| from typing import Dict |
| from ultralytics import YOLO |
| import requests |
| from io import BytesIO |
| from PIL import Image |
| import time |
| import logging |
| import os |
| import torch |
| import torchvision |
|
|
|
|
| class EndpointHandler(): |
| def __init__(self, path=""): |
| |
| 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(path)}') |
| t1 = time.time() |
| self.model = YOLO(os.path.join(path, 'yolov8m_detect_usdl.pt')) |
| logging.info(f'TIME: loading the model {time.time() - t1}') |
| logging.info(f'torch version : {torch.__version__}') |
| logging.info(f'torch vision version: {torchvision.__version__}') |
|
|
|
|
| def __call__(self, data: Dict) -> Dict: |
|
|
| logging.info(f'data is : {data}') |
| logging.info(f'type of data is : {type(data)}') |
| image_url = data.get('image_url') |
| logging.info(f'Image url is : {image_url}') |
| response = requests.get(image_url) |
| pil_image = Image.open(BytesIO(response.content)) |
| |
| logging.info('Model inference started....') |
| t1 = time.time() |
| results = self.model(pil_image) |
| logging.info(f'TIME Model inference: {time.time() - t1}') |
| |
| return {"bbox": results[0].boxes.data.tolist()} |
