readme update

README.md

@@ -18,11 +18,13 @@ We will try to build a custom Resnet Architecture on the CIFAR10 dataset. We wil
 
 The detailed code repo is available [here](https://github.com/mkthoma/era_v1/tree/main/Session%2012) with the original model class and the lightning module implementation. The model is pickled after training and used here to demonstrate its capability and let users make predictions and play around with it.
 
+The outputs are diplayed in two tabs - Input and Image and Misclassified Images
+
 ## Input an Image
 
 ![image](https://github.com/mkthoma/era_v1/assets/135134412/d802e9bd-88dc-4d82-aae6-297a3a823324)
 
-This tab lets users play around with the models predictions and see the results. The model supports the following classes: plane, car, bird, cat, deer, dog, frog, horse, ship, truck. Users can also select from the examples provided and see the predictions and the top classes it belongs to. GradCAM is also enabled to add model explainability for the users. Users are able to change the values for the top classes displayed for prediction, change the opacity and the layer which is used for the gradCAM. 
+This tab lets users play around with the models predictions and see the results. Users can upload images and test the model. The model supports the following classes: plane, car, bird, cat, deer, dog, frog, horse, ship, truck. Users can also select from the examples provided and see the predictions and the top classes it belongs to. GradCAM is also enabled to add model explainability for the users. Users are able to change the values for the top classes displayed for prediction, change the opacity and the layer which is used for the gradCAM. 
 
 Examples provided:
 
@@ -38,7 +40,7 @@ Sample output:
 
 ![image](https://github.com/mkthoma/era_v1/assets/135134412/52287c84-7ea0-44e2-9768-fd676905fdff)
 
-This tab lets the users to display misclassified images of the model. It lets the users select the number of images to display, whether to show the gradCAM outputs to add model explainibility, the layer used for gradCAM and the opacity for gradCAM. Based on the users selection the images are displayed. 
+This tab lets the users to display misclassified images of the model it was already trained on. It lets the users select the number of images to display, whether to show the gradCAM outputs to add model explainibility, the layer used for gradCAM and the opacity for gradCAM. Based on the users selection the images are displayed. 
 
 Sample output: