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library_name: onnxruntime
pipeline_tag: object-detection
license: mit
base_model: microsoft/table-transformer-detection
tags:
- table-detection
- table-structure-recognition
- tatr
- table-transformer
- onnx
- gmft
---
# Microsoft Table Transformer (TATR) — ONNX re-export
Re-export of Microsoft's Table Transformer to ONNX, packaged the way [GMFT](https://github.com/conjuncts/gmft) consumes it. Used by [ScanIndex](https://github.com/welcomyou/scanindex) for table detection + structure recognition during DOCX export.
## Variants
| Subdir | Upstream | Task |
|---|---|---|
| `gmft_onnx/detection/model.onnx` | [`microsoft/table-transformer-detection`](https://huggingface.co/microsoft/table-transformer-detection) | Detect table bounding boxes on a page |
| `gmft_onnx/structure/model.onnx` | [`microsoft/table-transformer-structure-recognition-v1.1-all`](https://huggingface.co/microsoft/table-transformer-structure-recognition-v1.1-all) | Detect rows / columns / cells inside a cropped table |
Each subdir also contains the HF `config.json` + preprocessor metadata so `transformers` / `optimum` can wrap the ONNX directly.
## Loading
```python
from huggingface_hub import snapshot_download
local = snapshot_download("welcomyou/gmft-tatr-onnx", local_dir="models")
# Detection: f"{local}/gmft_onnx/detection/model.onnx"
# Structure: f"{local}/gmft_onnx/structure/model.onnx"
```
## Re-export reproduction
See [train-convert/gmft/convert/export_gmft_tatr_to_onnx.py](https://github.com/welcomyou/scanindex/blob/main/train-convert/gmft/convert/export_gmft_tatr_to_onnx.py).
## License
MIT, inherited from Microsoft Table Transformer.
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