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README.md
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@@ -14,12 +14,10 @@ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-
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# CIFAR10 Image classification using a Custom ResNet Model
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## What is the app about?
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[This app](https://huggingface.co/spaces/nviraj/ERA-V1-Assignment12) built using [Gradio](https://www.gradio.app/) provides an interface to run inferences for CIFAR10 image classification using a custom ResNet model trained using PyTorch and Lightning with \>90% accuracy.
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### What input does it require?
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- **Example Input**
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- Do you want to see GradCAM for Misclassified Images and how many?
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- This is useful to see what parts of the image led to incorrect classification
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### What is the output?
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- Predictions for top number of classes chosen as well as the predicted class
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- Misclassified Images by the model
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- GradCAM for Misclassified Images by the model
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### How was the model built?
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- Model was trained using a custom ResNet model trained for just 24 epochs with 91.4% validation accuracy
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- [Modules](https://github.com/nviraj/era-v1/tree/main/Session%2012/Submission/modules)
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- [Model](https://github.com/nviraj/era-v1/tree/main/Session%2012/Submission/models)
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### Links
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- [GradCAM?](https://arxiv.org/abs/1610.02391)
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# CIFAR10 Image classification using a Custom ResNet Model
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## What is the app about?
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[This app](https://huggingface.co/spaces/nviraj/ERA-V1-Assignment12) built using [Gradio](https://www.gradio.app/) provides an interface to run inferences for CIFAR10 image classification using a custom ResNet model trained using PyTorch and Lightning with \>90% accuracy.
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### What input does it require?
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- **Example Input**
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- Do you want to see GradCAM for Misclassified Images and how many?
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- This is useful to see what parts of the image led to incorrect classification
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### What is the output?
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- Predictions for top number of classes chosen as well as the predicted class
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- Misclassified Images by the model
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- GradCAM for Misclassified Images by the model
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### How was the model built?
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- Model was trained using a custom ResNet model trained for just 24 epochs with 91.4% validation accuracy
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- [Modules](https://github.com/nviraj/era-v1/tree/main/Session%2012/Submission/modules)
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- [Model](https://github.com/nviraj/era-v1/tree/main/Session%2012/Submission/models)
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### Links
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- [GradCAM?](https://arxiv.org/abs/1610.02391)
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