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import os |
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import pdb |
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import torch |
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import numpy as np |
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import imageio |
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import cv2 |
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import imageio.v3 as iio |
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VIDEO_TYPE_LIST = {'.avi','.mp4','.gif','.AVI','.MP4','.GIF'} |
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def encodeffmpeg(inputs, frame_rate, output, format="png"): |
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"""output: need video_name""" |
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assert ( |
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os.path.splitext(output)[-1] in VIDEO_TYPE_LIST |
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), "output is the format of video, e.g., mp4" |
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assert os.path.isdir(inputs), "input dir is NOT file format" |
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inputs = inputs[:-1] if inputs[-1] == "/" else inputs |
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output = os.path.abspath(output) |
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cmd = ( |
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f"ffmpeg -r {frame_rate} -pattern_type glob -i '{inputs}/*.{format}' " |
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+ f'-vcodec libx264 -crf 10 -vf "pad=ceil(iw/2)*2:ceil(ih/2)*2" ' |
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+ f"-pix_fmt yuv420p {output} > /dev/null 2>&1" |
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) |
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print(cmd) |
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output_dir = os.path.dirname(output) |
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if os.path.exists(output): |
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os.remove(output) |
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os.makedirs(output_dir, exist_ok=True) |
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print("encoding imgs to video.....") |
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os.system(cmd) |
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print("video done!") |
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def images_to_video(images, output_path, fps, gradio_codec: bool, verbose=False, bitrate="2M"): |
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os.makedirs(os.path.dirname(output_path), exist_ok=True) |
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frames = [] |
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for i in range(images.shape[0]): |
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if isinstance(images, torch.Tensor): |
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frame = (images[i].permute(1, 2, 0).cpu().numpy() * 255).astype(np.uint8) |
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assert frame.shape[0] == images.shape[2] and frame.shape[1] == images.shape[3], \ |
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f"Frame shape mismatch: {frame.shape} vs {images.shape}" |
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assert frame.min() >= 0 and frame.max() <= 255, \ |
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f"Frame value out of range: {frame.min()} ~ {frame.max()}" |
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else: |
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frame = images[i] |
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width, height = frame.shape[1], frame.shape[0] |
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frames.append(frame) |
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frames = frames[:200] |
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frames = np.stack(frames) |
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print("start saving {} using imageio.v3 .".format(output_path)) |
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iio.imwrite(output_path,frames,fps=fps,codec="libx264",pixelformat="yuv420p",bitrate=bitrate, macro_block_size=32) |
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print("saved {} using imageio.v3 .".format(output_path)) |