# -*- coding: utf-8 -*- # @Organization : Tongyi Lab, Alibaba # @Author : Lingteng Qiu # @Email : 220019047@link.cuhk.edu.cn # @Time : 2025-08-31 10:02:15 # @Function : FFmpeg video encoding from image sequences import os import imageio.v3 as iio import numpy as np import torch VIDEO_TYPE_LIST = {".avi", ".mp4", ".gif", ".AVI", ".MP4", ".GIF"} def encodeffmpeg(inputs, frame_rate, output, format="png"): """output: need video_name""" assert ( os.path.splitext(output)[-1] in VIDEO_TYPE_LIST ), "output is the format of video, e.g., mp4" assert os.path.isdir(inputs), "input dir is NOT file format" inputs = inputs[:-1] if inputs[-1] == "/" else inputs output = os.path.abspath(output) cmd = ( f"ffmpeg -r {frame_rate} -pattern_type glob -i '{inputs}/*.{format}' " + f'-vcodec libx264 -crf 10 -vf "pad=ceil(iw/2)*2:ceil(ih/2)*2" ' + f"-pix_fmt yuv420p {output} > /dev/null 2>&1" ) print(cmd) output_dir = os.path.dirname(output) if os.path.exists(output): os.remove(output) os.makedirs(output_dir, exist_ok=True) print("encoding imgs to video.....") os.system(cmd) print("video done!") def images_to_video( images, output_path, fps, gradio_codec: bool, verbose=False, bitrate="10M" ): os.makedirs(os.path.dirname(output_path), exist_ok=True) frames = [] for i in range(images.shape[0]): if isinstance(images, torch.Tensor): frame = (images[i].permute(1, 2, 0).cpu().numpy() * 255).astype(np.uint8) assert ( frame.shape[0] == images.shape[2] and frame.shape[1] == images.shape[3] ), f"Frame shape mismatch: {frame.shape} vs {images.shape}" assert ( frame.min() >= 0 and frame.max() <= 255 ), f"Frame value out of range: {frame.min()} ~ {frame.max()}" else: frame = images[i] frames.append(frame) frames = np.stack(frames) iio.imwrite( output_path, frames, fps=fps, codec="libx264", pixelformat="yuv420p", bitrate=bitrate, macro_block_size=16, )