import gradio as gr
from ultralytics import YOLO
from PIL import Image
import numpy as np
import os
import gdown

# ✅ Download model from Google Drive if not already present
model_path = "best.pt"
file_id = "1O9C2ACDdqWKbgEShbf3AkuSqBKWDgJ3t"

if not os.path.exists(model_path):
    url = f"https://drive.google.com/uc?id={file_id}"
    gdown.download(url, model_path, quiet=False)

# ✅ Load the model
model = YOLO(model_path)

# ✅ Prediction function
def detect_damage(img):
    results = model.predict(img, conf=0.25)
    annotated = results[0].plot()
    return Image.fromarray(annotated)

# ✅ Gradio UI
demo = gr.Interface(
    fn=detect_damage,
    inputs=gr.Image(type="pil", label="Upload Car Image"),
    outputs=gr.Image(type="pil", label="Detected Damage"),
    title="🚗 Car Damage Detector (YOLOv8)",
    description="Upload an image to detect scratch, dent, crack, and more using a trained YOLOv8 model."
)

demo.launch()