Create app.py

app.py

@@ -0,0 +1,40 @@
+import gradio as gr
+from ultralytics import YOLO
+from PIL import Image
+import numpy as np
+import os
+
+# Load model (make sure best.pt is in the same directory)
+MODEL_PATH = "best.pt"
+
+if not os.path.exists(MODEL_PATH):
+    raise FileNotFoundError("best.pt not found. Upload your trained model to the Space.")
+
+model = YOLO(MODEL_PATH)
+
+def predict(image):
+    """
+    Run YOLOv8 pose inference on uploaded image
+    """
+    results = model(image)
+
+    # Plot result with keypoints
+    annotated_frame = results[0].plot()
+
+    return annotated_frame
+
+title = "🐶 DogFLW YOLOv8 Pose Detection"
+description = """
+Upload an image of a dog to detect facial keypoints using a trained YOLOv8 pose model.
+"""
+
+demo = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Image(type="numpy"),
+    title=title,
+    description=description,
+)
+
+if __name__ == "__main__":
+    demo.launch()