# Copyright (c) 2024 Bytedance Ltd. and/or its affiliates # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os import subprocess from tqdm import tqdm def inference_video_from_dir(input_dir, output_dir, unet_config_path, ckpt_path): os.makedirs(output_dir, exist_ok=True) video_names = sorted([f for f in os.listdir(input_dir) if f.endswith(".mp4")]) for video_name in tqdm(video_names): video_path = os.path.join(input_dir, video_name) audio_path = os.path.join(input_dir, video_name.replace(".mp4", "_audio.wav")) video_out_path = os.path.join(output_dir, video_name.replace(".mp4", "_out.mp4")) inference_command = f"python inference.py --unet_config_path {unet_config_path} --video_path {video_path} --audio_path {audio_path} --video_out_path {video_out_path} --inference_ckpt_path {ckpt_path} --seed 1247" subprocess.run(inference_command, shell=True) if __name__ == "__main__": input_dir = "/mnt/bn/maliva-gen-ai-v2/chunyu.li/HDTF/segmented/cross" output_dir = "/mnt/bn/maliva-gen-ai-v2/chunyu.li/HDTF/segmented/latentsync_cross" unet_config_path = "configs/unet/unet_latent_16_diffusion.yaml" ckpt_path = "output/unet/train-2024_10_08-16:23:43/checkpoints/checkpoint-1920000.pt" inference_video_from_dir(input_dir, output_dir, unet_config_path, ckpt_path)