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76 lines
2.3 KiB
Markdown
76 lines
2.3 KiB
Markdown
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Point cloud visualisation {#tutorial_point_cloud}
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==============================
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| Original author | Dmitrii Klepikov |
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| Compatibility | OpenCV >= 5.0 |
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Goal
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----
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In this tutorial you will:
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- Load and save point cloud data
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- Visualise your data
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Requirements
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------------
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For visualisations you need to compile OpenCV library with OpenGL support.
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For this you should set WITH_OPENGL flag ON in CMake while building OpenCV from source.
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Practice
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-------
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Loading and saving of point cloud can be done using `cv::loadPointCloud` and `cv::savePointCloud` accordingly.
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Currently supported formats are:
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- [.OBJ](https://en.wikipedia.org/wiki/Wavefront_.obj_file) (supported keys are v(which is responsible for point position), vn(normal coordinates) and f(faces of a mesh), other keys are ignored)
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- [.PLY](https://en.wikipedia.org/wiki/PLY_(file_format)) (all encoding types(ascii and byte) are supported with limitation to only float type for data)
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@code{.py}
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vertices, normals = cv2.loadPointCloud("teapot.obj")
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@endcode
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Function `cv::loadPointCloud` returns vector of points of float (`cv::Point3f`) and vector of their normals(if specified in source file).
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To visualize it you can use functions from viz3d module and it is needed to reinterpret data into another format
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@code{.py}
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vertices = np.squeeze(vertices, axis=1)
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color = [1.0, 1.0, 0.0]
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colors = np.tile(color, (vertices.shape[0], 1))
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obj_pts = np.concatenate((vertices, colors), axis=1).astype(np.float32)
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cv2.viz3d.showPoints("Window", "Points", obj_pts)
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cv2.waitKey(0)
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@endcode
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In presented code sample we add a colour attribute to every point
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Result will be:
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For additional info grid can be added
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@code{.py}
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vertices, normals = cv2.loadPointCloud("teapot.obj")
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@endcode
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Other possible way to draw 3d objects can be a mesh.
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For that we use special functions to load mesh data and display it.
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Here for now only .OBJ files are supported and they should be triangulated before processing (triangulation - process of breaking faces into triangles).
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@code{.py}
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vertices, _, indices = cv2.loadMesh("../data/teapot.obj")
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vertices = np.squeeze(vertices, axis=1)
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cv2.viz3d.showMesh("window", "mesh", vertices, indices)
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@endcode
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