Metadata-Version: 2.1
Name: kapture
Version: 1.0.2
Summary: kapture: file format for SfM
Home-page: https://github.com/naver/kapture/
Author: naverlabs
Author-email: kapture@naverlabs.com
License: UNKNOWN
Description: ![KAPTURE](assets/kapture_logo.svg)
        
        kapture: data format
        ====================
        
        Overview
        --------
        
        Kapture is a pivot file format, based on text and binary files, used to
        describe SfM (Structure From Motion) and more generally sensor-acquired
        data.
        
        It can be used to store sensor parameters and raw sensor data: - cameras
        - images - lidar and other sensor data
        
        As well as computed data:
        
        -   2d features
        
        -   3d reconstruction
        
        Specifications
        --------------
        
        The format specification is detailed in the [kapture format
        specifications document](kapture_format.adoc).
        
        Example File Structure
        ----------------------
        
        This is an example file structure of a dataset in the kapture format.
        
            my_dataset                 # Dataset root path
            ├─ sensors/                # Sensor data root path
            │  ├─ sensors.txt          # list of all sensors with their specifications (e.g. camera intrinsics)
            │  ├─ rigs.txt             # geometric relationship between sensors (optional)
            │  ├─ trajectories.txt     # extrinsics (timestamp, sensor, pose)
            │  ├─ records_camera.txt   # all records of type 'camera' (timestamp, sensor and path to image)
            │  ├─ records_SENSOR_TYPE.txt # all records of type SENSOR_TYPE (other sensors, eg: 'magnetic', 'pressure'...)
            │  └─ records_data/            # image and lidar data path
            │     ├─ map/cam_01/00001.jpg  # image path used in records_camera.txt (example)
            │     ├─ map/cam_01/00002.jpg
            │     ├─ map/lidar_01/0001.pcd # lidar data path used in records_lidar.txt
            │     ├─ query/query001.jpg    # image path used in records_camera.txt
            │     ├─ ...
            ├─ reconstruction/
            │  ├─ keypoints/                    # 2D keypoints files
            │  │  ├─ keypoints.txt              # type of keypoint
            │  │  ├─ map/cam_01/00001.jpg.kpt   # keypoints for corresponding image (example)
            │  │  ├─ query/query001.jpg.kpt     # keypoints for corresponding image (example)
            │  │  ├─ ...
            │  ├─ descriptors/                  # keypoint descriptors files
            │  │  ├─ descriptors.txt            # type of descriptor
            │  │  ├─ map/cam_01/00001.jpg.desc  # descriptors for corresponding image (example)
            │  │  ├─ query/query001.jpg.desc    # descriptors for corresponding image (example)
            │  │  ├─ ...
            │  ├─ ...
            │  ├─ points3d.txt                  # 3D points of the reconstruction
            │  ├─ observations.txt              # 2D/3D points corespondences
            │  ├─ matches/                      # matches files.
            │  │  ├─ map/cam_01/00001.jpg.overlapping/cam_01/00002.jpg.matches # example
            │  │  ├─ ...
        
        Software
        --------
        
        The kapture format is provided with a Python library, as well as several
        conversion tools.
        
        ### Install
        
            pip install kapture
        
        or see [installation](doc/installation.adoc) for more detailed
        instructions.
        
        ### Using docker
        
        Build the docker image:
        
            # build the docker image
            docker build . -t kapture
            # run unit tests
            docker run -it --rm kapture python3 -m unittest discover -s /opt/source/kapture/tests
        
        If you want to process your own data, you can bind directories between
        the host and the container using `--volume` or `--mount` option (See the
        [docker documentation](https://docs.docker.com/storage/bind-mounts/)).
        The following example mounts `/path/to/dataset/` from the host to
        `/dataset` inside the docker.
        
            docker run -it \
                --rm \ # Automatically remove the container when it exits \
                --volume /path/to/dataset/:/dataset:ro \ #read only
                kapture
        
        ### kapture library
        
        ### kapture tools
        
        In this repository, you will find a set of **conversion tools** to or
        from kapture format. Import results to kapture format, and conversely,
        export converts kapture data to other formats. Depending of the format,
        some data might not be converted, either because the other format does
        not support it (`—`) or because its was not implemented (`⨉`). Here is a
        table summarizing the conversion capabilities:
        
