---
license: cc-by-nc-4.0
task_categories:
- image-classification
- object-detection
language:
- zh
- en
tags:
- tt100k
- traffic signs
pretty_name: TT100K
size_categories:
- 10K<n<100K
dataset_info:
- config_name: default
  features:
  - name: image
    dtype: image
  - name: objects
    sequence:
    - name: category
      dtype:
        class_label:
          names:
            '0': i1
            '1': i10
            '2': i11
            '3': i12
            '4': i13
            '5': i14
            '6': i15
            '7': i2
            '8': i3
            '9': i4
            '10': i5
            '11': il100
            '12': il110
            '13': il50
            '14': il60
            '15': il70
            '16': il80
            '17': il90
            '18': io
            '19': ip
            '20': p1
            '21': p10
            '22': p11
            '23': p12
            '24': p13
            '25': p14
            '26': p15
            '27': p16
            '28': p17
            '29': p18
            '30': p19
            '31': p2
            '32': p20
            '33': p21
            '34': p22
            '35': p23
            '36': p24
            '37': p25
            '38': p26
            '39': p27
            '40': p28
            '41': p3
            '42': p4
            '43': p5
            '44': p6
            '45': p7
            '46': p8
            '47': p9
            '48': pa10
            '49': pa12
            '50': pa13
            '51': pa14
            '52': pa8
            '53': pb
            '54': pc
            '55': pg
            '56': ph1.5
            '57': ph2
            '58': ph2.1
            '59': ph2.2
            '60': ph2.4
            '61': ph2.5
            '62': ph2.8
            '63': ph2.9
            '64': ph3
            '65': ph3.2
            '66': ph3.5
            '67': ph3.8
            '68': ph4
            '69': ph4.2
            '70': ph4.3
            '71': ph4.5
            '72': ph4.8
            '73': ph5
            '74': ph5.3
            '75': ph5.5
            '76': pl10
            '77': pl100
            '78': pl110
            '79': pl120
            '80': pl15
            '81': pl20
            '82': pl25
            '83': pl30
            '84': pl35
            '85': pl40
            '86': pl5
            '87': pl50
            '88': pl60
            '89': pl65
            '90': pl70
            '91': pl80
            '92': pl90
            '93': pm10
            '94': pm13
            '95': pm15
            '96': pm1.5
            '97': pm2
            '98': pm20
            '99': pm25
            '100': pm30
            '101': pm35
            '102': pm40
            '103': pm46
            '104': pm5
            '105': pm50
            '106': pm55
            '107': pm8
            '108': pn
            '109': pne
            '110': po
            '111': pr10
            '112': pr100
            '113': pr20
            '114': pr30
            '115': pr40
            '116': pr45
            '117': pr50
            '118': pr60
            '119': pr70
            '120': pr80
            '121': ps
            '122': pw2
            '123': pw2.5
            '124': pw3
            '125': pw3.2
            '126': pw3.5
            '127': pw4
            '128': pw4.2
            '129': pw4.5
            '130': w1
            '131': w10
            '132': w12
            '133': w13
            '134': w16
            '135': w18
            '136': w20
            '137': w21
            '138': w22
            '139': w24
            '140': w28
            '141': w3
            '142': w30
            '143': w31
            '144': w32
            '145': w34
            '146': w35
            '147': w37
            '148': w38
            '149': w41
            '150': w42
            '151': w43
            '152': w44
            '153': w45
            '154': w46
            '155': w47
            '156': w48
            '157': w49
            '158': w5
            '159': w50
            '160': w55
            '161': w56
            '162': w57
            '163': w58
            '164': w59
            '165': w60
            '166': w62
            '167': w63
            '168': w66
            '169': w8
            '170': wo
            '171': i6
            '172': i7
            '173': i8
            '174': i9
            '175': ilx
            '176': p29
            '177': w29
            '178': w33
            '179': w36
            '180': w39
            '181': w4
            '182': w40
            '183': w51
            '184': w52
            '185': w53
            '186': w54
            '187': w6
            '188': w61
            '189': w64
            '190': w65
            '191': w67
            '192': w7
            '193': w9
            '194': pax
            '195': pd
            '196': pe
            '197': phx
            '198': plx
            '199': pmx
            '200': pnl
            '201': prx
            '202': pwx
            '203': w11
            '204': w14
            '205': w15
            '206': w17
            '207': w19
            '208': w2
            '209': w23
            '210': w25
            '211': w26
            '212': w27
            '213': pl0
            '214': pl4
            '215': pl3
            '216': pm2.5
            '217': ph4.4
            '218': pn40
            '219': ph3.3
            '220': ph2.6
    - name: bbox
      dtype:
      - name: xmin
        dtype: float32
      - name: ymin
        dtype: float32         
      - name: ymax
        dtype: float32    
      - name: xmax
        dtype: float32
  splits:
  - name: train
    num_bytes: 1239201
    num_examples: 6105
  - name: validation
    num_bytes: 196342
    num_examples: 1097
  - name: test
    num_bytes: 617330
    num_examples: 3071
  download_size: 4761632373
  dataset_size: 2052873
configs:
- config_name: default
  data_files:
  - split: train
    path: default/train/data-*.arrow
  - split: validation
    path: default/validation/data-*.arrow
  - split: test
    path: default/test/data-*.arrow
---

# 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
```python
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
```bash
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>

## Thanks
 - <https://docs.ultralytics.com/datasets/detect/tt100k>