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Running
on
Zero
Running
on
Zero
| import sys | |
| from pathlib import Path | |
| from .. import MODEL_REPO_ID, logger | |
| from ..utils.base_model import BaseModel | |
| darkfeat_path = Path(__file__).parent / "../../third_party/DarkFeat" | |
| sys.path.append(str(darkfeat_path)) | |
| from darkfeat import DarkFeat as DarkFeat_ | |
| class DarkFeat(BaseModel): | |
| default_conf = { | |
| "model_name": "DarkFeat.pth", | |
| "max_keypoints": 1000, | |
| "detection_threshold": 0.5, | |
| "sub_pixel": False, | |
| } | |
| required_inputs = ["image"] | |
| def _init(self, conf): | |
| model_path = self._download_model( | |
| repo_id=MODEL_REPO_ID, | |
| filename="{}/{}".format(Path(__file__).stem, self.conf["model_name"]), | |
| ) | |
| logger.info("Loaded DarkFeat model: {}".format(model_path)) | |
| self.net = DarkFeat_(model_path) | |
| logger.info("Load DarkFeat model done.") | |
| def _forward(self, data): | |
| pred = self.net({"image": data["image"]}) | |
| keypoints = pred["keypoints"] | |
| descriptors = pred["descriptors"] | |
| scores = pred["scores"] | |
| idxs = scores.argsort()[-self.conf["max_keypoints"] or None :] | |
| keypoints = keypoints[idxs, :2] | |
| descriptors = descriptors[:, idxs] | |
| scores = scores[idxs] | |
| return { | |
| "keypoints": keypoints[None], # 1 x N x 2 | |
| "scores": scores[None], # 1 x N | |
| "descriptors": descriptors[None], # 1 x 128 x N | |
| } | |