Skip to main content

doc page extractor can identify text and format in images and return structured data.

Project description

doc page extractor

English | 中文

Introduction

doc page extractor can identify text and format in images and return structured data.

Installation

pip install doc-page-extractor
pip install onnxruntime==1.21.0

Using CUDA

Please refer to the introduction of PyTorch and select the appropriate command to install according to your operating system.

In addition, replace the command to install onnxruntime in the previous article with the following:

pip install onnxruntime-gpu==1.21.0

Example

from PIL import Image
from doc_page_extractor import DocExtractor

extractor = DocExtractor(
  model_dir_path=model_path, # Folder address where AI model is downloaded and installed
  device="cpu", # If you want to use CUDA, please change to device="cuda".
)
with Image.open("/path/to/your/image.png") as image:
  result = extractor.extract(
  image=image,
  lang="ch", # Language of image text
)
for layout in result.layouts:
  for fragment in layout.fragments:
    print(fragment.rect, fragment.text)

Acknowledgements

The code of doc_page_extractor/onnxocr in this repo comes from OnnxOCR.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

doc-page-extractor-test-0.1.7.tar.gz (62.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

doc_page_extractor_test-0.1.7-py3-none-any.whl (74.5 kB view details)

Uploaded Python 3

File details

Details for the file doc-page-extractor-test-0.1.7.tar.gz.

File metadata

  • Download URL: doc-page-extractor-test-0.1.7.tar.gz
  • Upload date:
  • Size: 62.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.13

File hashes

Hashes for doc-page-extractor-test-0.1.7.tar.gz
Algorithm Hash digest
SHA256 0bb4f1381e45be6f529edfa03b58586a2b23a29d0b10fd6631236ef9b884fbf9
MD5 31ea28f841102d2fe5d483f3fe92d2a1
BLAKE2b-256 f60520e884ab79483b5536e13fd37809b71d87756b7d4043309ed07fe062c0c6

See more details on using hashes here.

File details

Details for the file doc_page_extractor_test-0.1.7-py3-none-any.whl.

File metadata

File hashes

Hashes for doc_page_extractor_test-0.1.7-py3-none-any.whl
Algorithm Hash digest
SHA256 6c48ff822e5640bd73ccac3d8b3e12cb2e58c7da9410a4a32a0a993654506c5f
MD5 cc52f2681bf96d56273afe40b9bb567b
BLAKE2b-256 70ab1b3b7d4ce28c8346630c4bd8796d19fa0601664ed25275ae5bf7240ef1cf

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page