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Creating Ambient occlusion render of point clouds (elevation maps) using "Portion de Ciel Visible" (PCV) algorithm + Pyside GUI

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SimplePCV

Creating an ambient occlusion render of point clouds (elevation maps, DSM or DTM) using "Portion de Ciel Visible" (PCV) algorithm. A small PySide6 GUI allows to play with the colormap range (using matplotlib 'Greys' by default).

COMING SOON:

  • Importing the point cloud and genarating the Tif raster file within the tool

Introduction

Making convincing ambient occlusion renders from elevation maps (terrains or construction sites, for example) can be useful for better point cloud segmentation. Using CloudCompare can be overkill for such a task. This is an implementation based on Duguet, Florent & Girardeau-Montaut, Daniel. (2004). Rendu en Portion de Ciel Visible de Gros Nuages de Points 3D.

NOTE: creating the input dtm tif can be done with CloudCompare or any point cloud rasterization tools.

#Pillow #Open3D #Voxels #ImageProcessing #Pointcloud

Use

Install all requirements, then simply run main.py (Do not forget to change the image path). One test image is provided

input

Capture-d-cran-2023-10-09-122414

Simple PCV (ambient occlusion)

Installation instructions

  1. Clone the repository:
git clone https://github.com/s-du/SimplePCV
  1. Navigate to the app directory:
cd SimplePCV
  1. Install the required dependencies:
pip install -r requirements.txt
  1. (optional) Modify main.py --> replace image path

  2. Run the app:

python main.py

Contributing

Contributions to the app are welcome! If you find any bugs, have suggestions for new features, or would like to contribute enhancements, please follow these steps:

  1. Fork the repository.
  2. Create a new branch for your feature or bug fix.
  3. Make the necessary changes and commit them.
  4. Push your changes to your fork.
  5. Submit a pull request describing your changes.

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Creating Ambient occlusion render of point clouds (elevation maps) using "Portion de Ciel Visible" (PCV) algorithm + Pyside GUI

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