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Blender Data Generation

The main objective of this project is to provide an abstraction layer over Blender API in order to have a set of tools for an easy generation of labeled synthetic data.

Using it

In this repository an example for a basic generation is provided in "tinker.py". The blender project "YOLO_data_generator.blend" includes in the scripting section the script already opened.

You have to provide absolute path for:

  • "dataset_path": where the dataset is located
  • "render_img_saving_path": where we save our results

With EPOCHS we specify the number of images we want to generate

Roadmap

TODO:

  • Render labeled image masks
  • Option to make images look at the camera
  • Option/params to scale images/+- scaling randomly (Class already done, needs to integrate)
  • Make images "stand" on the floor as a parameter (Done by default)
  • Add background simple
  • Add 3D objects and handle them with DataHandler
  • Scene rendering class
  • Enable GPU by code
  • Refactor code

FIX:

  • Sometimes image planes are not deleted properly (probably related with class DataHandler with delete_images_planes())

Acknowledgments

  • Federico Arenas López: For providing a good base project and functions for defining bounding boxes and rendering.