
showMaximize()
def materialErrorTable():
shape_name = "ThreeBox"
L = normalizeVector(np.array([-0.4, 0.5, 0.6]))
num_materials = len(colorMapFiles())
C_errors = np.zeros((num_materials, 3))
N_errors = np.zeros((num_materials, 3))
I_errors = np.zeros((num_materials, 3))
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
A_8U = cv2.bilateralFilter(A_8U, 0, 5, 2)
for mi, color_map_file in enumerate(colorMapFiles()):
M_32F = loadColorMap(color_map_file)
C0_32F = ColorMapShader(M_32F).diffuseShading(L, Ng_32F)
toon_sfs = ToonSFS(L, C0_32F, A_8U)
toon_sfs.setInitialNormal(N0_32F)
toon_sfs.setNumIterations(iterations=20)
toon_sfs.setWeights(w_lap=9.0)
toon_sfs.run()
N_toon = toon_sfs.normal()
C_toon = toon_sfs.shading()
C_lumo, N_lumo = lumoSFS(C0_32F, L, N0_32F, A_8U)
C_wu, N_wu = wuSFS(C0_32F, L, N0_32F, A_8U)
C_error_toon, N_error_toon, I_error_toon = computeErrors(L, C0_32F, C_toon, Ng_32F, N_toon, A_8U)
C_error_lumo, N_error_lumo, I_error_lumo = computeErrors(L, C0_32F, C_lumo, Ng_32F, N_lumo, A_8U)
C_error_wu, N_error_wu, I_error_wu = computeErrors(L, C0_32F, C_wu, Ng_32F, N_wu, A_8U)
C_errors[mi, 0] = np.mean(C_error_toon)
C_errors[mi, 1] = np.mean(C_error_lumo)
C_errors[mi, 2] = np.mean(C_error_wu)
I_errors[mi, 0] = np.mean(I_error_toon)
I_errors[mi, 1] = np.mean(I_error_lumo)
I_errors[mi, 2] = np.mean(I_error_wu)
N_errors[mi, 0] = np.mean(N_error_toon)
N_errors[mi, 1] = np.mean(N_error_lumo)
N_errors[mi, 2] = np.mean(N_error_wu)
file_path = shapeResultFile("ShapeEstimation", "MaterialShadingError", file_ext=".npy")
np.save(file_path, C_errors)
file_path = shapeResultFile("ShapeEstimation", "MaterialNormalError", file_ext=".npy")
np.save(file_path, N_errors)
file_path = shapeResultFile("ShapeEstimation", "MaterialIlluminationError", file_ext=".npy")
np.save(file_path, I_errors)
def colorMapFigure():
L = normalizeVector(np.array([-0.2, 0.3, 0.7]))
N_32F, A_32F = normalSphere(h=512, w=512)
fig, axes = plt.subplots(figsize=(6, 4))
font_size = 15
fig.subplots_adjust(left=0.02,
right=0.98,
top=0.98,
bottom=0.02,
hspace=0.1,
wspace=0.1)
fig.suptitle("", fontsize=font_size)
num_rows = 4
num_cols = 6
plot_grid = SubplotGrid(num_rows, num_cols)
for colormap_file in colorMapFiles():
M_32F = loadColorMap(colormap_file)
C_32F = ColorMapShader(M_32F).diffuseShading(L, N_32F)
plot_grid.showImage(setAlpha(C_32F, A_32F), "")
file_path = os.path.join(colorMapResultsDir(), "ColorMapMaterials.png")
fig.savefig(file_path, transparent=True)
def materialList():
shape_name = "ThreeBox"
num_rows = 1
num_cols = len(colorMapFiles())
w = 24
h = w * num_rows / num_cols
L = normalizeVector(np.array([-0.4, 0.5, 0.6]))
fig, axes = plt.subplots(figsize=(w, h))
font_size = 15
fig.subplots_adjust(left=0.02,
right=0.98,
top=0.96,
bottom=0.04,
hspace=0.1,
wspace=0.05)
fig.suptitle("", fontsize=font_size)
plot_grid = SubplotGrid(num_rows, num_cols)
Ng_data = shapeFile(shape_name)
Ng_data = loadNormal(Ng_data)
Ng_32F, A_8U = Ng_data
for colormap_file in colorMapFilesSortedReflectanceError():
M_32F = loadColorMap(colormap_file)
C0_32F = ColorMapShader(M_32F).diffuseShading(L, Ng_32F)
plot_grid.showImage(setAlpha(C0_32F, to32F(A_8U)), "")
file_path = shapeResultFile("ShapeEstimation", "MaterialList")
fig.savefig(file_path, transparent=True)
def shapeList():
num_rows = 1
num_cols = len(shapeNames())
w = 20
h = w * num_rows / num_cols
cmap_id = 10
colormap_file = colorMapFile(cmap_id)
M_32F = loadColorMap(colormap_file)
L = normalizeVector(np.array([-0.4, 0.5, 0.6]))
fig, axes = plt.subplots(figsize=(w, h))
font_size = 15
fig.subplots_adjust(left=0.02, right=0.98, top=0.96, bottom=0.04, hspace=0.15, wspace=0.1)
fig.suptitle("", fontsize=font_size)
plot_grid = SubplotGrid(num_rows, num_cols)
for shape_name in shapeNames():
Ng_data = shapeFile(shape_name)
Ng_data = loadNormal(Ng_data)
Ng_32F, A_8U = Ng_data
C0_32F = ColorMapShader(M_32F).diffuseShading(L, Ng_32F)
plot_grid.showImage(setAlpha(C0_32F, to32F(A_8U)), "")
file_path = shapeResultFile("ShapeEstimation", "ShapeList")
fig.savefig(file_path, transparent=True)
def computeErrorTables(Lg=normalizeVector(np.array([-0.2, 0.3, 0.6]))):
colormap_files = colorMapFiles()
shape_names = shapeNames()
num_materials = len(colormap_files)
num_shapes = len(shape_names)
L_errors = np.zeros((num_shapes, num_materials))
Ms = []
for colormap_file in colormap_files:
M_32F = loadColorMap(colormap_file)
Ms.append(M_32F)
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
