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README.md

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+---
+license: apache-2.0
+tags:
+  - document-layout-analysis
+  - table-structure-recognition
+  - onnx
+  - kreuzberg
+---
+
+# Kreuzberg Layout Models
+
+ONNX models used by [Kreuzberg](https://kreuzberg.dev) for document layout detection and table structure recognition.
+
+## Models
+
+### RT-DETR (Document Layout Detection)
+
+| Property | Value |
+|----------|-------|
+| **Path** | `rtdetr/model.onnx` |
+| **Size** | 169 MB |
+| **Precision** | FP32 |
+| **Architecture** | RT-DETR v2 (Real-Time Detection Transformer) |
+| **Input** | `images`: `[batch, 3, 640, 640]` f32 (ImageNet-normalized, letterboxed) |
+| **Input** | `orig_target_sizes`: `[batch, 2]` i64 (original `[height, width]`) |
+| **Outputs** | `labels` i64, `boxes` f32 `[batch, N, 4]`, `scores` f32 |
+| **Classes** | 17 document layout classes |
+| **SHA256** | `3bf2fb0ee6df87435b7ae47f0f3930ec3dc97ec56fd824acc6d57bc7a6b89ef2` |
+
+**Layout Classes:** Caption, Footnote, Formula, ListItem, PageFooter, PageHeader, Picture, SectionHeader, Table, Text, Title, DocumentIndex, Code, CheckboxSelected, CheckboxUnselected, Form, KeyValueRegion
+
+### SLANet-plus (Table Structure Recognition)
+
+| Property | Value |
+|----------|-------|
+| **Path** | `slanet-plus/model.onnx` |
+| **Size** | 7.8 MB |
+| **Precision** | FP32 |
+| **Architecture** | SLANet-plus (Sequence-to-Sequence table decoder) |
+| **Input** | `x`: `[1, 3, 488, 488]` f32 (BGR channel order, ImageNet-normalized) |
+| **Outputs** | `[1, seq_len, 8]` cell bbox corners, `[1, seq_len, 50]` HTML token probabilities |
+| **Vocabulary** | 50 tokens (HTML structure tags, rowspan/colspan 1-20, sos/eos) |
+| **SHA256** | `e0bff8da087f9b83629f1e1a6e0f8252fc2de85a7d80415b3510fc521338da3d` |
+
+## Attribution & Provenance
+
+### RT-DETR
+
+This model is mirrored from [docling-project/docling-layout-heron-onnx](https://huggingface.co/docling-project/docling-layout-heron-onnx), created by the [Docling](https://github.com/docling-project/docling) team at IBM Research.
+
+- **Original repository:** [docling-project/docling-layout-heron-onnx](https://huggingface.co/docling-project/docling-layout-heron-onnx)
+- **License:** Apache-2.0
+- **Architecture paper:** Zhao et al., "DETRs Beat YOLOs on Real-time Object Detection" ([arXiv:2304.08069](https://arxiv.org/abs/2304.08069))
+- **Training data:** DocLayNet and internal IBM document datasets
+
+### SLANet-plus
+
+This model was converted from PaddlePaddle format to ONNX using [Paddle2ONNX](https://github.com/PaddlePaddle/Paddle2ONNX). The original model is from the [PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR) project by PaddlePaddle.
+
+- **Original repository:** [PaddlePaddle/SLANet_plus](https://huggingface.co/PaddlePaddle/SLANet_plus)
+- **License:** Apache-2.0
+- **Architecture paper:** "PP-StructureV2: A Stronger Document Analysis System" ([arXiv:2210.05391](https://arxiv.org/abs/2210.05391))
+- **Conversion:** PaddlePaddle inference format → ONNX via Paddle2ONNX (opset 17)
+
+## Usage
+
+These models are automatically downloaded and cached by the [Kreuzberg](https://kreuzberg.dev) document extraction library. See the [layout extraction documentation](https://kreuzberg.dev) for details.
+
+## License
+
+All models in this repository are distributed under the [Apache-2.0 License](https://www.apache.org/licenses/LICENSE-2.0), consistent with the licenses of the original models.

rtdetr/model.onnx

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slanet-plus/model.onnx

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