Create a series of training and inference tutorials exploring Kornia API with up-to-date real cases open source:
- using hugging faces datasets library and datasets available on hugging faces hub
- using torchmetrics and/or evaluation for model evaluation
- using kornia x, lighting trainer, or other api with accelerate integration for training
- using kornia for data augmentation, exploring augmentation sequential api
- using timm for encoders
Exploring image classification, semantic segmentation, and object detection. Showing how to export and/or compile the pipelines for better performance
My goal here, aside from providing tutorials for the community, is to explore and identify inconsistencies between other libraries and Kornia. We can use these tutorials to explore improvements for kornia to be easier to use along other ML libraries.
Tracker list:
Each tutorial will need to be skipped run on CI or be able to just use some samples. Open to discussion to what other libraries of the ecosystem we should have examples on tutorials
Create a series of training and inference tutorials exploring Kornia API with up-to-date real cases open source:
Exploring image classification, semantic segmentation, and object detection. Showing how to export and/or compile the pipelines for better performance
My goal here, aside from providing tutorials for the community, is to explore and identify inconsistencies between other libraries and Kornia. We can use these tutorials to explore improvements for kornia to be easier to use along other ML libraries.
Tracker list:
training
- [ ] image classification
- [ ] semantic segmentation
- [ ] object detection
inference
- [ ] image classification
- [ ] semantic segmentation
- [ ] object detection
Each tutorial will need to be skipped run on CI or be able to just use some samples. Open to discussion to what other libraries of the ecosystem we should have examples on tutorials