handler.py

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


class EndpointHandler():
    def __init__(self, path=""):
        # load the model
        logging.info(f'value of path is : {path}')
        current_directory = os.getcwd()
        logging.info(f'current dir: {current_directory}')
        logging.info(f'all files: {os.listdir(current_directory)}')
        # model_path = "yolov8m_detect_usdl.pt"
        # self.model = YOLO(model_path)
        # print('Yolo model loaded successfully')


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

        logging.info(f'Value of data is : {data}')

        # 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 -> results[0].boxes.data.tolist()
        return {"bbox": data}