Update app.py

app.py

@@ -1,26 +1,18 @@
 import gradio as gr
-import spaces
 import supervision as sv
 import PIL.Image as Image
 from ultralytics import YOLO, YOLOv10
 from huggingface_hub import hf_hub_download
 
-
 def download_models(model_id):
     hf_hub_download("atalaydenknalbant/asl-models", filename=f"{model_id}", local_dir=f"./")
     return f"./{model_id}"
 
-
-
 box_annotator = sv.BoxAnnotator()
 category_dict = {0: 'A', 1: 'B', 2: 'C', 3: 'D', 4: 'E', 5: 'F', 6: 'G', 7: 'H', 8: 'I',
                  9: 'J', 10: 'K', 11: 'L', 12: 'M', 13: 'N', 14: 'O', 15: 'P', 16: 'Q',
                  17: 'R', 18: 'S', 19: 'T', 20: 'U', 21: 'V', 22: 'W', 23: 'X', 24: 'Y', 25: 'Z'}
 
-
-
-
-@spaces.GPU(duration=200)
 def yolo_inference(image, model_id, conf_threshold, iou_threshold):
     model_path = download_models(model_id)
     if model_id[:7] == 'yolov10':
@@ -42,7 +34,7 @@ def app():
     with gr.Blocks():
         with gr.Row():
             with gr.Column():
-                image = gr.Image(type="pil", label="Image")
+                image = gr.Image(type="pil", label="Image", tool="editor")
                 
                 model_id = gr.Dropdown(
                     label="Model",
@@ -71,7 +63,7 @@ def app():
                 yolov10_infer = gr.Button(value="Detect Objects")
 
             with gr.Column():
-                output_image = gr.Image(type="pil", label="Annotated Image")
+                output_image = gr.Image(type="pil", label="Annotated Image", interactive=False)
 
         yolov10_infer.click(
             fn=yolo_inference,
@@ -116,4 +108,4 @@ with gradio_app:
         with gr.Column():
             app()
 
-gradio_app.launch(debug=True)
+gradio_app.launch(debug=True)