| import numpy as np |
| import torch |
|
|
| from .data_process import DataProcess |
|
|
|
|
| class NormalizeImage(DataProcess): |
| RGB_MEAN = np.array([122.67891434, 116.66876762, 104.00698793]) |
|
|
| def process(self, data): |
| assert 'image' in data, '`image` in data is required by this process' |
| image = data['image'] |
| image -= self.RGB_MEAN |
| image /= 255. |
| image = torch.from_numpy(image).permute(2, 0, 1).float() |
| data['image'] = image |
| return data |
|
|
| @classmethod |
| def restore(self, image): |
| image = image.permute(1, 2, 0).to('cpu').numpy() |
| image = image * 255. |
| image += self.RGB_MEAN |
| image = image.astype(np.uint8) |
| return image |
|
|