| license: apache-2.0 | |
| library_name: PaddleOCR | |
| language: | |
| - en | |
| - zh | |
| pipeline_tag: image-to-text | |
| tags: | |
| - OCR | |
| - PaddlePaddle | |
| - PaddleOCR | |
| - doc_img_unwarping | |
| # UVDoc | |
| ## Introduction | |
| The main purpose of text image correction is to carry out geometric transformation on the image to correct the document distortion, inclination, perspective deformation and other problems in the image, so that the subsequent text recognition can be more accurate. | |
| | Model| CER | | |
| | --- | --- | | |
| |UVDoc | 0.179 | | |
| **Note**: Test data set: docunet benchmark data set. | |
| ## Model Usage | |
| ### Install Dependencies | |
| ```shell | |
| pip install -U paddleocr | |
| pip install -U onnxruntime-gpu | |
| ``` | |
| ### CLI Usage | |
| ```shell | |
| paddleocr text_image_unwarping -i ./demo.jpg --model_name UVDoc --engine onnxruntime | |
| ``` | |
| ### Python API Usage | |
| ```python | |
| from paddleocr import TextImageUnwarping | |
| model = TextImageUnwarping( | |
| model_name="UVDoc", | |
| engine="onnxruntime", | |
| ) | |
| output = model.predict("./demo.jpg", batch_size=1) | |
| for res in output: | |
| res.print() | |
| res.save_to_img(save_path="./output/") | |
| ``` |