---
title: S13
emoji: 🐨
colorFrom: indigo
colorTo: blue
sdk: gradio
sdk_version: 4.28.0
app_file: app.py
pinned: false
license: mit
---
# Pytorch LIghtning Model Trained for CIFAR10

- This application showcases the inference capabilities of a model trained on the CIFAR dataset.
-  The architecture utilized is based on Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun's work on Deep Residual Learning for Image Recognition (arXiv:1512.03385).
- It has been recreated and trained on the CIFAR10 dataset, achieving an accuracy of 85%+ within 24 epochs. The training process was accelerated using the One Cycle Policy technique. The model implementation is done using PyTorch Lightning.
- The model is coded using PyTorch Lightning 2.2.2. 

Mentioned below is the link for Training Repository [Training Repo Link](https://github.com/Shivdutta/ERA2-Session13)

- Following the training process, the model is saved locally and then uploaded to Gradio Spaces.
- Attached below is the link to [download model file](https://huggingface.co/spaces/Shivdutta/S13/blob/main/model.pth)

-  This app has two features :

  - **GradCam:** 
"   - To visualize the specific regions of the image that the model focuses on during inference
    - This insight can guide the development of augmentation strategies aimed at enhancing model accuracy"
  - **Misclassified Image:**
    - Despite achieving a test accuracy of over 85% during model training, there remained a 12% misclassification rate for certain images.
    - This feature facilitates the visualization of misclassified images alongside their correct and incorrect labels.
    - Such visualization aids in devising strategies to enhance accuracy, especially for specific classes."

## Usage:

### GradCam

  - Upload an image or choose from predefined examples.
  - Adjust the opacity.
  - Specify the number of top classes you wish to view.
  - Click the 'Submit' button to generate the results."

### Misclassified Images

  - Select the number of misclassified images you want to see
  - Click on `Display Misclassified Images` to show the images in the center and their respective correct and misclassified labels in the sequence

![GradCam and Misclassified Image](https://raw.githubusercontent.com/Shivdutta/ERA2-Session13/main/gradio-S13-1-new.png)
![GradCam and Misclassified Image](https://raw.githubusercontent.com/Shivdutta/ERA2-Session13/main/gradio-S13-2.png)
Thank you