tt100k-yolov4
Collection
yolov4 trained on TT100K dataset • 2 items • Updated • 1
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image image | objects dict |
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End of preview.
Intro
The Tsinghua–Tencent 100K (TT100K) dataset is a large-scale traffic sign benchmark built from 100,000 Tencent Street View images, containing over 30,000 annotated instances across 221 categories. Designed for real-world detection and classification tasks, it features significant variation in lighting, weather, viewpoint, and distance. While the original study focuses on a 45-class subset using a 100-instance threshold per class, the Ultralytics configuration retains all 221 categories, including many with sparse samples, making the dataset both comprehensive and challenging for robust model development. The current dataset is a version from which negative samples have been removed.
Usage
from datasets import load_dataset
ds = load_dataset(
"Genius-Society/tt100k",
name="default",
split="train",
cache_dir="./__pycache__",
)
for i in ds:
print(i)
Maintenance
GIT_LFS_SKIP_SMUDGE=1 git clone git@hf.co:datasets/Genius-Society/tt100k
cd tt100k
Mirror
https://www.modelscope.cn/datasets/Genius-Society/tt100k
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