PP OCRv5 Server Rec Onnx

--- license: apache-2.0 library_name: PaddleOCR language: - en - zh pipeline_tag: image-to-text tags: - OCR - PaddlePaddle - PaddleOCR - textline_recognition --- # PP-OCRv5_server_rec ## Introduction PP-OCRv5_server_rec is one of the PP-OCRv5_rec that are the latest generation text line recognition models developed by PaddleOCR team. It aims to efficiently and accurately support the recognition of four major languages—Simplified Chinese, Traditional Chinese, English, and Japanese—as well as complex text scenarios such as handwriting, vertical text, pinyin, and rare characters using a single model. The key accuracy metrics are as follow: | Handwritten Chinese | Handwritten English | Printed Chinese | Printed English | Traditional Chinese | Ancient Text | Japanese | General Scenario | Pinyin | Rotation | Distortion | Artistic Text | Average | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 0.5807 | 0.5806 | 0.9013 | 0.8679 | 0.7472 | 0.6039 | 0.7372 | 0.5946 | 0.8384 | 0.7435 | 0.9314 | 0.6397 | 0.8401 | **Note**: If any character (including punctuation) in a line was incorrect, the entire line was marked as wrong. This ensures higher accuracy in practical applications. ## Model Usage ### Install Dependencies ```shell pip install -U paddleocr pip install -U onnxruntime-gpu ``` ### CLI Usage ```shell paddleocr text_recognition -i ./demo.png --model_name PP-OCRv5_server_rec --engine onnxruntime ``` ### Python API Usage ```python from paddleocr import TextRecognition model = TextRecognition( model_name="PP-OCRv5_server_rec", engine="onnxruntime", ) output = model.predict("./demo.png", batch_size=1) for res in output: res.print() res.save_to_json(save_path="./output/res.json") ```

Source context: 1895 downloads · 0 likes · Pipeline image-to-text · Library PaddleOCR · Repo PaddlePaddle/PP-OCRv5_server_rec_onnx

Source context: 366 downloads · 0 likes · Pipeline image-to-text · Library PaddleOCR · Repo PaddlePaddle/PP-OCRv5_server_rec_onnx