| # %BANNER_BEGIN% | |
| # --------------------------------------------------------------------- | |
| # %COPYRIGHT_BEGIN% | |
| # | |
| # Magic Leap, Inc. ("COMPANY") CONFIDENTIAL | |
| # | |
| # Unpublished Copyright (c) 2020 | |
| # Magic Leap, Inc., All Rights Reserved. | |
| # | |
| # NOTICE: All information contained herein is, and remains the property | |
| # of COMPANY. The intellectual and technical concepts contained herein | |
| # are proprietary to COMPANY and may be covered by U.S. and Foreign | |
| # Patents, patents in process, and are protected by trade secret or | |
| # copyright law. Dissemination of this information or reproduction of | |
| # this material is strictly forbidden unless prior written permission is | |
| # obtained from COMPANY. Access to the source code contained herein is | |
| # hereby forbidden to anyone except current COMPANY employees, managers | |
| # or contractors who have executed Confidentiality and Non-disclosure | |
| # agreements explicitly covering such access. | |
| # | |
| # The copyright notice above does not evidence any actual or intended | |
| # publication or disclosure of this source code, which includes | |
| # information that is confidential and/or proprietary, and is a trade | |
| # secret, of COMPANY. ANY REPRODUCTION, MODIFICATION, DISTRIBUTION, | |
| # PUBLIC PERFORMANCE, OR PUBLIC DISPLAY OF OR THROUGH USE OF THIS | |
| # SOURCE CODE WITHOUT THE EXPRESS WRITTEN CONSENT OF COMPANY IS | |
| # STRICTLY PROHIBITED, AND IN VIOLATION OF APPLICABLE LAWS AND | |
| # INTERNATIONAL TREATIES. THE RECEIPT OR POSSESSION OF THIS SOURCE | |
| # CODE AND/OR RELATED INFORMATION DOES NOT CONVEY OR IMPLY ANY RIGHTS | |
| # TO REPRODUCE, DISCLOSE OR DISTRIBUTE ITS CONTENTS, OR TO MANUFACTURE, | |
| # USE, OR SELL ANYTHING THAT IT MAY DESCRIBE, IN WHOLE OR IN PART. | |
| # | |
| # %COPYRIGHT_END% | |
| # ---------------------------------------------------------------------- | |
| # %AUTHORS_BEGIN% | |
| # | |
| # Originating Authors: Paul-Edouard Sarlin | |
| # | |
| # %AUTHORS_END% | |
| # --------------------------------------------------------------------*/ | |
| # %BANNER_END% | |
| import torch | |
| from .superpoint import SuperPoint | |
| from .superglue import SuperGlue | |
| class Matching(torch.nn.Module): | |
| """Image Matching Frontend (SuperPoint + SuperGlue)""" | |
| def __init__(self, config={}): | |
| super().__init__() | |
| self.superpoint = SuperPoint(config.get("superpoint", {})) | |
| self.superglue = SuperGlue(config.get("superglue", {})) | |
| def forward(self, data): | |
| """Run SuperPoint (optionally) and SuperGlue | |
| SuperPoint is skipped if ['keypoints0', 'keypoints1'] exist in input | |
| Args: | |
| data: dictionary with minimal keys: ['image0', 'image1'] | |
| """ | |
| pred = {} | |
| # Extract SuperPoint (keypoints, scores, descriptors) if not provided | |
| if "keypoints0" not in data: | |
| pred0 = self.superpoint({"image": data["image0"]}) | |
| pred = {**pred, **{k + "0": v for k, v in pred0.items()}} | |
| if "keypoints1" not in data: | |
| pred1 = self.superpoint({"image": data["image1"]}) | |
| pred = {**pred, **{k + "1": v for k, v in pred1.items()}} | |
| # Batch all features | |
| # We should either have i) one image per batch, or | |
| # ii) the same number of local features for all images in the batch. | |
| data = {**data, **pred} | |
| for k in data: | |
| if isinstance(data[k], (list, tuple)): | |
| data[k] = torch.stack(data[k]) | |
| # Perform the matching | |
| pred = {**pred, **self.superglue(data)} | |
| return pred | |