import gradio as gr
from huggingface_hub import hf_hub_download
from ultralytics import YOLO
import numpy as np

model_path = hf_hub_download(repo_id="newtechdevng/detect", filename="best.pt")
model = YOLO(model_path)

def predict(image):
    results = model(image)
    result = results[0]

    # Get annotated image with boxes drawn
    annotated = result.plot()

    labels = []
    for box in result.boxes:
        confidence = float(box.conf)
        if confidence < 0.5:
            continue
        label = result.names[int(box.cls)]
        labels.append(f"{label}: {confidence:.2f}")

    return annotated, "\n".join(labels) if labels else "No objects detected"

gr.Interface(
    fn=predict,
    inputs=gr.Image(type="pil"),
    outputs=[
        gr.Image(label="Detected Objects"),   # image with boxes
        gr.Text(label="Labels")               # text results
    ],
    title="Car / Bike / Mountain / Road Detector"
).launch()