for mi, M_32F in enumerate(Ms):
C0_32F = ColorMapShader(M_32F).diffuseShading(Lg, Ng_32F)
I_32F = luminance(C0_32F)
L = lightEstimation(I_32F, N0_32F, A_8U)
L_errors[si, mi] = angleError(Lg, L)
file_path = shapeResultFile("LightEstimation", "LightEstimationError", file_ext=".npy")
np.save(file_path, L_errors)
def stylizedShadingFigure():
target_shapes = ["Man", "Ogre", "Grog", "Vase"]
target_shapes = [shapeFile(shape_name) for shape_name in target_shapes]
target_colormaps = [1, 5, 10, 3]
target_colormaps = [colorMapFile(cmap_id) for cmap_id in target_colormaps]
fig, axes = plt.subplots(figsize=(12, 4))
font_size = 15
fig.subplots_adjust(left=0.02,
right=0.98,
top=0.98,
bottom=0.02,
hspace=0.1,
wspace=0.1)
fig.suptitle("", fontsize=font_size)
num_rows = 1
num_cols = 4
plot_grid = SubplotGrid(num_rows, num_cols)
Ls = []
Ls.append(normalizeVector(np.array([-0.5, 0.3, 0.7])))
Ls.append(normalizeVector(np.array([0.2, -0.35, 0.4])))
Ls.append(normalizeVector(np.array([-0.2, 0.6, 0.3])))
Ls.append(normalizeVector(np.array([-0.2, 0.6, 0.3])))
for shape_file, colormap_file, L in zip(target_shapes, target_colormaps,
Ls):
N_32F, A_8U = loadNormal(shape_file)
M_32F = loadColorMap(colormap_file)
C_32F = ColorMapShader(M_32F).diffuseShading(L, N_32F)
# C_32F = trim(C_32F, A_8U)
# A_8U = trim(A_8U, A_8U)
C_32F = setAlpha(C_32F, to32F(A_8U))
# h, w = C_32F.shape[:2]
#
# h_t = 512
# w_t = w * h_t / h
# C_32F = cv2.resize(C_32F, (w_t, h_t))
plot_grid.showImage(C_32F, "", alpha_clip=True)
file_path = os.path.join(shapeResultsDir(), "StylizedShading.png")
fig.savefig(file_path, transparent=True)
def colorMapFigure():
L = normalizeVector(np.array([-0.2, 0.3, 0.7]))
N_32F, A_32F = normalSphere(h=512, w=512)
fig, axes = plt.subplots(figsize=(6, 4))
font_size = 15
fig.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.02, hspace=0.1, wspace=0.1)
fig.suptitle("", fontsize=font_size)
num_rows = 4
num_cols = 6
plot_grid = SubplotGrid(num_rows, num_cols)
for colormap_file in colorMapFiles():
M_32F = loadColorMap(colormap_file)
C_32F = ColorMapShader(M_32F).diffuseShading(L, N_32F)
plot_grid.showImage(setAlpha(C_32F, A_32F), "")
file_path = os.path.join(colorMapResultsDir(), "ColorMapMaterials.png")
fig.savefig(file_path, transparent=True)
def _runColorMap(self, colormap_file, Ng_32F, N0_32F, A_8U):
M_32F = loadColorMap(colormap_file)
L0 = normalizeVector(np.array([-0.2, 0.3, 0.6]))
L0_img = lightSphere(L0)
L0_txt = 0.01 * np.int32(100 * L0)
C0_32F = ColorMapShader(M_32F).diffuseShading(L0, Ng_32F)
I_32F = luminance(C0_32F)
L = lightEstimation(I_32F, N0_32F, A_8U)
L_txt = 0.01 * np.int32(100 * L)
L_img = lightSphere(L)
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 = 1
num_cols = 4
plot_grid = SubplotGrid(num_rows, num_cols)
plot_grid.showImage(setAlpha(C0_32F, A_8U),
r'Input image: $\mathbf{c}$',
font_size=font_size)
plot_grid.showImage(normalToColor(N0_32F, A_8U),
r'Initial normal: $\mathbf{N}_0$')
plot_grid.showImage(
L0_img, r'Ground trugh light: $L_g = (%s, %s, %s)$' %
(L0_txt[0], L0_txt[1], L0_txt[2]))
plot_grid.showImage(
L_img, r'Estimated light: $L = (%s, %s, %s)$' %
(L_txt[0], L_txt[1], L_txt[2]))
showMaximize()
def stylizedShadingFigure():
target_shapes = ["Man", "Ogre", "Grog", "Vase"]
target_shapes = [shapeFile(shape_name) for shape_name in target_shapes]
target_colormaps = [1, 5, 10, 3]
target_colormaps = [colorMapFile(cmap_id) for cmap_id in target_colormaps]
fig, axes = plt.subplots(figsize=(12, 4))
font_size = 15
fig.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.02, hspace=0.1, wspace=0.1)
fig.suptitle("", fontsize=font_size)
num_rows = 1
num_cols = 4
plot_grid = SubplotGrid(num_rows, num_cols)
Ls = []
Ls.append(normalizeVector(np.array([-0.5, 0.3, 0.7])))
Ls.append(normalizeVector(np.array([0.2, -0.35, 0.4])))
Ls.append(normalizeVector(np.array([-0.2, 0.6, 0.3])))
Ls.append(normalizeVector(np.array([-0.2, 0.6, 0.3])))
for shape_file, colormap_file, L in zip(target_shapes, target_colormaps, Ls):
N_32F, A_8U = loadNormal(shape_file)
M_32F = loadColorMap(colormap_file)
C_32F = ColorMapShader(M_32F).diffuseShading(L, N_32F)
# C_32F = trim(C_32F, A_8U)
# A_8U = trim(A_8U, A_8U)
C_32F = setAlpha(C_32F, to32F(A_8U))
# h, w = C_32F.shape[:2]
#
# h_t = 512
# w_t = w * h_t / h
# C_32F = cv2.resize(C_32F, (w_t, h_t))
plot_grid.showImage(C_32F, "", alpha_clip=True)
file_path = os.path.join(shapeResultsDir(), "StylizedShading.png")
