---
pretty_name: ECG Image Digitization
license: cc-by-4.0
task_categories:
- image-to-text
- time-series-forecasting
tags:
- ecg
- medical
- signal-processing
- image
size_categories:
- 1K<n<10K
---

# ECG Image Digitization

Recover 12-lead ECG voltage time series from images of printed ECG pages. Each record is
one 10 second 12-lead acquisition; training records carry nine renderings of the same
printed page under different scan and photograph conditions.

## Contents

The data tree lives under `data/`, exactly as the benchmark environment presents it at
`/app/ecgdig`. Its own description is at `data/README.md`.

- 7074 files, 12821532396 bytes (11.9 GiB)
- structure hash (sha256 over sorted `path\tsize` lines): `b476fd2dcfec31e3b18025da79d38d723cb1efd19e4ea99594d8c290b61a665b`
- `data.manifest.tsv` at the repo root lists every file as `sha256  size  path`

## Use

```python
from huggingface_hub import snapshot_download

snapshot_download("Emulated-Inc/ecgdig", repo_type="dataset", revision="REVISION",
                  local_dir="./ecgdig", allow_patterns="data/*")
```

Pin `revision` to a commit sha rather than a branch if you need reproducibility.

## Provenance and licence

Derived from the PhysioNet Digitization of ECG Images Kaggle competition
(https://www.kaggle.com/competitions/physionet-ecg-image-digitization), whose data is
released under CC BY 4.0. Attribution is required by that licence; please cite
PhysioNet and the competition when using this dataset.