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import os
import PIL
import cv2
import math
import numpy as np
import torch
import torchvision
import imageio
from einops import rearrange
def save_videos_grid(videos, path=None, rescale=True, n_rows=4, fps=8, discardN=0):
videos = rearrange(videos, "b c t h w -> t b c h w").cpu()
outputs = []
for x in videos:
x = torchvision.utils.make_grid(x, nrow=n_rows)
x = x.transpose(0, 1).transpose(1, 2).squeeze(-1)
if rescale:
x = (x / 2.0 + 0.5).clamp(0, 1) # -1,1 -> 0,1
x = (x * 255).numpy().astype(np.uint8)
#x = adjust_gamma(x, 0.5)
outputs.append(x)
outputs = outputs[discardN:]
if path is not None:
#os.makedirs(os.path.dirname(path), exist_ok=True)
imageio.mimsave(path, outputs, duration=1000/fps, loop=0)
return outputs
def convert_image_to_fn(img_type, minsize, image, eps=0.02):
width, height = image.size
if min(width, height) < minsize:
scale = minsize/min(width, height) + eps
image = image.resize((math.ceil(width*scale), math.ceil(height*scale)))
if image.mode != img_type:
return image.convert(img_type)
return image