| 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. |