Back to Avoid Runtime Erorr

app.py

@@ -134,70 +134,71 @@ if __name__ == "__main__":
     with gr.Blocks() as demo:
         gr.Markdown("# Saliency Maps with the MERIT Dataset 🎒📃🏆")
 
-        with gr.Column(scale=2, min_width=600):
-            gr.Image(value=README_IMAGE_PATH, height=400, fit="scale-down")
-
-            with gr.Tabs():
-                with gr.Tab("Introduction"):
-                    gr.Markdown(
-                        """
-                    ## Welcome to Saliency Maps with the [MERIT Dataset](https://huggingface.co/datasets/de-Rodrigo/merit) 🎒📃🏆
-
-                    This space demonstrates the capabilities of different Vision Language models 
-                    for document understanding tasks.
-
-                    ### Key Features:
-                    - Process images from the [MERIT Dataset](https://huggingface.co/datasets/de-Rodrigo/merit) or upload your own image.
-                    - Use a fine-tuned version of the models availabe to extract grades from documents.
-                    - Visualize saliency maps to understand where the model is looking (WIP 🛠️).
-                    """
-                    )
+        gr.Image(value=README_IMAGE_PATH, width=800, height=600)
 
-                with gr.Tab("Try It Yourself"):
-                    gr.Markdown(
-                        "Select a model and an image from the dataset, or upload your own image."
-                    )
+        with gr.Tab("Introduction"):
+            gr.Markdown(
+                """
+            ## Welcome to Saliency Maps with the [MERIT Dataset](https://huggingface.co/datasets/de-Rodrigo/merit) 🎒📃🏆
 
-                    with gr.Row():
-                        with gr.Column():
-                            model_dropdown = gr.Dropdown(
-                                choices=models, label="Select Model"
-                            )
-                            dataset_slider = gr.Slider(
-                                minimum=0,
-                                maximum=len(dataset) - 1,
-                                step=1,
-                                label="Dataset Image Index",
-                            )
-                            upload_image = gr.Image(
-                                type="pil", label="Or Upload Your Own Image"
-                            )
-
-                        preview_image = gr.Image(label="Selected/Uploaded Image")
-
-                    process_button = gr.Button("Process Image")
-
-                    with gr.Row():
-                        output_image = gr.Image(label="Processed Image")
-                        output_text = gr.Textbox(label="Result")
-
-                    # Update preview image when slider changes
-                    dataset_slider.change(
-                        fn=update_image,
-                        inputs=[dataset_slider],
-                        outputs=[preview_image],
-                    )
+            This space demonstrates the capabilities of different Vision Language models 
+            for document understanding tasks.
 
-                    # Update preview image when an image is uploaded
-                    upload_image.change(
-                        fn=lambda x: x, inputs=[upload_image], outputs=[preview_image]
-                    )
+            ### Key Features:
+            - Process images from the [MERIT Dataset](https://huggingface.co/datasets/de-Rodrigo/merit) or upload your own image.
+            - Use a fine-tuned version of the models availabe to extract grades from documents.
+            - Visualize saliency maps to understand where the model is looking (WIP 🛠️).
+            """
+            )
 
-                    # Process image when button is clicked
-                    process_button.click(
-                        fn=process_image,
-                        inputs=[model_dropdown, upload_image, dataset_slider],
-                        outputs=[output_image, output_text],
+            # gr.Image(
+            #     value=GIF_PATH,
+            #     label="Dataset samples you can process",
+            #     width=800,
+            #     height=600,
+            # )
+
+        with gr.Tab("Try It Yourself"):
+            gr.Markdown(
+                "Select a model and an image from the dataset, or upload your own image."
+            )
+
+            with gr.Row():
+                with gr.Column():
+                    model_dropdown = gr.Dropdown(choices=models, label="Select Model")
+                    dataset_slider = gr.Slider(
+                        minimum=0,
+                        maximum=len(dataset) - 1,
+                        step=1,
+                        label="Dataset Image Index",
+                    )
+                    upload_image = gr.Image(
+                        type="pil", label="Or Upload Your Own Image"
                     )
 
+                preview_image = gr.Image(label="Selected/Uploaded Image")
+
+            process_button = gr.Button("Process Image")
+
+            with gr.Row():
+                output_image = gr.Image(label="Processed Image")
+                output_text = gr.Textbox(label="Result")
+
+            # Update preview image when slider changes
+            dataset_slider.change(
+                fn=update_image, inputs=[dataset_slider], outputs=[preview_image]
+            )
+
+            # Update preview image when an image is uploaded
+            upload_image.change(
+                fn=lambda x: x, inputs=[upload_image], outputs=[preview_image]
+            )
+
+            # Process image when button is clicked
+            process_button.click(
+                fn=process_image,
+                inputs=[model_dropdown, upload_image, dataset_slider],
+                outputs=[output_image, output_text],
+            )
+
     demo.launch()