Update app.py

app.py

@@ -57,9 +57,12 @@ for model in models:
 
 def inference(images, min_score, model_name):
     results = []
-    for image in images:    
-
-        im = cv2.imread(image)
+    for image in images:
+        # Si la imagen es de tipo PIL, conviértela a NumPy
+        if isinstance(image, np.ndarray):
+            im = image[:, :, ::-1]  # Convertir de RGB a BGR
+        else:
+            im = np.array(image)[:, :, ::-1]  # Si es PIL, convertir a NumPy y cambiar a BGR
 
         model_id = model_name_to_id[model_name]
 
@@ -88,7 +91,7 @@ with gr.Blocks() as demo:
     gr.Markdown(description)
     
     with gr.Tab("From Image"):
-        image_input = gr.Gallery(label="Input Images", type="numpy")
+        image_input = gr.Image(type="numpy", label="Input Image")
 
     min_score = gr.Slider(minimum=0.0, maximum=1.0, value=0.5, label="Minimum score")