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
File size: 754 Bytes
88c064c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | """Private utility methods used by the subset modules"""
def _add_method(*clazzes):
"""Returns a decorator function that adds a new method to one or
more classes."""
def wrapper(method):
done = []
for clazz in clazzes:
if clazz in done:
continue # Support multiple names of a clazz
done.append(clazz)
assert clazz.__name__ != "DefaultTable", "Oops, table class not found."
assert not hasattr(
clazz, method.__name__
), "Oops, class '%s' has method '%s'." % (clazz.__name__, method.__name__)
setattr(clazz, method.__name__, method)
return None
return wrapper
def _uniq_sort(l):
return sorted(set(l))
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