---
license: cc-by-4.0
task_categories:
  - image-to-text
language:
  - en
tags:
  - ocr
  - cs2
  - counter-strike
  - hud
  - video-games
  - crnn-training
pretty_name: CS2 HUD OCR Crops
size_categories:
  - 10K<n<100K
---

# CS2 HUD OCR Crops

Per-region HUD crops sliced from three Counter-Strike 2 match recordings,
labelled where possible from the demo file's `parse_ticks` state. Built
to train a specialist CRNN that replaces the EasyOCR killfeed reader
(currently ~6 s p95 on CPU) with a sub-30 ms specialist.

## Source

Three matches by the same POV player (`farouqqq`), recorded in CS2's
built-in DVR + the corresponding `.dem` files:

| sample  | map      | dem            | rounds | resolution  | fps |
|---------|----------|----------------|--------|-------------|-----|
| sample1 | Ancient  | ancent.dem     |      8 | 1280 × 1024 |  60 |
| sample2 | Dust 2   | dust_2.dem     |     10 | 1280 × 1024 |  60 |
| sample3 | Overpass | overpass.dem   |      9 | 1280 × 1024 |  60 |

Frames sampled at 5 fps. Per-region ROIs slice via the
[`hud_extractor`](https://github.com/bashiryounis/coach-api) package's
calibrated `hud_template.json`.

## Signals + label sources

| signal          | label source                              | gate                                                          |
|-----------------|-------------------------------------------|---------------------------------------------------------------|
| `hp`            | dem `health` (POV-filtered, alive only)   | v_mask brightness + phash dedupe                              |
| `money`         | dem `balance`                             | v_mask brightness + phash dedupe                              |
| `ammo`          | dem `m_iClip1` (alive only)               | v_mask brightness + phash dedupe                              |
| `timer`         | tesserocr text (≥ 0.70 conf) — optional   | v_mask brightness + phash dedupe                              |
| `killcam`       | tesserocr binary (≥ 0.50 conf) — optional | v_mask + phash + ±5 s POV death window                        |
| `killfeed`      | **unlabeled** in this v1 (use Colab GPU)  | v_mask brightness + phash dedupe; one crop per row slot       |
| `friendly_chat` | **unlabeled** in this v1 (use Colab GPU)  | v_mask brightness + phash dedupe; one crop per row slot       |

`killfeed` and `friendly_chat` are saved without text labels in this
release because the EasyOCR teacher (~600 ms / row on CPU) made a single
pass impractical. The crops are ready for a GPU-side labeling sweep
(EasyOCR `gpu=True` is ~10× faster on a single T4).

## File layout

```
dataset/cs2_ocr/
├── crops/                              # PNG, one per labeled crop
│   ├── hp_sample1_r07_f000048.png
│   ├── money_sample2_r03_f000132.png
│   ├── killfeed_sample3_r05_f000240_row2.png
│   ├── friendly_chat_sample1_r10_f000600_row3.png
│   └── ...
├── train.parquet
├── val.parquet
├── test.parquet
└── manifest.json
```

Split key = `(sample, round)`, so no frame leak across splits.

| split | composition                                                                                              |
|-------|-----------------------------------------------------------------------------------------------------------|
| train | sample1 r07-r10 · sample2 r01-r07 · sample3 r01-r06                                                       |
| val   | sample1 r11 · sample2 r08 · sample3 r07                                                                  |
| test  | sample1 r12-r14 · sample2 r09-r10 · sample3 r08-r09                                                       |

## Parquet schema

| column          | type   | notes                                                                              |
|-----------------|--------|------------------------------------------------------------------------------------|
| `crop_path`     | str    | relative to dataset root, e.g. `crops/hp_sample1_r07_f000048.png`                   |
| `signal`        | str    | one of `hp` `money` `ammo` `timer` `killcam` `killfeed` `friendly_chat`             |
| `label`         | str    | ground-truth string; `""` for unlabeled rows                                       |
| `teacher_engine`| str    | `dem` / `tesserocr` / `easyocr` / `unlabeled`                                       |
| `teacher_conf`  | float  | 0-1; `1.0` for `dem`, `0.0` for `unlabeled`                                         |
| `dem_verified`  | bool   | `True` iff label came from the dem (the dem is ground truth)                       |
| `clip_id`       | str    | source clip, e.g. `sample1_r07`                                                    |
| `frame_idx`     | int    | original frame ordinal inside the clip                                             |
| `width_px`      | int    | crop width in pixels                                                               |
| `height_px`     | int    | crop height in pixels                                                              |

## How to load

```python
from datasets import load_dataset
ds = load_dataset("ybashir/CS2-HUD-OCR-Crops")
```

To get an actual image rather than a path you'll need to join the
`crop_path` column with the downloaded `crops/` directory.

## Build details

- Frame extractor + dem alignment + ROI slicer:
  [`scripts/build_crnn_dataset.py`](https://github.com/bashiryounis/coach-api)
- Clip cutter (per-round mp4s):
  [`scripts/cut_clips.py`](https://github.com/bashiryounis/coach-api)
- HUD template (calibrated ROIs + row slots):
  [`hud_extractor/hud_extractor/config/hud_template.json`](https://github.com/bashiryounis/coach-api)

## Known limitations

- POV-only labels. The `dem` ground truth applies to `farouqqq`'s state;
  other players' HUDs are not in scope.
- `sample3` round 1 begins before the dem started recording. Its
  `dem_freeze_s` is negative — the dem-truth labels begin partway into
  the clip.
- `parse_event` is broken on these dem files (`EntityNotFound` across
  every version of `demoparser2`), so `player_death` correlations for
  killfeed verification are not available. EasyOCR remains the only
  signal source for killfeed/chat.
- Re-encoded clips (`-c libx264 -crf 20`) lose a few decibels vs. the
  source DVR; not visible at HUD resolution but flagged for transparency.

## License

CC-BY-4.0. The underlying gameplay footage is captured from a personal
Counter-Strike 2 session (Valve Corp.) — the dataset is published for
non-commercial research on HUD-region OCR distillation.