fig.savefig(file_path, transparent=True)
def errorTable():
colormap_files = colorMapFiles()
num_colormap_files = len(colormap_files)
M_errors = np.zeros((num_colormap_files))
for mi, colormap_file in enumerate(colormap_files):
M_32F = loadColorMap(colormap_file)
C_32F = M_32F.reshape(1, len(M_32F), 3)
I_32F = np.linspace(0.0, 1.0, len(M_32F))
I_32F = I_32F.reshape(C_32F.shape[:2])
reflectance = LambertReflectanceEstimation(C_32F, I_32F)
Ml = reflectance.shading(I_32F)[0, :, :]
I0_32F = luminance(C_32F)
IL_32F = luminance(Ml.reshape(1, -1, 3))
I_min, I_max = np.min(I0_32F), np.max(I0_32F)
M_error = normVectors(M_32F - Ml)
#M_errors[mi] = np.mean(M_error) / (I_max - I_min)
# M_errors[mi] = computeGradientDistance(M_32F, Ml) / (I_max - I_min)
#M_errors[mi] = np.linalg.norm(I0_32F - IL_32F) / (I_max - I_min)
M_errors[mi] = np.mean(M_error) / (I_max - I_min)
# M_errors[mi] = np.linalg.norm(M_32F - Ml) / (I_max - I_min)
# M_errors[mi] = compareHist(M_32F, Ml)
file_path = shapeResultFile("ReflectanceEstimation", "ReflectanceError", file_ext=".npy")
np.save(file_path, M_errors)
plt.plot(M_errors)
plt.show()
def shapeList():
num_rows = 1
num_cols = len(shapeNames())
w = 20
h = w * num_rows / num_cols
cmap_id = 10
colormap_file = colorMapFile(cmap_id)
M_32F = loadColorMap(colormap_file)
L = normalizeVector(np.array([-0.4, 0.5, 0.6]))
fig, axes = plt.subplots(figsize=(w, h))
font_size = 15
fig.subplots_adjust(left=0.02,
right=0.98,
top=0.96,
bottom=0.04,
hspace=0.15,
wspace=0.1)
fig.suptitle("", fontsize=font_size)
plot_grid = SubplotGrid(num_rows, num_cols)
for shape_name in shapeNames():
Ng_data = shapeFile(shape_name)
Ng_data = loadNormal(Ng_data)
Ng_32F, A_8U = Ng_data
C0_32F = ColorMapShader(M_32F).diffuseShading(L, Ng_32F)
plot_grid.showImage(setAlpha(C0_32F, to32F(A_8U)), "")
file_path = shapeResultFile("ShapeEstimation", "ShapeList")
fig.savefig(file_path, transparent=True)
def reflectanceEstimationFigure():
errorTable()
M_errors = loadReflectanceErrorTable()
M_error_orders = np.argsort(M_errors)
print M_errors[M_error_orders]
colormap_files = colorMapFiles()
colormap_files = [colormap_files[M_error_order] for M_error_order in M_error_orders]
colormap_files = colormap_files[0:-1:3]
Ms = []
MLs = []
for colormap_file in colormap_files:
M_32F = loadColorMap(colormap_file)
Ms.append(M_32F)
C_32F = M_32F.reshape(1, len(M_32F), 3)
I_32F = np.linspace(0.0, 1.0, len(M_32F))
I_32F = I_32F.reshape(C_32F.shape[:2])
reflectance = LambertReflectanceEstimation(C_32F, I_32F)
Ml = reflectance.shading(I_32F)
MLs.append(Ml[0, :, :])
num_rows = 3
num_cols = len(colormap_files)
w = 10
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=0.98, bottom=0.02, hspace=0.05, wspace=0.05)
fig.suptitle("", fontsize=font_size)
N_sphere, A_32F = normalSphere(h=512, w=512)
Lg = normalizeVector(np.array([-0.2, 0.3, 0.6]))
plot_grid = SubplotGrid(num_rows, num_cols)
mi = 1
for M, Ml in zip(Ms, MLs):
CM_32F = ColorMapShader(M).diffuseShading(Lg, N_sphere)
CL_32F = ColorMapShader(Ml).diffuseShading(Lg, N_sphere)
C_error = normVectors((CM_32F - CL_32F).reshape(-1, 3)).reshape(CL_32F.shape[:2])
C_error[A_32F < 0.5 * np.max(A_32F)] = 0.0
plot_grid.setPlot(1, mi)
plot_grid.showImage(setAlpha(CM_32F, A_32F), "")
plot_grid.setPlot(2, mi)
plot_grid.showImage(setAlpha(CL_32F, A_32F), "")
plot_grid.setPlot(3, mi)
plot_grid.showColorMap(C_error, "", v_min=0.0, v_max=0.3, with_colorbar=False)
mi += 1
file_path = shapeResultFile("ReflectanceEstimation", "ReflectanceEstimationError")
fig.savefig(file_path, transparent=True)
def relightingFigure(shape_name="Vase", cmap_id=3):
num_methods = 3
num_lights = 2
num_rows = num_lights + 1
num_cols = num_methods + 2
w = 15
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=0.04,
hspace=0.15,
wspace=0.1)
fig.suptitle("", fontsize=font_size)
plot_grid = SubplotGrid(num_rows, num_cols)
Lg = normalizeVector(np.array([-0.2, 0.3, 0.5]))
Lg_img = lightSphere(Lg)
L1 = normalizeVector(np.array([0.0, 0.7, 0.6]))
L2 = normalizeVector(np.array([0.3, 0.5, 0.6]))
# Ls = [normalizeVector(Lg * (1.0 - t) + t * L1) for t in np.linspace(0.0, 1.0, num_lights) ]
Ls = [L1, L2]
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
A_8U = cv2.bilateralFilter(A_8U, 0, 5, 2)
colormap_file = colorMapFile(cmap_id)
M_32F = loadColorMap(colormap_file)
C0_32F = ColorMapShader(M_32F).diffuseShading(Lg, Ng_32F)
toon_sfs = ToonSFS(Lg, C0_32F, A_8U)
toon_sfs.setInitialNormal(N0_32F)
