Perform optical character recognition using the DocTR library
Project description
Sinapsis DocTR
DocTR-based Optical Character Recognition (OCR) for images
🐍 Installation • 🚀 Features • 📚 Usage example • 🌐 Webapp • 📙 Documentation • 🔍 License
Sinapsis DocTR provides a powerful and flexible implementation for extracting text from images using the DocTR OCR engine. It enables users to easily configure and run OCR tasks with minimal setup.
🐍 Installation
Install using your package manager of choice. We encourage the use of uv
Example with uv:
uv pip install sinapsis-doctr --extra-index-url https://pypi.sinapsis.tech
or with raw pip:
pip install sinapsis-doctr --extra-index-url https://pypi.sinapsis.tech
[!IMPORTANT] Templates may require extra dependencies. For development, we recommend installing the package with all the optional dependencies:
with uv:
uv pip install sinapsis-doctr[all] --extra-index-url https://pypi.sinapsis.tech
or with raw pip:
pip install sinapsis-doctr[all] --extra-index-url https://pypi.sinapsis.tech
[!TIP] Use CLI command
sinapsis info --all-template-namesto show a list with all the available Template names installed with Sinapsis OCR.
[!TIP] Use CLI command
sinapsis info --example-template-config DocTROCRPredictionto produce an example Agent config for the DocTROCRPrediction template.
🚀 Features
Templates Supported
This module includes a template tailored for the DocTR OCR engine:
- DocTROCRPrediction: Uses DocTR's OCR model to extract text, bounding boxes, and confidence scores from images.
DocTROCRPrediction Attributes
recognized_characters_as_labels(bool): Whether to use recognized characters as labels. Defaults toFalse.artefact_type_as_labels(bool): Whether to use artefact type as labels. Defaults toFalse.det_arch(str): Detection architecture to use. Defaults to"fast_base".reco_arch(str): Recognition architecture to use. Defaults to"crnn_vgg16_bn".pretrained(bool): Whether to use pretrained models. Defaults toTrue.pretrained_backbone(bool): Whether to use pretrained backbone. Defaults toTrue.assume_straight_pages(bool): Whether to assume pages are straight. Defaults toTrue.preserve_aspect_ratio(bool): Whether to preserve aspect ratio. Defaults toTrue.symmetric_pad(bool): Whether to use symmetric padding. Defaults toTrue.export_as_straight_boxes(bool): Whether to export as straight boxes. Defaults toFalse.detect_orientation(bool): Whether to detect orientation. Defaults toFalse.straighten_pages(bool): Whether to straighten pages. Defaults toFalse.detect_language(bool): Whether to detect language. Defaults toFalse.
📚 Usage example
DocTR Example
agent:
name: doctr_prediction
description: agent to run inference with DocTR, performs on images read, recognition and save
templates:
- template_name: InputTemplate
class_name: InputTemplate
attributes: {}
- template_name: FolderImageDatasetCV2
class_name: FolderImageDatasetCV2
template_input: InputTemplate
attributes:
data_dir: dataset/input
- template_name: DocTROCRPrediction
class_name: DocTROCRPrediction
template_input: FolderImageDatasetCV2
attributes:
recognized_characters_as_labels: True
- template_name: BBoxDrawer
class_name: BBoxDrawer
template_input: DocTROCRPrediction
attributes:
draw_confidence: True
draw_extra_labels: True
- template_name: ImageSaver
class_name: ImageSaver
template_input: BBoxDrawer
attributes:
save_dir: output
root_dir: dataset
To run, simply use:
sinapsis run name_of_the_config.yml
🌐 Webapp
The webapp provides a simple interface to extract text from images using DocTR OCR. Upload your image, and the app will process it and display the detected text with bounding boxes.
[!IMPORTANT] To run the app you first need to clone the sinapsis-ocr repository:
git clone https://github.com/Sinapsis-ai/sinapsis-ocr.git
cd sinapsis-ocr
[!NOTE] If you'd like to enable external app sharing in Gradio,
export GRADIO_SHARE_APP=True
[!IMPORTANT] To use DocTR in the webapp, set the environment variable:
AGENT_CONFIG_PATH=/app/packages/sinapsis_doctr/src/sinapsis_doctr/configs/doctr_demo.yaml
🐳 Docker
IMPORTANT This docker image depends on the sinapsis:base image. Please refer to the official sinapsis instructions to Build with Docker.
- Build the sinapsis-ocr image:
docker compose -f docker/compose.yaml build
- Start the app container:
docker compose -f docker/compose_app.yaml up
- Check the status:
docker logs -f sinapsis-ocr-app
- The logs will display the URL to access the webapp, e.g.:
NOTE: The url can be different, check the output of logs
Running on local URL: http://127.0.0.1:7860
- To stop the app:
docker compose -f docker/compose_app.yaml down
💻 UV
To run the webapp using the uv package manager, please:
- Create the virtual environment and sync the dependencies:
uv sync --frozen
- Install packages:
uv pip install sinapsis-doctr[all] --extra-index-url https://pypi.sinapsis.tech
- Run the webapp:
uv run webapps/gradio_ocr.py
- The terminal will display the URL to access the webapp, e.g.:
Running on local URL: http://127.0.0.1:7860
NOTE: The url can be different, check the output of the terminal
- To stop the app press
Control + Con the terminal
📙 Documentation
Documentation for this and other sinapsis packages is available on the sinapsis website
Tutorials for different projects within sinapsis are available at sinapsis tutorials page
🔍 License
This project is licensed under the AGPLv3 license, which encourages open collaboration and sharing. For more details, please refer to the LICENSE file.
For commercial use, please refer to our official Sinapsis website for information on obtaining a commercial license.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file sinapsis_doctr-0.1.7.tar.gz.
File metadata
- Download URL: sinapsis_doctr-0.1.7.tar.gz
- Upload date:
- Size: 22.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.5.16
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
4852fcb868eb8a13dbc7f22ed8d23832ba66da4a94651fcb547f9a954cff3ad7
|
|
| MD5 |
7484da96bcfcf2f15ddd9e075c615061
|
|
| BLAKE2b-256 |
a309fec3528c902361e31fa24d98fdce8387273ee9f5fcb3152c574326d3221f
|
File details
Details for the file sinapsis_doctr-0.1.7-py3-none-any.whl.
File metadata
- Download URL: sinapsis_doctr-0.1.7-py3-none-any.whl
- Upload date:
- Size: 20.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.5.16
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a991e2129d822a4704c950d54049cd17902ffeb9473a12757c5349c50c89dd38
|
|
| MD5 |
638d5d25d418603bb7582721602b7115
|
|
| BLAKE2b-256 |
7532d013e647b7454117b0844b8d04034336bec8e31526509ad61ba16828abbd
|