Update app.py

app.py

@@ -8,10 +8,17 @@ examples=[["photo/a.jpg","Image1"],["photo/b.jpg","Image2"],
           ["photo/g.jpg","Image7"],["photo/h.jpg","Image8"]]
 
 
-def detect_objects_on_image(image_path):
+def detect_objects_on_image(image_path, conf_threshold, iou_threshold):
     image = cv2.imread(image_path)
     model = YOLO("best.pt")
-    results = model.predict(image_path, conf=0.3, iou=0.5)
+    results = model.predict(
+        source=image,
+        conf=conf_threshold,
+        iou=iou_threshold,
+        show_labels=True,
+        show_conf=True,
+        imgsz=640,
+    )
     result = results[0]
     output = []
     for box in result.boxes:
@@ -45,7 +52,11 @@ outputs_image = [
 ]
 demo = gr.Interface(
     fn=detect_objects_on_image,
-    inputs=inputs_image,
+    inputs=[
+        gr.Image(type="pil", label="Upload Image"),
+        gr.Slider(minimum=0, maximum=1, value=0.25, label="Confidence threshold"),
+        gr.Slider(minimum=0, maximum=1, value=0.45, label="IoU threshold"),
+    ],
     outputs=outputs_image,
     title="Yolov8 Custom Object Detection",
     examples=examples,