license: mit | |
A simple single label classification model, ResNet18, to predict the cat or dog breed from the provided image. The model was created in Fast.ai | |
and exported to ONNX using PyTorch's ONNX export capabilities. | |
The source dataset is the OXFORD-IIIT PET. Omkar M Parkhi, Andrea Vedaldi, Andrew Zisserman and C. V. Jawahar | |
We have created a 37 category pet dataset with roughly 200 images for each class. | |
The images have a large variations in scale, pose and lighting. All images havean | |
associated ground truth annotation of breed, head ROI, and pixel level trimap segmentation. | |
The ONNX model can be used in other frameworks like Elixir's Axon. An example of converting the ONNX model into Axon can be found at: | |
https://github.com/elixir-nx/axon/tree/main/notebooks/onnx_to_axon.livemd. | |