metadata
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.
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
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:
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:
# 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.