Update app.py

app.py

@@ -21,9 +21,7 @@ model = YOLO('best (1).pt')
       
 #       return im_rgb
 
-def response2(image: gr.Image = None,image_size: gr.Slider = 640, conf_threshold: gr.Slider = 0.5, iou_threshold: gr.Slider = 0.6):
-                    
-    model = YOLO('best (1).pt')
+def response2(image: gr.Image = None,image_size: gr.Slider = 640, conf_threshold: gr.Slider = 0.3, iou_threshold: gr.Slider = 0.6):
     
     results = model.predict(image, conf=conf_threshold, iou=iou_threshold, imgsz=image_size)
 
@@ -44,14 +42,14 @@ inputs = [
     gr.Image(type="filepath",  label="Input Image"),
     gr.Slider(minimum=320, maximum=1280, value=640,
                      step=32, label="Image Size"),
-    gr.Slider(minimum=0.0, maximum=1.0, value=0.25,
+    gr.Slider(minimum=0.0, maximum=1.0, value=0.3,
                      step=0.05, label="Confidence Threshold"),
-    gr.Slider(minimum=0.0, maximum=1.0, value=0.45,
+    gr.Slider(minimum=0.0, maximum=1.0, value=0.6,
                      step=0.05, label="IOU Threshold"),
 ]
 
 
-outputs = gr.Image( type="filepath", label="Output Image")
+outputs = gr.Image( type="filepath", label="")
 
 title = "YOLOv8 Custom Object Detection by Uyen Nguyen"