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|
| | 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, |
| | ) |
| |
|
