Instructions to use dl1wjd2/Logistics_AX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use dl1wjd2/Logistics_AX with ultralytics:
from huggingface_hub import hf_hub_download from ultralytics import YOLO # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("dl1wjd2/Logistics_AX", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Download hug/lib/python3.12/site-packages/PIL/ImagePath.py from dl1wjd2/Logistics_AX: direct link, hf CLI and curl.
- Browser
- Download file 371 Bytes
-
https://huggingface.co/dl1wjd2/Logistics_AX/resolve/main/hug/lib/python3.12/site-packages/PIL/ImagePath.py
- Command line
-
hf download hf://dl1wjd2/Logistics_AX/hug/lib/python3.12/site-packages/PIL/ImagePath.py
-
curl -L -o ImagePath.py https://huggingface.co/dl1wjd2/Logistics_AX/resolve/main/hug/lib/python3.12/site-packages/PIL/ImagePath.py
371 Bytes
| # | |
| # The Python Imaging Library | |
| # $Id$ | |
| # | |
| # path interface | |
| # | |
| # History: | |
| # 1996-11-04 fl Created | |
| # 2002-04-14 fl Added documentation stub class | |
| # | |
| # Copyright (c) Secret Labs AB 1997. | |
| # Copyright (c) Fredrik Lundh 1996. | |
| # | |
| # See the README file for information on usage and redistribution. | |
| # | |
| from __future__ import annotations | |
| from . import Image | |
| Path = Image.core.path | |