Update app.py

app.py

@@ -42,10 +42,8 @@ model = load_model()
 labels = load_labels()
 
 #image: PIL.Image.Image
-def predict(url: str, score_threshold: float) -> tuple[dict[str, float], dict[str, float], str]:
+def predict(image: PIL.Image.Image, score_threshold: float) -> tuple[dict[str, float], dict[str, float], str]:
     _, height, width, _ = model.input_shape
-    response = requests.get(url)
-    image = PIL.Image.open(BytesIO(response.content))
     image = np.asarray(image)
     image = tf.image.resize(image, size=(height, width), method=tf.image.ResizeMethod.AREA, preserve_aspect_ratio=True)
     image = image.numpy()
@@ -77,8 +75,9 @@ with gr.Blocks(css="style.css") as demo:
     with gr.Row():
         with gr.Column():
             #image = gr.Image(label="Input", type="pil")
-            url = gr.Textbox("")
-            
+            url = gr.Textbox(value="https://raw.githubusercontent.com/gradio-app/gradio/main/test/test_files/bus.png")
+            response = requests.get(url)
+            image = PIL.Image.open(BytesIO(response.content))
             score_threshold = gr.Slider(label="Score threshold", minimum=0, maximum=1, step=0.05, value=0.5)
             run_button = gr.Button("Run")