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: 1,020 Bytes
bbae060 | 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 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | from collections import UserDict, UserList
__all__ = ["LazyDict", "LazyList"]
class LazyDict(UserDict):
def __init__(self, data):
super().__init__()
self.data = data
def __getitem__(self, k):
v = self.data[k]
if callable(v):
v = v(k)
self.data[k] = v
return v
class LazyList(UserList):
def __getitem__(self, k):
if isinstance(k, slice):
indices = range(*k.indices(len(self)))
return [self[i] for i in indices]
v = self.data[k]
if callable(v):
v = v(k)
self.data[k] = v
return v
def __add__(self, other):
if isinstance(other, LazyList):
other = list(other)
elif isinstance(other, list):
pass
else:
return NotImplemented
return list(self) + other
def __radd__(self, other):
if not isinstance(other, list):
return NotImplemented
return other + list(self)
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