def load_disp(filename):
gt_disp = None
if gt_disp_name.endswith('pfm'):
gt_disp, scale = load_pfm(gt_disp_name)
gt_disp = gt_disp[::-1, :]
elif gt_disp_name.endswith('npy'):
gt_disp = np.load(gt_disp_name)
gt_disp = gt_disp[::-1, :]
elif gt_disp_name.endswith('exr'):
gt_disp = load_exr(filename)
else:
gt_disp = Image.open(gt_disp_name)
gt_disp = np.ascontiguousarray(gt_disp, dtype=np.float32) / 256
return gt_disp
def load_norm(filename):
gt_norm = None
if filename.endswith('exr'):
gt_norm = load_exr(filename)
# transform visualization normal to its true value
gt_norm = gt_norm * 2.0 - 1.0
## fix opposite normal
#m = gt_norm >= 0
#m[:,:,0] = False
#m[:,:,1] = False
#gt_norm[m] = - gt_norm[m]
return gt_norm
def load_disp(filename):
gt_disp = None
if gt_disp_name.endswith('pfm'):
gt_disp, scale = load_pfm(gt_disp_name)
gt_disp = gt_disp[::-1, :]
elif gt_disp_name.endswith('npy'):
gt_disp = np.load(gt_disp_name)
gt_disp = gt_disp[::-1, :]
elif gt_disp_name.endswith('exr'):
gt_disp = load_exr(filename)
else:
f_in = np.array(Image.open(gt_disp_name))
d_r = f_in[:, :, 0].astype('float32')
d_g = f_in[:, :, 1].astype('float32')
d_b = f_in[:, :, 2].astype('float32')
gt_disp = d_r * 4 + d_g / (2**6) + d_b / (2**14)
return gt_disp