toon_sfs.setNumIterations(iterations=50)
toon_sfs.setWeights(w_lap=0.2)
toon_sfs.run()
N_toon = toon_sfs.normal()
C_toon = toon_sfs.shading()
C_lumo, N_lumo = lumoSFS(C0_32F, Lg, N0_32F, A_8U)
C_wu, N_wu = wuSFS(C0_32F, Lg, N0_32F, A_8U)
M_lumo = estimatedReflectance(C0_32F, Lg, N_lumo, A_8U)
M_wu = estimatedReflectance(C0_32F, Lg, N_wu, A_8U)
plot_grid.showImage(Lg_img, "Light direction")
plot_grid.showImage(setAlpha(C0_32F, to32F(A_8U)), "Ground-truth")
title = ""
plot_grid.showImage(setAlpha(C_lumo, to32F(A_8U)), "Lumo")
#plot_grid.showColorMap(C_error_lumo, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C_wu, to32F(A_8U)), "Lambert assumption")
#plot_grid.showColorMap(C_error_wu, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C_toon, to32F(A_8U)), "Our result")
#plot_grid.showColorMap(C_error_toon, title, v_min=0, v_max=0.1, with_colorbar=True)
for L in Ls:
C1 = ColorMapShader(M_32F).diffuseShading(L, Ng_32F)
C1_lumo = M_lumo.shading(LdotN(L,
N_lumo).flatten()).reshape(C0_32F.shape)
C1_wu = M_wu.shading(LdotN(L, N_wu).flatten()).reshape(C0_32F.shape)
C1_toon = toon_sfs.relighting(L)
plot_grid.showImage(lightSphere(L), "")
plot_grid.showImage(setAlpha(C1, to32F(A_8U)), "")
title = ""
plot_grid.showImage(setAlpha(C1_lumo, to32F(A_8U)), "")
#plot_grid.showColorMap(C_error_lumo, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C1_wu, to32F(A_8U)), "")
#plot_grid.showColorMap(C_error_wu, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C1_toon, to32F(A_8U)), "")
# showMaximize()
file_path = shapeResultFile("Relighting",
"RelightingComparison",
file_ext=".png")
fig.savefig(file_path, transparent=True)
def methodComparisonFigure(shape_name="ThreeBox", cmap_id=10):
num_methods = 3
num_rows = 3
num_cols = 2 * num_methods + 1
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=0.04,
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]))
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
A_8U = cv2.bilateralFilter(A_8U, 0, 5, 2)
colormap_file = colorMapFile(cmap_id)
M_32F = loadColorMap(colormap_file)
C0_32F = ColorMapShader(M_32F).diffuseShading(L, Ng_32F)
toon_sfs = ToonSFS(L, C0_32F, A_8U)
toon_sfs.setInitialNormal(N0_32F)
toon_sfs.setNumIterations(iterations=100)
toon_sfs.setWeights(w_lap=0.1)
toon_sfs.run()
N_toon = toon_sfs.normal()
C_toon = toon_sfs.shading()
C_lumo, N_lumo = lumoSFS(C0_32F, L, N0_32F, A_8U)
C_wu, N_wu = wuSFS(C0_32F, L, N0_32F, A_8U)
C_error_toon, N_error_toon, I_error_toon = computeErrors(
L, C0_32F, C_toon, Ng_32F, N_toon, A_8U)
C_error_lumo, N_error_lumo, I_error_lumo = computeErrors(
L, C0_32F, C_lumo, Ng_32F, N_lumo, A_8U)
C_error_wu, N_error_wu, I_error_wu = computeErrors(L, C0_32F, C_wu, Ng_32F,
N_wu, A_8U)
plot_grid.showImage(setAlpha(C0_32F, to32F(A_8U)), "Ground-truth")
title = ""
plot_grid.showImage(setAlpha(C_lumo, to32F(A_8U)), "Lumo")
plot_grid.showColorMap(C_error_lumo,
title,
v_min=0,
v_max=0.1,
with_colorbar=True)
plot_grid.showImage(setAlpha(C_wu, to32F(A_8U)), "Lambert assumption")
plot_grid.showColorMap(C_error_wu,
title,
v_min=0,
v_max=0.1,
with_colorbar=True)
plot_grid.showImage(setAlpha(C_toon, to32F(A_8U)), "Our result")
plot_grid.showColorMap(C_error_toon,
title,
v_min=0,
v_max=0.1,
with_colorbar=True)
plot_grid.showImage(normalToColor(Ng_32F, A_8U), title)
plot_grid.showImage(normalToColor(N_lumo, A_8U), title)
plot_grid.showColorMap(N_error_lumo,
title,
v_min=0,
v_max=50.0,
with_colorbar=True)
plot_grid.showImage(normalToColor(N_wu, A_8U), title)
plot_grid.showColorMap(N_error_wu,
title,
v_min=0,
v_max=50.0,
with_colorbar=True)
plot_grid.showImage(normalToColor(N_toon, A_8U), title)
plot_grid.showColorMap(N_error_toon,
title,
v_min=0,
v_max=50.0,
with_colorbar=True)
plot_grid.showImage(computeIllumination(L, Ng_32F, A_8U), title)
plot_grid.showImage(computeIllumination(L, N_lumo, A_8U), title)
plot_grid.showColorMap(I_error_lumo,
title,
v_min=0,
v_max=0.2,
with_colorbar=True)
plot_grid.showImage(computeIllumination(L, N_wu, A_8U), title)
plot_grid.showColorMap(I_error_wu,
title,
v_min=0,
v_max=0.2,
with_colorbar=True)
plot_grid.showImage(computeIllumination(L, N_toon, A_8U), title)
plot_grid.showColorMap(I_error_toon,
title,
v_min=0,
v_max=0.2,
with_colorbar=True)
# showMaximize()
file_path = shapeResultFile("ShapeEstimation",
"Comparison_%s_%s" % (shape_name, cmap_id),
file_ext=".png")
fig.savefig(file_path, transparent=True)
def shapeErrorTable():
cmap_id = 10
