(self)
| 77 | return cls._instance |
| 78 | |
| 79 | def initialize(self): |
| 80 | self.transformer_ = [create_transforms_inference(h=512, w=512), |
| 81 | create_transforms_inference1(h=512, w=512), |
| 82 | create_transforms_inference2(h=512, w=512), |
| 83 | create_transforms_inference3(h=512, w=512), |
| 84 | create_transforms_inference4(h=512, w=512), |
| 85 | create_transforms_inference5(h=512, w=512)] |
| 86 | self.srm = SRMConv2d_simple() |
| 87 | |
| 88 | # model init |
| 89 | self.model = load_model('all', 2) |
| 90 | model_path = './final_model_csv/final_model.pth' |
| 91 | self.model = extract_model_from_pth(model_path, self.model) |
| 92 | |
| 93 | device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
| 94 | self.model = self.model.to(device) |
| 95 | |
| 96 | self.model.eval() |
| 97 | |
| 98 | def _add_new_channels_worker(self, image): |
| 99 | new_channels = [] |
no test coverage detected