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import os |
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from pathlib import Path |
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from einops import rearrange |
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import torch |
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import torchvision |
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import numpy as np |
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import imageio |
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CODE_SUFFIXES = { |
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".py", |
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".sh", |
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".yaml", |
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".yml", |
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} |
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def safe_dir(path): |
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""" |
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Create a directory (or the parent directory of a file) if it does not exist. |
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Args: |
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path (str or Path): Path to the directory. |
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Returns: |
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path (Path): Path object of the directory. |
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""" |
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path = Path(path) |
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path.mkdir(exist_ok=True, parents=True) |
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return path |
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def safe_file(path): |
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""" |
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Create the parent directory of a file if it does not exist. |
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Args: |
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path (str or Path): Path to the file. |
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Returns: |
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path (Path): Path object of the file. |
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""" |
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path = Path(path) |
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path.parent.mkdir(exist_ok=True, parents=True) |
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return path |
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def save_videos_grid(videos: torch.Tensor, path: str, rescale=False, n_rows=1, fps=24): |
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"""save videos by video tensor |
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copy from https://github.com/guoyww/AnimateDiff/blob/e92bd5671ba62c0d774a32951453e328018b7c5b/animatediff/utils/util.py#L61 |
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Args: |
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videos (torch.Tensor): video tensor predicted by the model |
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path (str): path to save video |
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rescale (bool, optional): rescale the video tensor from [-1, 1] to . Defaults to False. |
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n_rows (int, optional): Defaults to 1. |
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fps (int, optional): video save fps. Defaults to 8. |
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""" |
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videos = rearrange(videos, "b c t h w -> t b c h w") |
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outputs = [] |
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for x in videos: |
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x = torchvision.utils.make_grid(x, nrow=n_rows) |
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x = x.transpose(0, 1).transpose(1, 2).squeeze(-1) |
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if rescale: |
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x = (x + 1.0) / 2.0 |
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x = torch.clamp(x, 0, 1) |
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x = (x * 255).numpy().astype(np.uint8) |
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outputs.append(x) |
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os.makedirs(os.path.dirname(path), exist_ok=True) |
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imageio.mimsave(path, outputs, fps=fps) |
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