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on
Zero
Running
on
Zero
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 |