UVDoc Onnx
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...
Fuente del modelo
- Tipo
- Modelo
- Tamaño del archivo
- 30,2 MB
- Versión
- vRevision 3bcf535
- Actualizado
- 30 oct 2026
- Descargas
- 1,9 mil
- Fuente
- Hugging Face
Descripción de la fuente
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
pip install -U paddleocr
pip install -U onnxruntime-gpu
CLI Usage
paddleocr text_image_unwarping -i ./demo.jpg --model_name UVDoc --engine onnxruntime
Python API Usage
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/")
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 30 oct
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactoExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- 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/") ```
Source context: 1850 downloads · 2 likes · Pipeline image-to-text · Library PaddleOCR · Repo PaddlePaddle/UVDoc_onnx
Source context: 484 downloads · 0 likes · Pipeline image-to-text · Library PaddleOCR · Repo PaddlePaddle/UVDoc_onnx
