for post_images in tqdm(os.listdir(output_data_dir)):
root, ext = os.path.splitext(post_images)
img_link = os.path.join(output_data_dir, post_images)
# Only handle DAIN-inference imgs
if root[-1] != "0" and ext == "png":
img = cv2.imread(img_link)
dimension = (img.shape[1] + 2, img.shape[0] + 2)
resized = cv2.resize(img,
dimension,
interpolation=cv2.INTER_LANCZOS4)
crop = resized[1:(dimension[1] - 1), 1:(dimension[0] - 1)]
cv2.imwrite(img_link, crop)
except IOError:
print("IOError: Resizing frames rewrite failure!")
else:
print("Succeed to resize DAIN-inference-frames!")
# STAGE 4: video post-processing
os.chdir(DAIN_PREFIX)
clean_folder(input_data_dir)
file_order(src=output_data_dir, dst=input_data_dir)
output_video_file = f"{args.input_video.split('.')[0]}-{target_fps}.{args.input_video.split('.')[1]}"
video_fusion(
src=input_data_dir + "/%10d.png",
dst=os.path.join(output_data_dir, output_video_file),
fps=target_fps,
thread=4,
)
clean_folder(input_data_dir)
os.system(
f"sed -i 's/num_frames: 240/num_frames: {args.frames}/g' curr_argument.yml"
)
os.system(
f"sed -i 's/longer_side_len: 960/longer_side_len: {args.longer_side_len}/g' curr_argument.yml"
)
# start processing
file_list = os.listdir(input_data_dir)
actual_input_dir = os.path.join(Photo_3D, "image")
actual_output_dir = os.path.join(Photo_3D, "video")
for i in range(len(file_list)):
# transfer inputs
shutil.copy(src=os.path.join(input_data_dir, file_list[i]),
dst=actual_input_dir)
# file_transfer(
# src=os.path.join(input_data_dir, file_list[i]), dst=actual_input_dir
# )
# inference
os.system("python3 main.py --config curr_argument.yml")
# transfer outputs
file_transfer(src=actual_output_dir, dst=output_data_dir)
# clean cache
clean_folder(actual_input_dir)
clean_folder(actual_output_dir)
# clean input
clean_folder(input_data_dir)
os.remove(curr_cfg_file)