| import torch | |
| import numpy as np | |
| import cv2 | |
| def tensor2img_denorm(tensor): | |
| std = torch.tensor([0.229, 0.224, 0.225]).view(1, 3, 1, 1) | |
| mean = torch.tensor([0.485, 0.456, 0.406]).view(1, 3, 1, 1) | |
| tensor = std * tensor.detach().cpu() + mean | |
| img = tensor.numpy() | |
| img = img.transpose(0, 2, 3, 1)[0] | |
| img = np.clip(img * 255, 0.0, 255.0).astype(np.uint8) | |
| return img | |
| def tensor2img(tensor): | |
| tensor = tensor.detach().cpu().numpy() | |
| img = tensor.transpose(0, 2, 3, 1)[0] | |
| img = np.clip(img * 255, 0.0, 255.0).astype(np.uint8) | |
| return img | |
| def show_tensor(tensor, name): | |
| img = cv2.cvtColor(tensor2img(tensor), cv2.COLOR_RGB2BGR) | |
| cv2.namedWindow(name, cv2.WINDOW_NORMAL) | |
| cv2.imshow(name, img) | |
| cv2.waitKey() | |