def cleanNormalBatch():
target = "original"
for data_name in dataNames(target="original"):
N_32F, A_8U = loadData(data_name, target)
N_32F, A_8U = cleanNormal(N_32F, A_8U)
saveData(data_name, N_32F, A_8U, target="normal")
def testToon(method_name, estimate_func):
L_g = normalizeVector(np.array([-0.5, 0.7, 0.5]))
for data_name in normal.dataNames():
N_32F, A_8U = normal.loadData(data_name)
C_32F = toondata.loadData(data_name, L_g)
I_32F = luminance(C_32F[:, :, :3])
estimateResultFunc(data_name, "Toon", N_32F, L_g, I_32F, A_8U, method_name, estimate_func)
def testDiffuse(method_name, estimate_func):
L_g = normalizeVector(np.array([-0.5, 0.7, 0.5]))
for data_name in normal.dataNames():
N_32F, A_8U = normal.loadData(data_name)
I_32F, A_8U = diffuse.loadData(data_name, L_g)
estimateResultFunc(data_name, "Lambert", N_32F, L_g, I_32F, A_8U, method_name, estimate_func)