Update app.py

app.py

@@ -1,24 +1,27 @@
-import gradio as gr
-from ultralytics import YOLO
-import cv2
-
-# Load your YOLOv8 model
-model = YOLO("best.pt")
-
-# Prediction function
-def detect_fracture(image):
-    results = model.predict(source=image, save=False)  # Run inference
-    annotated_img = results[0].plot()  # Draw detections
-    return annotated_img
-
-# Gradio interface
-demo = gr.Interface(
-    fn=detect_fracture,
-    inputs=gr.Image(type="numpy", label="Upload Bone X-ray"),
-    outputs=gr.Image(type="numpy", label="Detection Result"),
-    title="Human Bone Fracture Detection",
-    description="Upload an X-ray image to detect types of human bone fractures using YOLOv8."
-)
-
-if __name__ == "__main__":
-    demo.launch(debug=True)
+import gradio as gr
+from ultralytics import YOLO
+import cv2
+
+
+torch.serialization.add_safe_globals([DetectionModel])
+
+# Load your YOLOv8 model
+model = YOLO("best.pt")
+
+# Prediction function
+def detect_fracture(image):
+    results = model.predict(source=image, save=False)  # Run inference
+    annotated_img = results[0].plot()  # Draw detections
+    return annotated_img
+
+# Gradio interface
+demo = gr.Interface(
+    fn=detect_fracture,
+    inputs=gr.Image(type="numpy", label="Upload Bone X-ray"),
+    outputs=gr.Image(type="numpy", label="Detection Result"),
+    title="Human Bone Fracture Detection",
+    description="Upload an X-ray image to detect types of human bone fractures using YOLOv8."
+)
+
+if __name__ == "__main__":
+    demo.launch(debug=True)