Canada Visa Form Extraction (CVFE) is a tool set to extract and transform Canada visa forms (IMM 5257 E and IMM 5645 E) into standard format.

pip install git+https://github.com/Nikronic/canada-visa-form-extraction.git

Or if you have cloned/downloaded the repository already, just use:

pip install .

We have provided a conda_env.yml (bare minimum) and conda_env_dev.yml (all packages including, tests, docs, and formatting) for ease of install using conda (or mamba). Please use:

conda env create -n YOUR_ENV_NAME --file conda_env.yml

Official Image: The easiest way is to just pull the official image from GitHub Container Registry:

docker pull ghcr.io/nikronic/cvfe:DESIRED_VERSION

For instance, for the version v0.2.1 (cat VERSION), you can pull docker pull ghcr.io/nikronic/cvfe:v0.2.1.

Then for running it, use:

docker run -p YOUR_HOST_PORT:CONTAINER_PORT ghcr.io/nikronic/cvfe:DESIRED_VERSION python -m cvfe.main --bind 0.0.0.0 --port CONTAINER_PORT

For example:

docker run -p 9999:8000 ghcr.io/nikronic/cvfe:v0.2.1 python -m cvfe.main --bind 0.0.0.0 --port 8000

note: All the images can be found on the repo packages.

Manual Image: We have provided a Dockerfile for ease of install using docker. Please use:

docker build -t cvfe .

For running it, you need to map the port 8000 of the container to your desired port (8001) on host:

docker run -p 8001:8000 cvfe

remark: note that we do not use mamba in Dockerfile as the complexity of the environment is small and the overhead of installing mamba itself might not worth it.

Using conda as the package manager is not necessary nor provides any advantages (of course virtual environment are necessary). Hence, if you like, you can install dependencies via conda. Note that only few of the dependencies are available on conda channels and you still need to use pip.

tip: You can use mamba to hugely speed up the installation process.

if conda:

conda create --name cvfe python=3.11 -y

Make sure you activate this environment right away: if conda:

conda activate cvfe

You should have at least pip >= 23.1.2

pip install --upgrade pip

pip install xmltodict>=0.13.0
pip install pikepdf>=5.1.5
pip install pypdf>=3.17.0
pip install python-dateutil>=2.8.1

These libraries (the main one is FastAPI) are not for the ML part and only are here to provide the API and web services.

pip install pydantic>=2.0.3
pip install fastapi>=0.100.0
pip install gunicorn>=21.2.0
pip install uvicorn>=0.23.1
pip install python-multipart>=0.0.6

[Optional] For making it online (only for development) using ngrok:

pip install pydantic-settings
pip install pyngrok

For using ngrok, start uvicorn server with your own args:

USE_NGROK=True python api.py --bind host --port port

Note that USE_NGROK=True has been handled by the code and you can use this flag to use ngrok (online) or not (offline). Also, you can use 0.0.0.0 for the host to listen on all interfaces. By default we use host=0.0.0.0 and port=8000.

Make sure you are in the root of the project, i.e. the same directory as the repo name. If you are in correct path, you should see setup.py containing information about cvfe.

pip install -e .

These section is about developers who want to work on the source directly and includes things such as setting up tests, formatting and so on.

for formatting our repo correctly without needing to check every time, I suggest using pre-commit to hijack commit and using black and isort on them.

pip install pre-commit

be sure we have pre-commit configs at .pre-commit-config.yaml than use

pre-commit install

pre-commit run --all-files

1. Visaland: They are using this project to convert already filled forms into a standard format to include it into their CRM and ERP.