from typing import  Dict
from ultralytics import YOLO
import requests
from io import BytesIO
from PIL import Image
import time


class EndpointHandler():
    def __init__(self, path=""):
        # load the model
        print('Loading the yolo model')
        model_path = "yolov8m_detect_usdl.pt"
        self.model = YOLO(model_path)
        print('Yolo model loaded successfully')


    def __call__(self, data: Dict) -> Dict:

        image_url = data.get('image_url')
        print(f'Image url is : {image_url}')
        response = requests.get(image_url)
        pil_image = Image.open(BytesIO(response.content))
        
        print('Model inference started....')
        t1 = time.time()
        results = self.model(pil_image)
        print(f'TIME Model inference: {time.time() - t1}')
        # postprocess the prediction
        return {"bbox": results[0].boxes.data.tolist()}