img_path_name.sort()
for i in range(len(img_path_name)):
# load rgb images
rgb = cv2.imread(img_path_name[i])
rgb = cv2.cvtColor(rgb, cv2.COLOR_BGR2RGB)
rgb = np.float32(rgb) / 255.0
rgb = np.expand_dims(np.transpose(rgb, [2, 0, 1]), axis=0).copy()
print(img_path_name[i].split('/')[-1])
_, img_res = reconstruction_patch_image_gpu(rgb, model, 128, 128)
_, img_res_overlap = reconstruction_patch_image_gpu(
rgb[:, :, 128 // 2:, 128 // 2:], model, 128, 128)
img_res[128 // 2:, 128 //
2:, :] = (img_res[128 // 2:, 128 // 2:, :] + img_res_overlap) / 2.0
rgbFlip = np.flip(rgb, 2).copy()
_, img_resFlip = reconstruction_patch_image_gpu(rgbFlip, model, 128, 128)
_, img_res_overlapFlip = reconstruction_patch_image_gpu(
rgbFlip[:, :, 128 // 2:, 128 // 2:], model, 128, 128)
img_resFlip[128 // 2:,
128 // 2:, :] = (img_resFlip[128 // 2:, 128 // 2:, :] +
img_res_overlapFlip) / 2.0
img_resFlip = np.flip(img_resFlip, 0)
img_res = (img_res + img_resFlip) / 2
mat_name = img_path_name[i].split('/')[-1][:-14] + '.mat'
mat_dir = os.path.join(result_path, mat_name)
save_matv73(mat_dir, var_name, img_res)
mat_path0_name.sort()
mat_path1_name.sort()
mat_path2_name.sort()
mat_path3_name.sort()
for i in range(len(mat_path1_name)):
hf0 = h5py.File(mat_path0_name[i])
data0 = hf0.get('cube')
res0 = np.transpose(np.array(data0), [2, 1, 0])
hf1 = h5py.File(mat_path1_name[i])
data1 = hf1.get('cube')
res1 = np.transpose(np.array(data1), [2, 1, 0])
hf2 = h5py.File(mat_path2_name[i])
data2 = hf2.get('cube')
res2 = np.transpose(np.array(data2), [2, 1, 0])
hf3 = h5py.File(mat_path3_name[i])
data3 = hf3.get('cube')
res3 = np.transpose(np.array(data3), [2, 1, 0])
res = 0.25 * res0 + 0.25 * res1 + 0.25 * res2 + 0.25 * res3
print(mat_path0_name[i].split('/')[-1], mat_path1_name[i].split('/')[-1], mat_path2_name[i].split('/')[-1], mat_path3_name[i].split('/')[-1])
mat_dir = os.path.join(save_path, mat_path1_name[i].split('/')[-1])
save_matv73(mat_dir, 'cube', res)
