thesanogoeffect/PP-DocLayoutV3-ONNX
By thesanogoeffect · ↓ 0 · ♥ 0 · Updated 2026-02-27
What's in this repo
This page lists the files in thesanogoeffect/PP-DocLayoutV3-ONNX, including pp_doclayout_v3_dynbatch.onnx.
- 1 ONNX models (.onnx files)
- 4 files, including 1 .md, 1 .onnx, 1 .data
- Last updated 2026-02-27
ONNX files
| File | Size | Download |
|---|---|---|
| pp_doclayout_v3_dynbatch.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
PP-DocLayout V3 — ONNX (Dynamic Batch)
ONNX export of PaddlePaddle/PP-DocLayoutV3_safetensors with dynamic batch axis support.
Details
- Architecture: RT-DETR with HGNet-v2 backbone
- Input:
pixel_values—[batch, 3, 800, 800](float32) - Outputs:
logits[batch, 300, 25],pred_boxes[batch, 300, 4] - Opset: 17
- Export method:
torch.onnx.export(TorchScript path) from HuggingFace Transformers
Usage
import onnxruntime as ort
import numpy as np
sess = ort.InferenceSession("pp_doclayout_v3_dynbatch.onnx")
images = np.random.randn(4, 3, 800, 800).astype(np.float32) # batch of 4
logits, pred_boxes = sess.run(None, {"pixel_values": images})[:2]
Labels
| ID | Label | ID | Label |
|---|---|---|---|
| 0 | abstract | 13 | header |
| 1 | algorithm | 14 | image |
| 2 | aside_text | 15 | formula |
| 3 | chart | 16 | number |
| 4 | content | 17 | paragraph_title |
| 5 | formula | 18 | reference |
| 6 | doc_title | 19 | reference_content |
| 7 | figure_title | 20 | seal |
| 8 | footer | 21 | table |
| 9 | footer | 22 | text |
| 10 | footnote | 23 | text |
| 11 | formula_number | 24 | vision_footnote |
| 12 | header |
Files (4)
.gitattributes
README.md
pp_doclayout_v3_dynbatch.onnx
ONNX
pp_doclayout_v3_dynbatch.onnx.data
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