| # Copyright (c) SenseTime Research. All rights reserved. | |
| import os | |
| from PIL import Image | |
| IMG_EXTENSIONS = [ | |
| '.jpg', '.JPG', '.jpeg', '.JPEG', | |
| '.png', '.PNG', '.ppm', '.PPM', '.bmp', '.BMP', '.tiff' | |
| ] | |
| def is_image_file(filename): | |
| return any(filename.endswith(extension) for extension in IMG_EXTENSIONS) | |
| def tensor2im(var): | |
| # var shape: (3, H, W) | |
| var = var.cpu().detach().transpose(0, 2).transpose(0, 1).numpy() | |
| var = ((var + 1) / 2) | |
| var[var < 0] = 0 | |
| var[var > 1] = 1 | |
| var = var * 255 | |
| return Image.fromarray(var.astype('uint8')) | |
| def make_dataset(dir): | |
| images = [] | |
| assert os.path.isdir(dir), '%s is not a valid directory' % dir | |
| for root, _, fnames in sorted(os.walk(dir)): | |
| for fname in fnames: | |
| if is_image_file(fname): | |
| path = os.path.join(root, fname) | |
| fname = fname.split('.')[0] | |
| images.append((fname, path)) | |
| return images | |