:param model: :return:
(model)
| 123 | return True |
| 124 | |
| 125 | def generagedImage(model): |
| 126 | """ |
| 127 | :param model: |
| 128 | :return: |
| 129 | """ |
| 130 | inputImg = np.array(Image.open(imagePath["filename"])) |
| 131 | # 图片由两张图片拼接的大小为1200 x 1200大小， |
| 132 | input_image = inputImg[:, :600, :] |
| 133 | target_image = inputImg[:, 600:, :] |
| 134 | |
| 135 | # 图像增强 |
| 136 | augmentations = config.both_transform( |
| 137 | image=input_image, |
| 138 | image0=target_image |
| 139 | ) |
| 140 | input_image, target_image = augmentations["image"], augmentations["image0"] |
| 141 | |
| 142 | input_image = config.transform_only_input(image=input_image)["image"] |
| 143 | target_image = config.transform_only_mask(image=target_image)["image"] |
| 144 | |
| 145 | img_transform = torch.unsqueeze(input=input_image,dim=0) |
| 146 | transformImg = model(img_transform) |
| 147 | save_image(transformImg * 0.5 + 0.5,f"cur.png") |
| 148 | print('cur.type: {}'.format(type(transformImg))) |
| 149 | save_image(target_image * 0.5 + 0.5, f"label.png") |
| 150 | |
| 151 | tkImage0 = '' |
| 152 | tkImage4 = '' |