Update README.md

README.md

@@ -10,16 +10,39 @@ pinned: false
 license: mit
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-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# CustomResNet with GradCAM - Interactive Interface
+    
+### Implimented a simple Gradio interface to infer on CustomResNet model and get GradCAM results
 
--> We trained CIFAR10 dataset using Custom ResNet model by using pytorch lightning. 
+## Task : 
+
+Classification on CIFAR10 dataset using Custom ResNet model by using pytorch lightning. 
+
+## Files :
 
 -> requirements.txt file contains necessary packages to install.
 
 -> custom_resnet.py file contains model architecture.
 
--> model_pth.ckpt contains trained model checkpoints (weights).
+-> CustomResNet.pth contains trained model checkpoints (weights).
+
+-> examples folder : 10 example images like cat.jpg, car.jpg,..
+
+--> app.py contains gradio code. By using gradio here implemented by selecting input images or examples output display the gradcam image and prediction and top k classes. 
+
+--> misclassified_images folder :  10 misclassified images 
+
+## Implimentation : 
+
+First loaded the model by using model weights .pth file.
+
+### By using GRADIO we created these features :
+
+-> Asking the user they want to see GradCAM images if yes then how many images, from which layer and also allow opacity change.
+
+-> Providing the option to user they want to view misclassified images, and how many images. If they want to apply grad cam for misclassified images.
+
+--> Option to upload new images, as well as select from 10 example images.
 
--> 10 example images like cat_1.jpg, cat_2.jpg,..
+--> Providing one more option how many top classes they want to see.
 
---> app.py contains gradio code. By using gradio here implemented by selecting input images or examples output display the gradcam image and prediction and top k classes. I tried with multiple gradcam and misclassified i am getting errors.