colormap_file = colorMapFile(cmap_id)
M_32F = loadColorMap(colormap_file)
L = normalizeVector(np.array([-0.4, 0.5, 0.6]))
num_shapes = len(shapeNames())
C_errors = np.zeros((num_shapes, 3))
N_errors = np.zeros((num_shapes, 3))
I_errors = np.zeros((num_shapes, 3))
for si, shape_name in enumerate(shapeNames()):
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
A_8U = cv2.bilateralFilter(A_8U, 0, 5, 2)
C0_32F = ColorMapShader(M_32F).diffuseShading(L, Ng_32F)
toon_sfs = ToonSFS(L, C0_32F, A_8U)
toon_sfs.setInitialNormal(N0_32F)
toon_sfs.setNumIterations(iterations=20)
toon_sfs.setWeights(w_lap=9.0)
toon_sfs.run()
N_toon = toon_sfs.normal()
C_toon = toon_sfs.shading()
C_lumo, N_lumo = lumoSFS(C0_32F, L, N0_32F, A_8U)
C_wu, N_wu = wuSFS(C0_32F, L, N0_32F, A_8U)
C_error_toon, N_error_toon, I_error_toon = computeErrors(
L, C0_32F, C_toon, Ng_32F, N_toon, A_8U)
C_error_lumo, N_error_lumo, I_error_lumo = computeErrors(
L, C0_32F, C_lumo, Ng_32F, N_lumo, A_8U)
C_error_wu, N_error_wu, I_error_wu = computeErrors(
L, C0_32F, C_wu, Ng_32F, N_wu, A_8U)
C_errors[si, 0] = np.mean(C_error_toon)
C_errors[si, 1] = np.mean(C_error_lumo)
C_errors[si, 2] = np.mean(C_error_wu)
I_errors[si, 0] = np.mean(I_error_toon)
I_errors[si, 1] = np.mean(I_error_lumo)
I_errors[si, 2] = np.mean(I_error_wu)
N_errors[si, 0] = np.mean(N_error_toon)
N_errors[si, 1] = np.mean(N_error_lumo)
N_errors[si, 2] = np.mean(N_error_wu)
file_path = shapeResultFile("ShapeEstimation",
"ShapeShadingError",
file_ext=".npy")
np.save(file_path, C_errors)
file_path = shapeResultFile("ShapeEstimation",
"ShapeNormalError",
file_ext=".npy")
np.save(file_path, N_errors)
file_path = shapeResultFile("ShapeEstimation",
"ShapeIlluminationErrorShape",
file_ext=".npy")
np.save(file_path, I_errors)
showShapeErrorTable()
def relightingVideo(shape_name="Ogre", cmap_id=3):
num_methods = 3
num_rows = 1
num_cols = num_methods + 2
num_lights = 120
w = 10
h = 5
fig, axes = plt.subplots(figsize=(w, h))
font_size = 15
fig.subplots_adjust(left=0.02,
right=0.98,
top=0.96,
bottom=0.04,
hspace=0.15,
wspace=0.1)
fig.suptitle("Shading Analysis", fontsize=font_size)
plot_grid = SubplotGrid(num_rows, num_cols)
Lg = normalizeVector(np.array([-0.2, 0.3, 0.5]))
Lg_img = lightSphere(Lg)
L1 = normalizeVector(np.array([0.5, 0.5, 0.6]))
Ls = [
normalizeVector(Lg * (1.0 - t) + t * L1)
for t in np.linspace(0.0, 1.0, num_lights)
]
# Ls = [normalizeVector(Lg + 1.0 * np.cos(t) * np.array([1, 0, 0]) + 1.0 * np.sin(t) * np.array([0, 1, 0])) for t in np.linspace(0.0, 1.0, num_lights) ]
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
A_8U = cv2.bilateralFilter(A_8U, 0, 5, 2)
colormap_file = colorMapFile(cmap_id)
M_32F = loadColorMap(colormap_file)
C0_32F = ColorMapShader(M_32F).diffuseShading(Lg, Ng_32F)
toon_sfs = ToonSFS(Lg, C0_32F, A_8U)
toon_sfs.setInitialNormal(N0_32F)
toon_sfs.setNumIterations(iterations=100)
toon_sfs.setWeights(w_lap=0.2)
toon_sfs.run()
N_toon = toon_sfs.normal()
C_toon = toon_sfs.shading()
C_lumo, N_lumo = lumoSFS(C0_32F, Lg, N0_32F, A_8U)
C_wu, N_wu = wuSFS(C0_32F, Lg, N0_32F, A_8U)
M_lumo = estimatedReflectance(C0_32F, Lg, N_lumo, A_8U)
M_wu = estimatedReflectance(C0_32F, Lg, N_wu, A_8U)
plot_grid.showImage(Lg_img, "Light direction")
plot_grid.showImage(setAlpha(C0_32F, to32F(A_8U)), "Ground-truth")
title = ""
plot_grid.showImage(setAlpha(C_lumo, to32F(A_8U)), "Lumo")
#plot_grid.showColorMap(C_error_lumo, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C_wu, to32F(A_8U)), "Lambert assumption")
#plot_grid.showColorMap(C_error_wu, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C_toon, to32F(A_8U)), "Our result")
#plot_grid.showColorMap(C_error_toon, title, v_min=0, v_max=0.1, with_colorbar=True)
images = []
for i in xrange(48):
images.append(figure2numpy(fig))
for li, L in enumerate(Ls):
print li
fig.clear()
fig.suptitle("Relighting", fontsize=font_size)
plot_grid.setPlot(1, 1)
C1 = ColorMapShader(M_32F).diffuseShading(L, Ng_32F)
C1_lumo = M_lumo.shading(LdotN(L,
N_lumo).flatten()).reshape(C0_32F.shape)
C1_wu = M_wu.shading(LdotN(L, N_wu).flatten()).reshape(C0_32F.shape)
C1_toon = toon_sfs.relighting(L)
plot_grid.showImage(lightSphere(L), "Light direction")
plot_grid.showImage(setAlpha(C1, to32F(A_8U)), "Ground-truth")
title = ""
plot_grid.showImage(setAlpha(C1_lumo, to32F(A_8U)), "Lumo")
#plot_grid.showColorMap(C_error_lumo, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C1_wu, to32F(A_8U)), "Lambert assumption")
