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Cats_v_Dogs.ONNX
ScottMueller/Cats_v_Dogs.ONNX
Cats_v_Dogs.ONNX is a machine learning model from ScottMueller. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
A simple single label classification model, ResNet18, to predict whether the provided image is a cat or a dog. The model was created in Fast.ai and exported to ONNX using PyTorch's ONNX export capabilities.
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Updated Aug 8, 2022
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At a glance
- License
- mit
- Access
- Public
- Created
- Aug 8, 2022
- Updated
- Aug 8, 2022
- SHA
- 87add5cc
Model card
From the Hugging Face model README
A simple single label classification model, ResNet18, to predict whether the provided image is a cat or a dog. 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.
- License
- mit
- Created
- Aug 8, 2022
- Updated
- Aug 8, 2022