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 errorInfo():
shape_names = shapeNames()
file_path = shapeResultFile("ShapeEstimation",
"ShadingError",
file_ext=".npy")
C_errors = np.load(file_path)
C_error_orders = np.argsort(C_errors)
print "Small Shading Error: ", np.min(C_errors)
for C_error_order in C_error_orders[:5]:
print " ", shape_names[C_error_order]
print "Large Shading Error: ", np.max(C_errors)
for C_error_order in C_error_orders[-5:]:
print " ", shape_names[C_error_order]
file_path = shapeResultFile("ShapeEstimation",
"NormalError",
file_ext=".npy")
N_errors = np.load(file_path)
N_error_orders = np.argsort(N_errors)
print "Small Normal Error: ", np.min(N_errors)
for N_error_order in N_error_orders[:5]:
print " ", shape_names[N_error_order]
print "Large Normal Error: ", np.max(N_errors)
for N_error_order in N_error_orders[-5:]:
print " ", shape_names[N_error_order]
def errorInfo():
shape_names = shapeNames()
file_path = shapeResultFile("ShapeEstimation", "ShadingError", file_ext=".npy")
C_errors = np.load(file_path)
C_error_orders = np.argsort(C_errors)
print "Small Shading Error: ", np.min(C_errors)
for C_error_order in C_error_orders[:5]:
print " ", shape_names[C_error_order]
print "Large Shading Error: ", np.max(C_errors)
for C_error_order in C_error_orders[-5:]:
print " ", shape_names[C_error_order]
file_path = shapeResultFile("ShapeEstimation", "NormalError", file_ext=".npy")
N_errors = np.load(file_path)
N_error_orders = np.argsort(N_errors)
print "Small Normal Error: ", np.min(N_errors)
for N_error_order in N_error_orders[:5]:
print " ", shape_names[N_error_order]
print "Large Normal Error: ", np.max(N_errors)
for N_error_order in N_error_orders[-5:]:
print " ", shape_names[N_error_order]
def errorInfo():
colormap_files = colorMapFiles()
shape_names = shapeNames()
num_materials = len(colormap_files)
num_shapes = len(shape_names)
file_path = shapeResultFile("LightEstimation", "LightEstimationError", file_ext=".npy")
L_errors = np.load(file_path)
shape_errors = np.zeros(num_shapes)
for si, shape_name in enumerate(shape_names):
shape_errors[si] = np.average(L_errors[si, :])
shape_error_orders = np.argsort(shape_errors)
print shape_error_orders
print shape_error_orders[:3]
print shape_error_orders[-3:]
for shape_error_order in shape_error_orders[:3]:
print shape_names[shape_error_order]
for shape_error_order in shape_error_orders[-3:]:
print shape_names[shape_error_order]
material_errors = np.zeros(num_materials)
for mi in xrange(num_materials):
material_errors[mi] = np.average(L_errors[:, mi])
material_error_orders = np.argsort(material_errors)
print material_error_orders[:3]
print material_error_orders[-3:]
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 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 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 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 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 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()
