Update app.py

app.py

@@ -8,34 +8,36 @@ import numpy as np
 model = YOLO('best (1).pt')
 
 
-def response(image):
-  print(image)
-  results = model(image)
-  for i, r in enumerate(results):
+# def response(image):
+#   print(image)
+#   results = model(image)
+#   for i, r in enumerate(results):
       
-    # Plot results image
-      im_bgr = r.plot()  
-      im_rgb = im_bgr[..., ::-1]  # Convert BGR to RGB
+#     # Plot results image
+#       im_bgr = r.plot()  
+#       im_rgb = im_bgr[..., ::-1]  # Convert BGR to RGB
     
-    # im_rgb = Image.fromarray(im_rgb)
+#     # im_rgb = Image.fromarray(im_rgb)
       
-      return im_rgb
+#       return im_rgb
 
-def yoloV8_func(image: gr.Image = None,
-                image_size: gr.Slider = 640,
-                conf_threshold: gr.Slider = 0.4,
-                iou_threshold: gr.Slider = 0.50):
+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')
     
-    results = model.predict(image,
-                            conf=conf_threshold,
-                            iou=iou_threshold,
-                            imgsz=image_size)
+    results = model.predict(image, conf=conf_threshold, iou=iou_threshold, imgsz=image_size)
 
     box = results[0].boxes
 
-    render = render_result(model=model, image=image, result=results[0], rect_th = 1, text_th = 1)
-    return render
+    # render = render_result(model=model, image=image, result=results[0], rect_th = 1, text_th = 1
+   for i, r in enumerate(results):
+      
+    # Plot results image
+      im_bgr = r.plot()  
+      im_rgb = im_bgr[..., ::-1]  # Convert BGR to RGB
+    
+    # im_rgb = Image.fromarray(im_rgb)
+    return im_rgb
 
 
 inputs = [
@@ -71,5 +73,5 @@ title = "YOLOv8 Custom Object Detection by Uyen Nguyen"
 # Launch the Gradio interface in debug mode with queue enabled
 # yolo_app.launch()
 
-iface = gr.Interface(fn=yoloV8_func, inputs=inputs, outputs=outputs)
+iface = gr.Interface(fn=response2, inputs=inputs, outputs=outputs)
 iface.launch()