Add application file

app.py

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+from ultralytics import YOLO
+from PIL import Image
+import gradio as gr
+from huggingface_hub import snapshot_download
+import os
+
+# Define the Hugging Face repository ID and the model path
+REPO_ID = "aleong888/snoopy"  # Replace with your Hugging Face repository ID
+
+# Function to load the model from the repository
+def load_model(repo_id):
+    download_dir = snapshot_download(repo_id)
+    print("Downloaded model to:", download_dir)
+    model_path = os.path.join(download_dir, "best_int8_openvino_model")
+    print("Model path:", model_path)
+    detection_model = YOLO(model_path, task='detect')
+    return detection_model
+
+# Function to make predictions on input images
+def predict(pilimg):
+    result = detection_model.predict(pilimg, conf=0.5, iou=0.4)
+    img_bgr = result[0].plot()
+    out_pilimg = Image.fromarray(img_bgr[..., ::-1])  # Convert BGR to RGB
+    return out_pilimg
+
+# Load the model
+detection_model = load_model(REPO_ID)
+
+# Create the Gradio interface
+gr.Interface(fn=predict,
+             inputs=gr.Image(type="pil", label="Upload an image"),
+             outputs=gr.Image(type="pil", label="Detection Result"),
+             title="Snoopy Detection Model",
+             description="Upload an image to detect Snoopy and Woodstock characters. This application uses a YOLOv8 model trained with OpenVINO optimization."
+             ).launch(share=True)