PyTorch based repository for structured and modularised code for various Computer Vision models, for results/metrics, ease of use and out of the box experimentation : work in progress
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Models
dir has all CV models, custom models are undercustom.py
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Utils
dir contains utility functions and components. -
Extra resources like images or gifs would go under
resources
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Notebooks
dir will hold all Jupyter Notebooks for experiments and/or final runs for presenting results.
- 89K and 95K parameter models on Cifar10 with 85%+ validation accuracy - uses augmentation +
groups
param - 93% validation accuracy on Cifar10 with Custom ResNet model - uses augmentation + One Cycle LR