        <table style="width:100%;">
        <caption>conversion capabilities</caption>
        <colgroup>
        <col style="width: 7%" />
        <col style="width: 7%" />
        <col style="width: 7%" />
        <col style="width: 7%" />
        <col style="width: 7%" />
        <col style="width: 7%" />
        <col style="width: 7%" />
        <col style="width: 7%" />
        <col style="width: 7%" />
        <col style="width: 7%" />
        <col style="width: 7%" />
        <col style="width: 7%" />
        <col style="width: 7%" />
        </colgroup>
        <thead>
        <tr class="header">
        <th>Format</th>
        <th>← →</th>
        <th>cam</th>
        <th>rig</th>
        <th>img</th>
        <th>trj</th>
        <th>gps</th>
        <th>kpt</th>
        <th>dsc</th>
        <th>gft</th>
        <th>p3D</th>
        <th>obs</th>
        <th>mch</th>
        </tr>
        </thead>
        <tbody>
        <tr class="odd">
        <td><p>colmap</p></td>
        <td><p>import</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>⨉</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>(✓)</p></td>
        </tr>
        <tr class="even">
        <td><p>export</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>⨉</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>(✓)</p></td>
        <td></td>
        </tr>
        <tr class="odd">
        <td><p>openmvg</p></td>
        <td><p>import</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>⨉</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        </tr>
        <tr class="even">
        <td><p>export</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>⨉</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td></td>
        </tr>
        <tr class="odd">
        <td><p>OpenSfM</p></td>
        <td><p>import</p></td>
        <td><p>✓</p></td>
        <td><p>⨉</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>⨉</p></td>
        <td><p>✓</p></td>
        </tr>
        <tr class="even">
        <td><p>export</p></td>
        <td><p>✓</p></td>
        <td><p>⨉</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>⨉</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>⨉</p></td>
        <td><p>✓</p></td>
        <td></td>
        </tr>
        <tr class="odd">
        <td><p>bundler</p></td>
        <td><p>import</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        </tr>
        <tr class="even">
        <td><p>image_folder</p></td>
        <td><p>import</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        </tr>
        <tr class="odd">
        <td><p>image_list</p></td>
        <td><p>import</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        </tr>
        <tr class="even">
        <td><p>nvm</p></td>
        <td><p>import</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        </tr>
        <tr class="odd">
        <td><p>IDL_dataset_cvpr17</p></td>
        <td><p>import</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        </tr>
        <tr class="even">
        <td><p>RobotCar_Seasons</p></td>
        <td><p>import</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>?</p></td>
        <td><p>—</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>?</p></td>
        </tr>
        <tr class="odd">
        <td><p>ROSbag cameras+trajectory</p></td>
        <td><p>import</p></td>
        <td><p>(✓)</p></td>
        <td><p>(✓)</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>⨉</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        </tr>
        <tr class="even">
        <td><p>SILDa</p></td>
        <td><p>import</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        </tr>
        <tr class="odd">
        <td><p>virtual_gallery</p></td>
        <td><p>import</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>✓</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        <td><p>—</p></td>
        </tr>
        </tbody>
        </table>
        
        -   `✓`: supported, `(✓)` partially supported, `⨉`: not implemented,
            `—`: not supported by format.
        
        -   `cam`: handle camera parameters, eg. intrisics
        
        -   `rig`: handle rig structure.
        
        -   `img`: handle the path to images.
        
        -   `trj`: handle trajectories, eg. poses.
        
        -   `kpt`: handle image keypoints locations.
        
        -   `dsc`: handle image keypoints descriptors.
        
        -   `gft`: handle global image feature descriptors.
        
        -   `p3D`: handle 3D point clouds.
        
        -   `obs`: handle observations, ie. 3D-points / 2D keypoints
            correspondences.
        
        -   `mch`: handle keypoints matches.
        
        Tutorial
        --------
        
        See the [kapture tutorial](doc/tutorial.adoc) for a short introduction
        to:
        
        -   conversion tools
        
        -   dataset download
        
        -   localization pipelines
        
        Contributing
        ------------
        
        If you wish to contribute, please refer to the
        [CONTRIBUTING](CONTRIBUTING.adoc) page.
        
        License
        -------
        
        Software license is detailed in the [LICENSE](LICENSE) file.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
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