Spaces:
Sleeping
Sleeping
title: ERA Session12 | |
emoji: 🔥 | |
colorFrom: green | |
colorTo: purple | |
sdk: gradio | |
sdk_version: 3.39.0 | |
app_file: app.py | |
pinned: false | |
license: mit | |
### 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. | |
## Components Used: | |
1. `gr.Dropdown` : Used for selecting the number of images for Misclassified & GradCAM output and also for the top n classes to be displayed. | |
2. `gr.Checkbox` : Used for boolean inputs like if user wants to visualize Misclassified or if they want to visualize gradCAM images. | |
3. `gr.Slider` : Used to select the opacity paramter to be used with GradCAM viaualization. | |
4. `gr.Gallery`: Used to display a numebr of images, used for displaying input images and output images. | |
5. `gr.UploadButton`: A generic file uplaod button, used for picking and uploading local image file for prediction. | |
6. `gr.Button`: Used for calling the main prediction module. | |
7. `gr.Label`: Used for displaying the top n classification results. | |
https://user-images.githubusercontent.com/23289802/258841585-4d2a75fa-3902-4839-a32a-bbfec4ef72ba.png |