wehub-resource-sync
99 lines
4.4 KiB
Markdown
99 lines
4.4 KiB
Markdown
<!--[metadata]
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title = "Open photogrammetry format"
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tags = ["2D", "3D", "Camera", "Photogrammetry"]
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thumbnail = "https://static.rerun.io/open-photogrammetry-format/c9bec43a3a3abd725a55ee8eb527a4c0cb01979b/480w.png"
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thumbnail_dimensions = [480, 480]
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channel = "release"
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include_in_manifest = true
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build_args = ["--jpeg-quality=50"]
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-->
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Uses [`pyopf`](https://github.com/Pix4D/pyopf) to load and display a photogrammetrically reconstructed 3D point cloud in the [Open Photogrammetry Format (OPF)](https://www.pix4d.com/open-photogrammetry-format/).
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<picture data-inline-viewer="examples/open_photogrammetry_format">
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<source media="(max-width: 480px)" srcset="https://static.rerun.io/open_photogrammetry_format/603d5605f9670889bc8bce3365f16b831fce1eb1/480w.png">
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<source media="(max-width: 768px)" srcset="https://static.rerun.io/open_photogrammetry_format/603d5605f9670889bc8bce3365f16b831fce1eb1/768w.png">
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<source media="(max-width: 1024px)" srcset="https://static.rerun.io/open_photogrammetry_format/603d5605f9670889bc8bce3365f16b831fce1eb1/1024w.png">
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<source media="(max-width: 1200px)" srcset="https://static.rerun.io/open_photogrammetry_format/603d5605f9670889bc8bce3365f16b831fce1eb1/1200w.png">
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<img src="https://static.rerun.io/open_photogrammetry_format/603d5605f9670889bc8bce3365f16b831fce1eb1/full.png" alt="">
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</picture>
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## Used Rerun types
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[`Image`](https://www.rerun.io/docs/reference/types/archetypes/image), [`Points3D`](https://www.rerun.io/docs/reference/types/archetypes/points3d), [`Transform3D`](https://www.rerun.io/docs/reference/types/archetypes/transform3d), [`Pinhole`](https://www.rerun.io/docs/reference/types/archetypes/pinhole)
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## Background
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This example loads an Open Photogrammetry Format (OPF) project and displays the cameras and point cloud data.
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OPF, which stands for 'open photogrammetry format,' is a file format used for photogrammetry data.
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It contains all the necessary information related to a reconstructed 3D model made with photogrammetry, including calibration, point clouds and dense reconstruction.
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## Logging and visualizing with Rerun
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The visualizations in this example were created with the following Rerun code:
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### Timelines
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For each processed frame, all data sent to Rerun is associated with specific time using [`timelines`](https://www.rerun.io/docs/concepts/logging-and-ingestion/timelines).
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```python
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rr.set_time("image", sequence=i)
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```
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### Video
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Pinhole camera is utilized for achieving a 3D view and camera perspective through the use of the [`Pinhole`](https://www.rerun.io/docs/reference/types/archetypes/pinhole) and [`Transform3D`](https://www.rerun.io/docs/reference/types/archetypes/transform3d) archetypes.
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```python
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rr.log("world/cameras", rr.Transform3D(translation=calib_camera.position, mat3x3=rot))
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```
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```python
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rr.log(
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"world/cameras/image",
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rr.Pinhole(
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resolution=sensor.image_size_px,
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focal_length=calib_sensor.internals.focal_length_px,
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principal_point=calib_sensor.internals.principal_point_px,
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camera_xyz=rr.ViewCoordinates.RUB,
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),
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)
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```
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The input video is logged as a sequence of [`Image`](https://www.rerun.io/docs/reference/types/archetypes/image) objects to the `world/cameras/image/rgb` entity.
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```python
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rr.log("world/cameras/image/rgb", rr.Image(np.array(img)).compress(jpeg_quality=jpeg_quality))
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```
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### Point clouds
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Point clouds from the project are logged as [`Points3D`](https://www.rerun.io/docs/reference/types/archetypes/points3d) archetype to the `world/points` entity.
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```python
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rr.log("world/points", rr.Points3D(points.position, colors=points.color), static=True)
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```
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## Run the code
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> This example requires Python 3.10 or higher because of [`pyopf`](https://pypi.org/project/pyopf/).
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To run this example, make sure you have the Rerun repository checked out and the latest SDK installed:
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```bash
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pip install --upgrade rerun-sdk # install the latest Rerun SDK
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git clone git@github.com:rerun-io/rerun.git # Clone the repository
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cd rerun
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git checkout latest # Check out the commit matching the latest SDK release
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```
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Install the necessary libraries specified in the requirements file:
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```bash
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pip install -e examples/python/open_photogrammetry_format
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```
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To experiment with the provided example, simply execute the main Python script:
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```bash
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python -m open_photogrammetry_format # run the example
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```
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If you wish to customize it or explore additional features, use the CLI with the `--help` option for guidance:
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```bash
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python -m open_photogrammetry_format --help
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```
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