Basic tutorial #113
Basic tutorial #113
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| source activate py35 | ||
| cmake -DPYTHON_EXECUTABLE:FILEPATH=<path-to-anaconda>/envs/py35/bin/python3.5 ../src | ||
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| This example uses Python 3.5, but you can choose 2.7 or other. |
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Why use a new conda environment?
I don't think we need it.
Some users may have installed conda3 already, so there is no point in adding a new environment.
Also, I think the latest python in conda is 3.6.
| Python binding | ||
| ================= | ||
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| We highly recommend this option as it gives easy interface to users. Open3D tutorial is written for Python binding. |
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Remove this line. It should not be placed here.
| Tutorial | ||
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| This is a quick Python tutorial to be familiar with the library. |
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Open3D has two interfaces: C++, and Python. This tutorial focuses on the Python interface since it is easy to use and should be regarded as the primary interface of Open3D.
--Note--
For C++ interfaces, refer to examples in [Test] and [Tools] folder.
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| .. _tutorial: | |||
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This should be separate files. Each tutorial file has its own document page.
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| Let's get started Open3D by importing Python module. | ||
| Once you successfully compiled Open3D with Python binding option, | ||
| py3d.so should be visible under Open3D build folder. Let's import it. |
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py3d.so (or py3d.pyd if you are using Windows) should be compiled under the build/lib folder. All [Python/Tutorials] files will be also copied to [build/lib]. You can call them in place and see results. Listed below:
- Basic
- basic1
- basic2
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| draw_geometries([pcd]) | ||
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| Note that ``draw_geometries`` can visualize multiple geometries by taking a list of objects. | ||
| We will see more examples of this function later. |
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Change this to:
The code is straightforward. First import the Open3D library (named py3d). Then call function read_point_cloud to read a point cloud from a file. This function detects the extension name of the file and tries its best to decode the file into a point cloud. Current supported extension names include: pcd, ply, xyz, xyzrgb, xyzn, pts.
The data structure of the point cloud is:
Pointcloud
-- points: (numpy array with xxxx)
-- colors: (xxxx, can be empty)
-- normals: (xxxx, xxxxx)
More tutorials will show how to manipulate these data records. In this tutorial we just focus on the rendering task. Thus, we finally call draw_geometries functions...
This functions does....
Show a figure.
Explain the GUI a bit. There are actually lots of stuff to explain, e.g., you can press +- to change the point size, etc.
| draw_geometries([mesh]) | ||
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| Here, method ``compute_vertex_normals`` computes point normal of meshed surface. | ||
| ``draw_geometries`` will draw shaded geometry based on the computed normal direction. |
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separate file.
there are also some special things for meshes to explain.
e.g. b to enable back face rendering. There are different render mode (phong, etc).
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| vol = read_selection_polygon_volume("../TestData/Crop/cropped.json") | ||
| chair = vol.crop_point_cloud(pcd) | ||
| draw_geometries([chair]) |
| Read RGBD Image | ||
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| Open3D provides a variety of 3D reconstruction algorithms using depth cameras. | ||
| A pair of color and depth image is a input for the reconstruction pipeline. |
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separate file and detailed explanation.
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| # Open3D: www.open3d.org | |||
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I am actually not a big fan of my code in test_py3d file.
They look very messy and ugly. Not tutorial quality code.
If you want to explain the internal structure of an image, you can do it in read_rgbd_image tutorial. Maybe add a few Jupyter notebook cells to show how they are accessed via numpy array.
But definitely not something like this. I can't even read it.
Moving 'test' examples to basic tutorial examples.
Working on tutorial documents.
Please merge #112 first.