diff --git a/README.md b/README.md index fbb2bba3f6c83b6399200f42a2fd386dec5277c3..250f6a6b3292ff7a36477ca15007e367bfe79829 100644 --- a/README.md +++ b/README.md @@ -10,15 +10,21 @@ QuiVer Benchmarks is based on `ocrd/all:maximum` and has all OCR-D processors at - Docker >= 23.0.0 -To speed up QuiVer Benchmarks you can mount already downloaded text recognition models to `/usr/local/share/ocrd-resources/` in [`docker-compose.yml`](). -Otherwise the tool will download the models on each run. +To speed up QuiVer Benchmarks you can mount already downloaded text recognition models to `/usr/local/share/ocrd-resources/` in `docker-compose.yml` by adding + +```yml +- path/to/your/models:/usr/local/share/ocrd-resources/ +``` + +to the `volumes` section. +Otherwise the tool will download all `ocrd-tesserocr-recognize` models as well as `ocrd-calamari-recognize qurator-gt4histocr-1.0` on each run. ## Usage - clone this repository - [customize](#custom-workflows-and-data) QuiVer Benchmarks according to your needs - run `docker compose build && docker compose up` -- the benchmarks and the evaluation results will be available in `data/` +- the benchmarks and the evaluation results will be available at `data/workflows.json` on your host system ## Benchmarks Considered @@ -47,11 +53,17 @@ Add new OCR-D workflows to the directory `workflows/ocrd_worflows` according to - workflows have to be TXT files - all workflows have to use [`ocrd process`](https://ocr-d.de/en/user_guide#ocrd-process) -Since the `workflows` directory is mounted to the container spun up by `docker compose up` it is not necessary to rebuild the Docker image. +You can then either rebuild the Docker image via `docker compose build` or mount the directory to the container via + +```yml +- ./workflows/ocrd_workflows:/app/workflows/ocrd_workflows +``` + +and spin up a new run with `docker compose up`. ### Removing OCR-D Workflows -Delete the respective TXT files from `workflows/ocrd_workflows`. +Delete the respective TXT files from `workflows/ocrd_workflows` and either rebuild the image or mount the directory as volume as described [above](#adding-new-ocr-d-workflows). ### Using Custom Data