π Installation β’ π¦ Packages β’ π Features β’ π Usage example β’ π Webapp β’ π Documentation β’ π License
Sinapsis OCR provides powerful and flexible implementations for extracting text from images using different OCR engines. It enables users to easily configure and run OCR tasks with minimal setup.
This mono repo consists of different packages for OCR:
- sinapsis-doctr
- sinapsis-easyocr
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.techor with raw pip:
  pip install sinapsis-doctr --extra-index-url https://pypi.sinapsis.techChange the name of the package for the one you want to install.
Important
Templates in each package 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.techor with raw pip:
  pip install sinapsis-doctr[all] --extra-index-url https://pypi.sinapsis.techTip
You can also install all the packages within this project:
  uv pip install sinapsis-ocr[all] --extra-index-url https://pypi.sinapsis.techPackages summary
- 
Sinapsis DocTR - Uses the DocTR library for high-quality OCR with modern deep learning models
- Supports multiple detection and recognition architectures
- Provides detailed text extraction with bounding boxes and confidence scores
 
- 
Sinapsis EasyOCR - Leverages the EasyOCR library for simple yet effective OCR
- Supports multiple languages
- Extracts text with bounding boxes and confidence scores
 
Tip
Use CLI command sinapsis info --all-template-names to show a list with all the available Template names installed with Sinapsis OCR.
Tip
Use CLI command sinapsis info --example-template-config TEMPLATE_NAME to produce an example Agent config for the Template specified in TEMPLATE_NAME.
For example, for DocTROCRPrediction use sinapsis info --example-template-config DocTROCRPrediction to produce an example config.
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: datasetEasyOCR Example
agent:
  name: easyocr_inference
  description: agent to run inference with EasyOCR, 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: EasyOCR
  class_name: EasyOCR
  template_input: FolderImageDatasetCV2
  attributes: {}
- template_name: BBoxDrawer
  class_name: BBoxDrawer
  template_input: EasyOCR
  attributes:
    draw_confidence: True
    draw_extra_labels: True
- template_name: ImageSaver
  class_name: ImageSaver
  template_input: BBoxDrawer
  attributes:
    save_dir: output
    root_dir: datasetTo run, simply use:
sinapsis run name_of_the_config.ymlThe webapp provides a simple interface to extract text from images using 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 this repository:
git clone https://github.com/Sinapsis-ai/sinapsis-ocr.git
cd sinapsis-ocrNote
If you'd like to enable external app sharing in Gradio, export GRADIO_SHARE_APP=True
Tip
The agent configuration can be updated using the AGENT_CONFIG_PATH environment var.
For default uses the config for easy ocr but this can be chaged with:
AGENT_CONFIG_PATH=/app/packages/sinapsis_doctr/src/sinapsis_doctr/configs/doctr_demo.yaml
π³ 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 downπ» 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-ocr[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://127.0.0.1:7860NOTE: The url can be different, check the output of the terminal
- To stop the app press Control + Con the terminal
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
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.
