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| # Copyright (c) 2023-2024, Zexin He | |
| # | |
| # 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 | |
| # | |
| # https://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 numpy as np | |
| import torch | |
| def images_to_video(images, output_path, fps, gradio_codec: bool, verbose=False): | |
| import imageio | |
| # images: torch.tensor (T, C, H, W), 0-1 or numpy: (T, H, W, 3) 0-255 | |
| 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) | |
| if gradio_codec: | |
| imageio.mimwrite(output_path, frames, fps=fps, quality=10) | |
| else: | |
| # imageio.mimwrite(output_path, frames, fps=fps, codec='mpeg4', quality=10) | |
| imageio.mimwrite(output_path, frames, fps=fps, quality=10) | |
| if verbose: | |
| print(f"Using gradio codec option {gradio_codec}") | |
| print(f"Saved video to {output_path}") | |
| def save_images2video(img_lst, v_pth, fps): | |
| import moviepy.editor as mpy | |
| # Convert the list of NumPy arrays to a list of ImageClip objects | |
| clips = [mpy.ImageClip(img).set_duration(0.1) for img in img_lst] # 0.1 seconds per frame | |
| # Concatenate the ImageClips into a single VideoClip | |
| video = mpy.concatenate_videoclips(clips, method="compose") | |
| # Write the VideoClip to a file | |
| video.write_videofile(v_pth, fps=fps) # setting fps to 10 as example | |
| print("save video to:", v_pth) | |
| if __name__ == "__main__": | |
| from glob import glob | |
| clip_name = "clip1" | |
| ptn = f"./assets/sample_motion/export/{clip_name}/images/*.png" | |
| images_pths = glob(ptn) | |
| import cv2 | |
| import numpy as np | |
| images = [cv2.imread(pth) for pth in images_pths] | |
| save_images2video(images, "./assets/sample_mption/export/{clip_name}/video.mp4", 25, True) |