Update app.py

app.py

@@ -223,20 +223,40 @@ def interface(name, age, medical_record, sex, input_image):
     
     return f'<img src="data:image/png;base64,{img_str}" alt="Processed Image"/>', raw_result, zip_file
 
-# Define Gradio interface
-gr.Interface(
-    fn=interface,
-    inputs=[
-        gr.Textbox(label="Name"),
-        gr.Textbox(label="Age"),
-        gr.Textbox(label="Medical Record"),
-        gr.Dropdown(label="Sex", choices=["Male", "Female", "Other"]),
-        gr.Image(source="upload", tool="editor", label="Upload an Image")
-    ],
-    outputs=[
-        gr.HTML(label="Processed Image"),
-        gr.Textbox(label="Raw Predictions"),
-        gr.File(label="Download ZIP")
-    ],
-    title="Patient Image Analysis"
-).launch()
+with gr.Blocks() as demo:
+    with gr.Column():
+        gr.Markdown("# Cataract Detection System")
+        gr.Markdown("Upload an image to detect cataract and add patient details.")
+        gr.Markdown("This application uses YOLOv8 with mAP=0.981")
+    
+    with gr.Column():
+        name = gr.Textbox(label="Name")
+        age = gr.Number(label="Age")
+        medical_record = gr.Number(label="Medical Record")
+        sex = gr.Radio(["Male", "Female"], label="Sex")
+        input_image = gr.Image(type="pil", label="Upload an Image", image_mode="RGB")
+
+    with gr.Column():
+        submit_btn = gr.Button("Submit")
+        output_image = gr.Image(type="pil", label="Predicted Image")
+
+    with gr.Row():
+        raw_result = gr.Textbox(label="Prediction Result")
+    
+    with gr.Row():
+        download_html_btn = gr.Button("Download Patient Information (HTML)")
+        download_uploaded_btn = gr.Button("Download Uploaded Images")
+        download_predicted_btn = gr.Button("Download Predicted Images")
+    
+    # Add file download output components for the uploaded and predicted images
+    patient_info_file = gr.File(label="Patient Information HTML File")
+    uploaded_folder_file = gr.File(label="Uploaded Images Zip File")
+    predicted_folder_file = gr.File(label="Predicted Images Zip File")
+
+    submit_btn.click(fn=interface, inputs=[name, age, medical_record, sex, input_image], outputs=[output_image, raw_result])
+    download_html_btn.click(fn=save_patient_info_to_html, inputs=[name, age, medical_record, sex, raw_result], outputs=patient_info_file)
+    download_uploaded_btn.click(fn=download_uploaded_folder, outputs=uploaded_folder_file)
+    download_predicted_btn.click(fn=download_predicted_folder, outputs=predicted_folder_file)
+
+# Launch Gradio app
+demo.launch()