Create app.py

app.py

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+import gradio as gr
+from PIL import Image
+from ultralytics import YOLO
+import numpy as np
+
+# Load your model
+model = YOLO("best (2).pt")
+
+# Prediction function
+def detect_teeth(image):
+    results = model.predict(image, conf=0.26)
+
+    # Optional post-processing
+    r = results[0]
+    if r.masks is not None:
+        r.masks.data = (r.masks.data > 0.3).float()
+
+    # Create segmented image with bounding boxes and masks
+    output_img = r.plot()
+    return Image.fromarray(output_img)
+
+# Gradio interface
+interface = gr.Interface(
+    fn=detect_teeth,
+    inputs=gr.Image(type="pil", label="Upload Dental X-ray"),
+    outputs=gr.Image(type="pil", label="Detection Result"),
+    title="Dental X-ray Detection",
+    description="Upload a dental X-ray to see segmentation and detection results using YOLOv8."
+)
+
+interface.launch()