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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, |
| ) |
|
|