#plot_grid.showColorMap(C_error_wu, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C1_toon, to32F(A_8U)), "Our result")
images.append(figure2numpy(fig))
file_path = shapeResultFile("Relighting",
"Relighting_%s_%s" % (shape_name, cmap_id),
file_ext=".wmv")
saveVideo(file_path, images)
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 relightingVideo(shape_name="Ogre", cmap_id=3):
num_methods = 3
num_rows = 1
num_cols = num_methods + 2
num_lights = 120
w = 10
h = 5
fig, axes = plt.subplots(figsize=(w, h))
font_size = 15
fig.subplots_adjust(left=0.02, right=0.98, top=0.96, bottom=0.04, hspace=0.15, wspace=0.1)
fig.suptitle("Shading Analysis", fontsize=font_size)
plot_grid = SubplotGrid(num_rows, num_cols)
Lg = normalizeVector(np.array([-0.2, 0.3, 0.5]))
Lg_img = lightSphere(Lg)
L1 = normalizeVector(np.array([0.5, 0.5, 0.6]))
Ls = [normalizeVector(Lg * (1.0 - t) + t * L1) for t in np.linspace(0.0, 1.0, num_lights) ]
# Ls = [normalizeVector(Lg + 1.0 * np.cos(t) * np.array([1, 0, 0]) + 1.0 * np.sin(t) * np.array([0, 1, 0])) for t in np.linspace(0.0, 1.0, num_lights) ]
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
A_8U = cv2.bilateralFilter(A_8U, 0, 5, 2)
colormap_file = colorMapFile(cmap_id)
M_32F = loadColorMap(colormap_file)
C0_32F = ColorMapShader(M_32F).diffuseShading(Lg, Ng_32F)
toon_sfs = ToonSFS(Lg, C0_32F, A_8U)
toon_sfs.setInitialNormal(N0_32F)
toon_sfs.setNumIterations(iterations=100)
toon_sfs.setWeights(w_lap=0.2)
toon_sfs.run()
N_toon = toon_sfs.normal()
C_toon = toon_sfs.shading()
C_lumo, N_lumo = lumoSFS(C0_32F, Lg, N0_32F, A_8U)
C_wu, N_wu = wuSFS(C0_32F, Lg, N0_32F, A_8U)
M_lumo = estimatedReflectance(C0_32F, Lg, N_lumo, A_8U)
M_wu = estimatedReflectance(C0_32F, Lg, N_wu, A_8U)
plot_grid.showImage(Lg_img, "Light direction")
plot_grid.showImage(setAlpha(C0_32F, to32F(A_8U)), "Ground-truth")
title = ""
plot_grid.showImage(setAlpha(C_lumo, to32F(A_8U)), "Lumo")
#plot_grid.showColorMap(C_error_lumo, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C_wu, to32F(A_8U)), "Lambert assumption")
#plot_grid.showColorMap(C_error_wu, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C_toon, to32F(A_8U)), "Our result")
#plot_grid.showColorMap(C_error_toon, title, v_min=0, v_max=0.1, with_colorbar=True)
images = []
for i in xrange(48):
images.append(figure2numpy(fig))
for li, L in enumerate(Ls):
print li
fig.clear()
fig.suptitle("Relighting", fontsize=font_size)
plot_grid.setPlot(1, 1)
C1 = ColorMapShader(M_32F).diffuseShading(L, Ng_32F)
C1_lumo = M_lumo.shading(LdotN(L, N_lumo).flatten()).reshape(C0_32F.shape)
C1_wu = M_wu.shading(LdotN(L, N_wu).flatten()).reshape(C0_32F.shape)
C1_toon = toon_sfs.relighting(L)
plot_grid.showImage(lightSphere(L), "Light direction")
plot_grid.showImage(setAlpha(C1, to32F(A_8U)), "Ground-truth")
title = ""
plot_grid.showImage(setAlpha(C1_lumo, to32F(A_8U)), "Lumo")
#plot_grid.showColorMap(C_error_lumo, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C1_wu, to32F(A_8U)), "Lambert assumption")
#plot_grid.showColorMap(C_error_wu, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C1_toon, to32F(A_8U)), "Our result")
images.append(figure2numpy(fig))
file_path = shapeResultFile("Relighting", "Relighting_%s_%s" %(shape_name, cmap_id), file_ext=".wmv")
saveVideo(file_path, images)
def relightingFigure(shape_name="Vase", cmap_id=3):
num_methods = 3
num_lights = 2
num_rows = num_lights + 1
num_cols = num_methods + 2
w = 15
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=0.04, hspace=0.15, wspace=0.1)
fig.suptitle("", fontsize=font_size)
plot_grid = SubplotGrid(num_rows, num_cols)
Lg = normalizeVector(np.array([-0.2, 0.3, 0.5]))
Lg_img = lightSphere(Lg)
L1 = normalizeVector(np.array([0.0, 0.7, 0.6]))
L2 = normalizeVector(np.array([0.3, 0.5, 0.6]))
# Ls = [normalizeVector(Lg * (1.0 - t) + t * L1) for t in np.linspace(0.0, 1.0, num_lights) ]
Ls = [L1, L2]
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
A_8U = cv2.bilateralFilter(A_8U, 0, 5, 2)
colormap_file = colorMapFile(cmap_id)
M_32F = loadColorMap(colormap_file)
C0_32F = ColorMapShader(M_32F).diffuseShading(Lg, Ng_32F)
toon_sfs = ToonSFS(Lg, C0_32F, A_8U)
toon_sfs.setInitialNormal(N0_32F)
toon_sfs.setNumIterations(iterations=50)
toon_sfs.setWeights(w_lap=0.2)
toon_sfs.run()
N_toon = toon_sfs.normal()
C_toon = toon_sfs.shading()
C_lumo, N_lumo = lumoSFS(C0_32F, Lg, N0_32F, A_8U)
C_wu, N_wu = wuSFS(C0_32F, Lg, N0_32F, A_8U)
