Update app.py

app.py

@@ -40,12 +40,8 @@ def predict_image(img):
     # Trouver les sous-catégories correspondantes
     subcategories = subcategory_dict.get(category_name, [])
 
-    # Préparer les résultats
-    results = {
-        "Category": category_name,
-        "Price ($)": f"{price_pred[0][0]:.2f}",
-        "Subcategories": ", ".join(subcategories) if subcategories else "No subcategories"
-    }
+    # Préparer les résultats sous forme de texte
+    results = f"Category: {category_name}\nPrice ($): {price_pred[0][0]:.2f}\nSubcategories: {', '.join(subcategories) if subcategories else 'No subcategories'}"
     return results
 
 # Charger le modèle pré-entraîné
@@ -56,11 +52,7 @@ model = tf.keras.models.load_model('trained_model.h5', custom_objects={'mse': Me
 interface = gr.Interface(
     fn=predict_image,
     inputs=gr.Image(type="pil"),
-    outputs=[
-        gr.Label(label="Category"),
-        gr.Text(label="Price ($)"),
-        gr.Text(label="Subcategories")
-    ],
+    outputs=gr.Textbox(label="Prediction Results"),
     title="Image Classification with TensorFlow",
     description="Upload an image to predict its category, price, and subcategories."
 )