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license: apache-2.0
task_categories:
- object-detection
tags:
- scene-text
- text-detection
- video
- multilingual
---
# SceneText50
SceneText50 is a diverse multilingual outdoor dataset introduced in the paper [Back-Tracking from Clarity: Self-Learning to See Text from Afar](https://huggingface.co/papers/2609.32477).
It consists of 50 outdoor ego-centric videos (~840 clips) from 17 countries, with quadrilateral text annotations. The annotations are for **evaluation**; the self-learning pipeline introduced in the paper needs no manual labels for training.
Code: https://github.com/trid2912/BackTrackingText
## Dataset structure
```text
tracking_data/
├── 01/ 02/ ... 50/ # one folder per video
│ ├── clip_10/ # a clip = a short frame sequence
│ │ ├── clip_10_0000.jpg
│ │ ├── clip_10_0001.jpg
│ │ └── ...
│ ├── clip_10_0000.txt # per-frame annotation (same basename as the frame)
│ ├── clip_10_0001.txt
│ └── ...
```
Each annotation line is one text instance:
```text
instance_id x1 y1 x2 y2 x3 y3 x4 y4
```
`instance_id` is the track ID (consistent across frames of a clip) and the four `(x, y)` pairs are the clockwise quadrilateral corners.
## Sample usage
Download from Hugging Face:
```bash
# option 1 — huggingface-cli
pip install -U "huggingface_hub[cli]"
huggingface-cli download Tri1/SceneText50 --repo-type dataset --local-dir data/tracking_data
# option 2 — git + git-lfs
git lfs install
git clone https://huggingface.co/datasets/Tri1/SceneText50 data/tracking_data
```
Point `--image_root` at this `tracking_data` folder when running the tracker / pipeline. |