M_lumo = estimatedReflectance(C0_32F, Lg, N_lumo, A_8U)
M_wu = estimatedReflectance(C0_32F, Lg, N_wu, A_8U)
plot_grid.showImage(Lg_img, "Light direction")
plot_grid.showImage(setAlpha(C0_32F, to32F(A_8U)), "Ground-truth")
title = ""
plot_grid.showImage(setAlpha(C_lumo, to32F(A_8U)), "Lumo")
#plot_grid.showColorMap(C_error_lumo, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C_wu, to32F(A_8U)), "Lambert assumption")
#plot_grid.showColorMap(C_error_wu, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C_toon, to32F(A_8U)), "Our result")
#plot_grid.showColorMap(C_error_toon, title, v_min=0, v_max=0.1, with_colorbar=True)
for L in Ls:
C1 = ColorMapShader(M_32F).diffuseShading(L, Ng_32F)
C1_lumo = M_lumo.shading(LdotN(L, N_lumo).flatten()).reshape(C0_32F.shape)
C1_wu = M_wu.shading(LdotN(L, N_wu).flatten()).reshape(C0_32F.shape)
C1_toon = toon_sfs.relighting(L)
plot_grid.showImage(lightSphere(L), "")
plot_grid.showImage(setAlpha(C1, to32F(A_8U)), "")
title = ""
plot_grid.showImage(setAlpha(C1_lumo, to32F(A_8U)), "")
#plot_grid.showColorMap(C_error_lumo, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C1_wu, to32F(A_8U)), "")
#plot_grid.showColorMap(C_error_wu, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C1_toon, to32F(A_8U)), "")
# showMaximize()
file_path = shapeResultFile("Relighting", "RelightingComparison", file_ext=".png")
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 lightEstimationFigure():
target_colormaps = [23, 0, 6, 22, 4, 12]
target_shapes = ["Raptor", "Man", "Blob1", "OctaFlower", "Pulley", "Cone"]
colormap_files = [colorMapFile(cmap_id) for cmap_id in target_colormaps]
shape_names = target_shapes
num_rows = len(shape_names) + 1
num_cols = len(colormap_files) + 1
w = 10
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=0.98, bottom=0.02, hspace=0.05, wspace=0.05)
fig.suptitle("", fontsize=font_size)
plot_grid = SubplotGrid(num_rows, num_cols)
Lg = normalizeVector(np.array([-0.2, 0.3, 0.6]))
Lg_img = lightSphere(Lg)
plot_grid.showImage(Lg_img, "")
Ms = []
for colormap_file in colormap_files:
M_32F = loadColorMap(colormap_file)
Cs_32F = colorMapSphere(Lg, M_32F)
plot_grid.showImage(Cs_32F, "")
Ms.append(M_32F)
L_errors = np.zeros((num_rows, num_cols))
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
plot_grid.showImage(normalToColor(Ng_32F, A_8U), "")
for mi, M_32F in enumerate(Ms):
C0_32F = ColorMapShader(M_32F).diffuseShading(Lg, Ng_32F)
I_32F = luminance(C0_32F)
L = lightEstimation(I_32F, N0_32F, A_8U)
L_errors[si, mi] = angleError(Lg, L)
L_img = lightSphereColorMap(L, v=L_errors[si, mi], v_min=0, v_max=40)
plot_grid.showImage(L_img, "")
L_error_min, L_error_max = np.min(L_errors), np.max(L_errors)
file_path = shapeResultFile("LightEstimation", "LightEstimationError")
fig.savefig(file_path, transparent=True)
def overviewFigure():
cmap_id = 10
colormap_file = colorMapFile(cmap_id)
num_rows = 1
num_cols = 5
w = 10
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=0.05, wspace=0.05)
fig.suptitle("", fontsize=font_size)
plot_grid = SubplotGrid(num_rows, num_cols)
L = normalizeVector(np.array([-0.4, 0.6, 0.6]))
L_img = lightSphere(L)
shape_name = "ThreeBox"
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
M_32F = loadColorMap(colormap_file)
Cg_32F = ColorMapShader(M_32F).diffuseShading(L, Ng_32F)
borders=[0.6, 0.8, 0.92]
colors = [np.array([0.2, 0.2, 0.4]),
np.array([0.3, 0.3, 0.6]),
np.array([0.4, 0.4, 0.8]),
np.array([0.5, 0.5, 1.0])]
#Cg_32F = ToonShader(borders, colors).diffuseShading(L, Ng_32F)
#Cg_32F = cv2.GaussianBlur(Cg_32F, (0,0), 2.0)
sfs_method = ToonSFS(L, Cg_32F, A_8U)
sfs_method.setInitialNormal(N0_32F)
sfs_method.setNumIterations(iterations=40)
sfs_method.setWeights(w_lap=10.0)
sfs_method.run()
N_32F = sfs_method.normal()
I_32F = np.float32(np.clip(LdotN(L, N_32F), 0.0, 1.0))
I0_32F = np.float32(np.clip(LdotN(L, N0_32F), 0.0, 1.0))
C_32F = sfs_method.shading()
C0_32F = sfs_method.initialShading()
M_32F = sfs_method.colorMap().mapImage()
L1 = normalizeVector(np.array([0.0, 0.6, 0.6]))
L1_img = lightSphere(L1)
C1_32F = sfs_method.relighting(L1)
L2 = normalizeVector(np.array([0.5, 0.8, 0.6]))
L2_img = lightSphere(L2)
C2_32F = sfs_method.relighting(L2)
N_sil = silhouetteNormal(A_8U, sigma=7.0)
N_sil[:, :, 2] = N_sil[:, :, 2] ** 10.0
N_sil = normalizeImage(N_sil)
A_sil = 1.0 - N_sil[:, :, 2]
A_sil = to8U(A_sil)
N_xy = N_sil[:, :, 0] ** 2 + N_sil[:, :, 1] ** 2
A_sil[N_xy < 0.1] = 0
