Update app.py

app.py

@@ -4,8 +4,6 @@ import cv2
 import numpy as np
 from PIL import Image, ImageDraw, ImageFont
 import sqlite3
-import base64
-from io import BytesIO
 import tempfile
 import pandas as pd
 
@@ -226,40 +224,38 @@ def download_interface(choice):
     try:
         file_path = download_file(choice)
         with open(file_path, "rb") as file:
-            return file.read(), f"{choice}"
+            return file.read(), file_path
     except Exception as e:
-        return str(e)
+        return f"Error: {str(e)}", None
 
-with gr.Blocks() as demo:
-    with gr.Tabs():
-        with gr.Tab("Image Analyzer and Screener"):
-            gr.Markdown("## Cataract Detection System")
-            with gr.Row():
-                with gr.Column():
-                    input_image = gr.Image(label="Upload Image")
-                    name = gr.Textbox(label="Patient Name")
-                    patient_id = gr.Textbox(label="Patient ID")
-                    submit_btn = gr.Button("Submit")
-
-                with gr.Column():
-                    output_image = gr.Image(label="Predicted Image")
-                    raw_result = gr.Textbox(label="Raw Result")
-                    submit_status = gr.Textbox(label="Submission Status")
+# Build Gradio Interface
+app = gr.Blocks()
 
-            submit_btn.click(fn=interface, inputs=[name, patient_id, input_image], outputs=[output_image, raw_result, submit_status])
+with app:
+    gr.Markdown("# Eye Condition Detection System")
 
-        with gr.Tab("Database Viewer"):
-            view_db_btn = gr.Button("View Database")
-            database_display = gr.Dataframe()
+    with gr.Row():
+        with gr.Column():
+            name = gr.Textbox(label="Name", placeholder="Enter patient's name")
+            patient_id = gr.Textbox(label="Patient ID", placeholder="Enter patient ID")
+            input_image = gr.Image(source="upload", type="pil", label="Upload an Eye Image")
 
-            view_db_btn.click(fn=view_db_interface, outputs=database_display)
+            with gr.Row():
+                download_choice = gr.Radio(label="Download Choice", choices=["Database (.db)", "Last Predicted Image (.png)"], value="Database (.db)")
+                download_button = gr.Button("Download")
 
-        with gr.Tab("Download Results"):
-            download_choice = gr.Radio(["Database (.db)", "Predicted Image (.png)"], label="Download Option")
-            download_btn = gr.Button("Download")
+        with gr.Column():
+            predicted_image = gr.Image(label="Predicted Image")
+            raw_result = gr.Textbox(label="Raw Prediction Results", interactive=False)
+            submit_status = gr.Textbox(label="Submission Status", interactive=False)
 
-            download_output = gr.File()
+    predict_button = gr.Button("Predict")
+    view_db_button = gr.Button("View Database")
 
-            download_btn.click(fn=download_interface, inputs=download_choice, outputs=download_output)
+    # Button actions
+    predict_button.click(interface, inputs=[name, patient_id, input_image], outputs=[predicted_image, raw_result, submit_status])
+    view_db_button.click(view_db_interface, outputs=gr.Dataframe())
+    download_button.click(download_interface, inputs=[download_choice], outputs=[gr.File(), gr.Textbox()])
 
-demo.launch()
+# Launch the Gradio app
+app.launch()