If you are using MacOS, then run brew install poppler tesseract first.

1. Create and activate python virtual environment.
2. Run pip install -r requirements.txt to install dependencies.
3. Run download.sh to get the minimal set of files required to run inference.

1. Run docker build . -t badgerdoc-tb-extr
2. Use built image for example like this docker run -it badgerdoc-tb-extr bash

Or any other way

If you would like to download models from S3, Before running setup following environment variables for example with docker env file AWS_S3_ENDPOINT # S3 endpoint url AWS_ACCESS_KEY_ID # aws access key id AWS_SECRET_ACCESS_KEY # aws secret access key AWS_REGION # AWS region name AWS_S3_SSE_TYPE # AWS SSE type (optional)

python -m table_extractor.run run <path-to-pdf-or-excel> <results-output-dir> --model_path <model-file-path> --verbose <true/false> --paddle_on <true/false> Pipeline will automatically decide how parse your document based on file extension. Supported file formats: *.pdf, *.xlsx, *.xlsm, *.xltx, *.xltm

Model on S3 could be used if <model-file-path> provided in format s3://<bucket>/<models_path>

Run pipeline on single pdf document

python -m table_extractor.run run-sequentially <path-to-pdf> <results-output-dir> --model_path <model-file-path> --verbose <true/false> --paddle_on <true/false>

Model on S3 could be used if <model-file-path> provided in format s3://<bucket>/<models_path>

python -m excel_extractor.excel_run <path-to-excel> <output-path>