Upload 3 files

app.py

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+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)

best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:855d4ed37ed87ac62632d2d826a468474e4e380cfdbdab26bdc1916c98ea224a
+size 6251939

requirements.txt

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+gradio==4.29.0
+ultralytics==8.2.53
+opencv-python==4.9.0.80
+torch>=2.0.0