| --- |
| license: mit |
| language: |
| - en |
| - tr |
| --- |
| |
| # PaddleOCR Mobile Quantized Models (ONNX) |
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| ## Overview |
| This repo hosts four **ONNX** models converted from PaddleOCR mobile checkpoints |
|
|
| | File | Task | Language scope | Input shape | |
| |------|------|----------------|-------------| |
| | `Multilingual_PP-OCRv3_det_infer.onnx` | Text-detection | 80+ scripts | **NCHW • 1×3×H×W** | |
| | `PP-OCRv3_mobile_det_infer.onnx` | Text-detection | Latin only | 1×3×H×W | |
| | `ch_ppocr_mobile_v2.0_cls_infer.onnx` | Angle classifier | Chinese/Latin | 1×3×H×W | |
| | `latin_PP-OCRv3_mobile_rec_infer.onnx` | Text-recognition | Latin | 1×3×H×W | |
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| All models were: |
| * exported with **paddle2onnx 1.2.3** (`opset 11`) |
| * simplified via **onnx-simplifier 0.4+** |
|
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| ## Quick Start |
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|
| ```python |
| import onnxruntime as ort, numpy as np |
| img = np.random.rand(1, 3, 224, 224).astype("float32") |
| |
| det = ort.InferenceSession("Multilingual_PP-OCRv3_det_infer.onnx") |
| cls = ort.InferenceSession("ch_ppocr_mobile_v2.0_cls_infer.onnx") |
| rec = ort.InferenceSession("latin_PP-OCRv3_mobile_rec_infer.onnx") |
| |
| det_out = det.run(None, {det.get_inputs()[0].name: img})[0] |
| # add your post-processing / cropping / decoding here … |
| |
