tensorflow / tensorflow/graphics
Adding preprocessing functions for pointclouds
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- Python
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Description
Hello,
I have implemented various preprocessing functions in tensorflow, compatible with tf.data.Dataset API for augmenting pointclouds including jitter, random_cutout, random_translation, random_rotation, random_zoom, etc..
I was curious to know if they would fall in the scope of tfg so I could submit a PR.
These could be implemented as augmentation layers just like keras-cv augmentations. I am not sure if these fall into the scope of tfg or keras-cv
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Research direction
The issue proposes point-cloud preprocessing functions such as jitter, random cutout, translation, rotation, and zoom, but names no files or tests. First clarify whether these augmentations belong in TensorFlow Graphics or Keras-CV and define the accepted scope. Done means an agreed implementation scope and contribution path.
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Assessment
- Tech stack
- python
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100