Update app.py

app.py

@@ -57,4 +57,29 @@ with gr.Blocks() as demo:
     with gr.Row():
         iou_threshold = gr.Slider(label="NMS IoU Threshold (0.0 - 1.0)", minimum=0.0, maximum=1.0, value=0.8)
         conf_threshold = gr.Slider(label="Umbral o threshold (0.0 - 1.0)", minimum=0.0, maximum=1.0, value=0.9)
-        size = gr.Dropdown(label="Tamaño de la
+        size = gr.Dropdown(label="Tamaño de la imagen", choices=["640", "1280"], value="1280")
+
+    uploaded_image = gr.Image(source="upload", type="pil", label="Cargar imagen")
+
+    result_image = gr.Image(label="Resultado")
+    objects_table = gr.DataFrame(label="Objetos detectados")
+
+    detect_btn = gr.Button("Detectar objetos")
+    feedback = gr.Textbox(label="Ingrese su feedback (máximo 100 caracteres)", max_lines=1)
+    user_text = gr.Textbox(label="Ingrese el nombre del usuario (máximo 50 caracteres)", max_lines=1)
+    check_status = gr.Checkbox(label="¿El resultado contiene la cantidad correcta de figuras detectadas?", value=False)
+    save_btn = gr.Button("Guardar feedback")
+    output_message = gr.Textbox(label="Mensaje de salida", interactive=False)
+
+    detect_btn.click(fn=detect_objects, 
+                     inputs=[uploaded_image, size, iou_threshold, conf_threshold], 
+                     outputs=[result_image, objects_table])
+
+    save_btn.click(fn=save_feedback, 
+                   inputs=[size, iou_threshold, conf_threshold, 
+                           objects_table, user_text, feedback, check_status], 
+                   outputs=[output_message])
+
+# Ejecuta la interfaz de Gradio
+if __name__ == "__main__":
+    demo.launch()