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import os |
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import PIL |
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import cv2 |
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import math |
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import numpy as np |
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import torch |
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import torchvision |
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import imageio |
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from einops import rearrange |
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def save_videos_grid(videos, path=None, rescale=True, n_rows=4, fps=8, discardN=0): |
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videos = rearrange(videos, "b c t h w -> t b c h w").cpu() |
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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 / 2.0 + 0.5).clamp(0, 1) |
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x = (x * 255).numpy().astype(np.uint8) |
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outputs.append(x) |
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outputs = outputs[discardN:] |
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if path is not None: |
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imageio.mimsave(path, outputs, duration=1000/fps, loop=0) |
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return outputs |
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def convert_image_to_fn(img_type, minsize, image, eps=0.02): |
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width, height = image.size |
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if min(width, height) < minsize: |
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scale = minsize/min(width, height) + eps |
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image = image.resize((math.ceil(width*scale), math.ceil(height*scale))) |
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if image.mode != img_type: |
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return image.convert(img_type) |
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return image |