Update app.py

app.py

@@ -29,11 +29,17 @@ def predict(images, eps):
     grid_zca = make_grid(zca_images, nrow=3, normalize=True).cpu().numpy()
     return np.transpose(grid_zca, [1, 2, 0])
 
+def load_example_images(example_images):
+    return example_images
+
 title = 'ZCA Whitening with Kornia!'
 description = '''[ZCA Whitening](https://paperswithcode.com/method/zca-whitening) is an image preprocessing method that leads to a transformation of data such that the covariance matrix is the identity matrix, leading to decorrelated features:
 *Note that you can upload only image files, e.g. jpg, png etc and there should be at least 2 images!* 
 Learn more about [ZCA Whitening and Kornia](https://kornia.readthedocs.io/en/latest/enhance.zca.html)'''
 
+example_images = ['irises.jpg', 'roses.jpg', 'sunflower.jpg', 'violets.jpg', 'chamomile.jpg', 
+                  'tulips.jpg', 'Alstroemeria.jpg', 'Carnation.jpg', 'Orchid.jpg', 'Peony.jpg']
+
 with gr.Blocks(title=title) as demo:
     gr.Markdown(f"# {title}")
     gr.Markdown(description)
@@ -47,16 +53,10 @@ with gr.Blocks(title=title) as demo:
     submit_button = gr.Button("Apply ZCA Whitening")
     submit_button.click(fn=predict, inputs=[input_images, eps_slider], outputs=output_image)
     
-    gr.Examples(
-        examples=[
-            [
-                ['irises.jpg', 'roses.jpg', 'sunflower.jpg', 'violets.jpg', 'chamomile.jpg', 
-                 'tulips.jpg', 'Alstroemeria.jpg', 'Carnation.jpg', 'Orchid.jpg', 'Peony.jpg'],
-                0.01
-            ]
-        ],
-        inputs=[input_images, eps_slider],
-    )
+    gr.Markdown("## Example Images")
+    example_gallery = gr.Gallery(value=example_images, label="Example Images", columns=5, height="auto")
+    load_examples_button = gr.Button("Load Example Images")
+    load_examples_button.click(fn=load_example_images, inputs=[example_gallery], outputs=[input_images])
 
 if __name__ == "__main__":
     demo.launch(show_error=True)