Test with augmentations. Only rescale=True is supported.
(self, imgs, img_metas, rescale=True)
| 289 | return seg_pred |
| 290 | |
| 291 | def aug_test(self, imgs, img_metas, rescale=True): |
| 292 | """Test with augmentations. |
| 293 | |
| 294 | Only rescale=True is supported. |
| 295 | """ |
| 296 | # aug_test rescale all imgs back to ori_shape for now |
| 297 | assert rescale |
| 298 | # to save memory, we get augmented seg logit inplace |
| 299 | seg_logit = self.inference(imgs[0], img_metas[0], rescale) |
| 300 | for i in range(1, len(imgs)): |
| 301 | cur_seg_logit = self.inference(imgs[i], img_metas[i], rescale) |
| 302 | seg_logit += cur_seg_logit |
| 303 | seg_logit /= len(imgs) |
| 304 | seg_pred = seg_logit.argmax(dim=1) |
| 305 | seg_pred = seg_pred.cpu().numpy() |
| 306 | # unravel batch dim |
| 307 | seg_pred = list(seg_pred) |
| 308 | return seg_pred |