| import torch | |
| import numpy as np | |
| import cv2 | |
| def plot_image(save_path, image, convert_RGB2BGR=True): | |
| if isinstance(image, torch.Tensor): | |
| image = image.detach().cpu().numpy() | |
| image = image.astype(float) | |
| if image.max() < 1.1 and image.min() > -0.1: # [0, 1] | |
| image = image * 255 | |
| elif image.max() < 1.1 and image.min() > -1.1: # [-1, 1] | |
| image = (image + 1.0) * 0.5 * 255 | |
| image = image.clip(0, 255) | |
| image = image.astype(np.uint8) | |
| if len(image.shape) == 4 and image.shape[0] == 1: | |
| image = image[0] | |
| if len(image.shape) == 3 and image.shape[0] <= 4: # C, H, W | |
| image = torch.from_numpy(image).permute(1, 2, 0).numpy() | |
| if len(image.shape) == 3 and convert_RGB2BGR: | |
| image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR) | |
| cv2.imwrite(save_path, image) |
Xet Storage Details
- Size:
- 820 Bytes
- Xet hash:
- 34cbef012463066f74ff76bea8734b6d0f603954a47c3e42227d77ed8004aec2
·
Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.