title = ""
plot_grid.showImage(setAlpha(Cg_32F, to32F(A_8U)), title)
plot_grid.showImage(normalToColor(N0_32F, A_8U), title)
plot_grid.showImage(setAlpha(C0_32F, to32F(A_8U)), title)
plot_grid.showImage(normalToColor(N_32F, A_8U), title)
plot_grid.showImage(setAlpha(C_32F, to32F(A_8U)), title)
# plot_grid.showImage(normalToColor(Ng_32F, A_8U), title)
#showMaximize()
file_path = shapeResultFile("Overview", "Overview")
fig.savefig(file_path, transparent=True)
file_path = shapeResultFile("Overview", "Cg")
saveRGBA(file_path, setAlpha(Cg_32F, to32F(A_8U)))
file_path = shapeResultFile("Overview", "L")
saveRGB(file_path, gray2rgb(to8U(L_img)))
file_path = shapeResultFile("Overview", "L1")
saveRGB(file_path, gray2rgb(to8U(L1_img)))
file_path = shapeResultFile("Overview", "L2")
saveRGB(file_path, gray2rgb(to8U(L2_img)))
file_path = shapeResultFile("Overview", "N0")
saveNormal(file_path, N0_32F, A_8U)
file_path = shapeResultFile("Overview", "N_sil")
saveNormal(file_path, N_sil, A_sil)
file_path = shapeResultFile("Overview", "N")
saveNormal(file_path, N_32F, A_8U)
file_path = shapeResultFile("Overview", "C0")
saveRGBA(file_path, setAlpha(C0_32F, to32F(A_8U)))
file_path = shapeResultFile("Overview", "C")
saveRGBA(file_path, setAlpha(C_32F, to32F(A_8U)))
file_path = shapeResultFile("Overview", "C1")
saveRGBA(file_path, setAlpha(C1_32F, to32F(A_8U)))
file_path = shapeResultFile("Overview", "C2")
saveRGBA(file_path, setAlpha(C2_32F, to32F(A_8U)))
file_path = shapeResultFile("Overview", "I")
saveRGBA(file_path, setAlpha(gray2rgb(I_32F), to32F(A_8U)))
file_path = shapeResultFile("Overview", "I0")
saveRGBA(file_path, setAlpha(gray2rgb(I0_32F), to32F(A_8U)))
file_path = shapeResultFile("Overview", "M")
saveRGB(file_path, M_32F)
def methodComparisonFigure(shape_name="ThreeBox", cmap_id=10):
num_methods = 3
num_rows = 3
num_cols = 2 * num_methods + 1
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=0.04, 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]))
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
A_8U = cv2.bilateralFilter(A_8U, 0, 5, 2)
colormap_file = colorMapFile(cmap_id)
M_32F = loadColorMap(colormap_file)
C0_32F = ColorMapShader(M_32F).diffuseShading(L, Ng_32F)
toon_sfs = ToonSFS(L, C0_32F, A_8U)
toon_sfs.setInitialNormal(N0_32F)
toon_sfs.setNumIterations(iterations=100)
toon_sfs.setWeights(w_lap=0.1)
toon_sfs.run()
N_toon = toon_sfs.normal()
C_toon = toon_sfs.shading()
C_lumo, N_lumo = lumoSFS(C0_32F, L, N0_32F, A_8U)
C_wu, N_wu = wuSFS(C0_32F, L, N0_32F, A_8U)
C_error_toon, N_error_toon, I_error_toon = computeErrors(L, C0_32F, C_toon, Ng_32F, N_toon, A_8U)
C_error_lumo, N_error_lumo, I_error_lumo = computeErrors(L, C0_32F, C_lumo, Ng_32F, N_lumo, A_8U)
C_error_wu, N_error_wu, I_error_wu = computeErrors(L, C0_32F, C_wu, Ng_32F, N_wu, A_8U)
plot_grid.showImage(setAlpha(C0_32F, to32F(A_8U)), "Ground-truth")
title = ""
plot_grid.showImage(setAlpha(C_lumo, to32F(A_8U)), "Lumo")
plot_grid.showColorMap(C_error_lumo, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C_wu, to32F(A_8U)), "Lambert assumption")
plot_grid.showColorMap(C_error_wu, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(setAlpha(C_toon, to32F(A_8U)), "Our result")
plot_grid.showColorMap(C_error_toon, title, v_min=0, v_max=0.1, with_colorbar=True)
plot_grid.showImage(normalToColor(Ng_32F, A_8U), title)
plot_grid.showImage(normalToColor(N_lumo, A_8U), title)
plot_grid.showColorMap(N_error_lumo, title, v_min=0, v_max=50.0, with_colorbar=True)
plot_grid.showImage(normalToColor(N_wu, A_8U), title)
plot_grid.showColorMap(N_error_wu, title, v_min=0, v_max=50.0, with_colorbar=True)
plot_grid.showImage(normalToColor(N_toon, A_8U), title)
plot_grid.showColorMap(N_error_toon, title, v_min=0, v_max=50.0, with_colorbar=True)
plot_grid.showImage(computeIllumination(L, Ng_32F, A_8U), title)
plot_grid.showImage(computeIllumination(L, N_lumo, A_8U), title)
plot_grid.showColorMap(I_error_lumo, title, v_min=0, v_max=0.2, with_colorbar=True)
plot_grid.showImage(computeIllumination(L, N_wu, A_8U), title)
plot_grid.showColorMap(I_error_wu, title, v_min=0, v_max=0.2, with_colorbar=True)
plot_grid.showImage(computeIllumination(L, N_toon, A_8U), title)
plot_grid.showColorMap(I_error_toon, title, v_min=0, v_max=0.2, with_colorbar=True)
# showMaximize()
file_path = shapeResultFile("ShapeEstimation", "Comparison_%s_%s" %(shape_name, cmap_id), file_ext=".png")
fig.savefig(file_path, transparent=True)