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| import sys | |
| from pathlib import Path | |
| import torch | |
| from .. import MODEL_REPO_ID, logger | |
| from ..utils.base_model import BaseModel | |
| gluestick_path = Path(__file__).parent / "../../third_party/GlueStick" | |
| sys.path.append(str(gluestick_path)) | |
| from gluestick import batch_to_np | |
| from gluestick.models.two_view_pipeline import TwoViewPipeline | |
| class GlueStick(BaseModel): | |
| default_conf = { | |
| "name": "two_view_pipeline", | |
| "model_name": "checkpoint_GlueStick_MD.tar", | |
| "use_lines": True, | |
| "max_keypoints": 1000, | |
| "max_lines": 300, | |
| "force_num_keypoints": False, | |
| } | |
| required_inputs = [ | |
| "image0", | |
| "image1", | |
| ] | |
| # Initialize the line matcher | |
| def _init(self, conf): | |
| # Download the model. | |
| model_path = self._download_model( | |
| repo_id=MODEL_REPO_ID, | |
| filename="{}/{}".format( | |
| Path(__file__).stem, self.conf["model_name"] | |
| ), | |
| ) | |
| logger.info("Loading GlueStick model...") | |
| gluestick_conf = { | |
| "name": "two_view_pipeline", | |
| "use_lines": True, | |
| "extractor": { | |
| "name": "wireframe", | |
| "sp_params": { | |
| "force_num_keypoints": False, | |
| "max_num_keypoints": 1000, | |
| }, | |
| "wireframe_params": { | |
| "merge_points": True, | |
| "merge_line_endpoints": True, | |
| }, | |
| "max_n_lines": 300, | |
| }, | |
| "matcher": { | |
| "name": "gluestick", | |
| "weights": str(model_path), | |
| "trainable": False, | |
| }, | |
| "ground_truth": { | |
| "from_pose_depth": False, | |
| }, | |
| } | |
| gluestick_conf["extractor"]["sp_params"]["max_num_keypoints"] = conf[ | |
| "max_keypoints" | |
| ] | |
| gluestick_conf["extractor"]["sp_params"]["force_num_keypoints"] = conf[ | |
| "force_num_keypoints" | |
| ] | |
| gluestick_conf["extractor"]["max_n_lines"] = conf["max_lines"] | |
| self.net = TwoViewPipeline(gluestick_conf) | |
| def _forward(self, data): | |
| pred = self.net(data) | |
| pred = batch_to_np(pred) | |
| kp0, kp1 = pred["keypoints0"], pred["keypoints1"] | |
| m0 = pred["matches0"] | |
| line_seg0, line_seg1 = pred["lines0"], pred["lines1"] | |
| line_matches = pred["line_matches0"] | |
| valid_matches = m0 != -1 | |
| match_indices = m0[valid_matches] | |
| matched_kps0 = kp0[valid_matches] | |
| matched_kps1 = kp1[match_indices] | |
| valid_matches = line_matches != -1 | |
| match_indices = line_matches[valid_matches] | |
| matched_lines0 = line_seg0[valid_matches] | |
| matched_lines1 = line_seg1[match_indices] | |
| pred["raw_lines0"], pred["raw_lines1"] = line_seg0, line_seg1 | |
| pred["lines0"], pred["lines1"] = matched_lines0, matched_lines1 | |
| pred["keypoints0"], pred["keypoints1"] = torch.from_numpy( | |
| matched_kps0 | |
| ), torch.from_numpy(matched_kps1) | |
| pred = {**pred, **data} | |
| return pred | |