Update README.md

README.md

@@ -7,6 +7,18 @@ sdk: gradio
 sdk_version: 3.39.0
 app_file: app.py
 pinned: false
+license: mit
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+### Gradio UI for CIFAR10 classification with ResNet
+
+## How to use?
+1. Select if you want visualize the misclassified images & Select the count of misclassified images.
+2. Select if you want to visualize the GradCAM images & Also select count of Gradcam images, Model layer and Opacity of the resulting image.
+3. Click on the upload button to upload the local image to be used for prediction and select the image for prediction.
+4. If you want use one of the sample images, please pick one from the list of 10 sample images.
+5. Select the top n classes for which you want see the model performance.
+6. Click on the Run button
+7. On the right side of the interface, the top view displays the selected number of misclassified images.
+8. The second view displays the GradCAM output.
+9. And Final view displays the top n predicitons for the given image.