👷🏾‍♂️ Use gt4histocr-calamari1/ as directory name for the Calmari 1 model

Makefile

@@ -11,7 +11,7 @@ help:
 	@echo "  Targets"
 	@echo ""
 	@echo "    install          Install ocrd_calamari"
-	@echo "    gt4histocr-calamari Get GT4HistOCR Calamari model (from SBB)"
+	@echo "    gt4histocr-calamari1 Get GT4HistOCR Calamari model (from SBB)"
 	@echo "    actevedef_718448162 Download example data"
 	@echo "    deps-test        Install testing python deps via pip"
 	@echo "    repo/assets      Clone OCR-D/assets to ./repo/assets"
@@ -34,9 +34,9 @@ install:
 
 
 # Get GT4HistOCR Calamari model (from SBB)
-gt4histocr-calamari:
-	mkdir gt4histocr-calamari
-	cd gt4histocr-calamari && \
+gt4histocr-calamari1:
+	mkdir -p gt4histocr-calamari1
+	cd gt4histocr-calamari1 && \
 	wget https://qurator-data.de/calamari-models/GT4HistOCR/2019-12-11T11_10+0100/model.tar.xz && \
 	tar xfv model.tar.xz && \
 	rm model.tar.xz
@@ -73,12 +73,12 @@ assets-clean:
 	rm -rf test/assets
 
 # Run unit tests
-test: test/assets gt4histocr-calamari
+test: test/assets gt4histocr-calamari1
 	# declare -p HTTP_PROXY
 	$(PYTHON) -m pytest --continue-on-collection-errors test $(PYTEST_ARGS)
 
 # Run unit tests and determine test coverage
-coverage: test/assets gt4histocr-calamari
+coverage: test/assets gt4histocr-calamari1
 	coverage erase
 	make test PYTHON="coverage run"
 	coverage report

README.md

@@ -41,8 +41,8 @@ pip install .
 Download models trained on GT4HistOCR data:
 
 ```
-make gt4histocr-calamari
-ls gt4histocr-calamari
+make gt4histocr-calamari1
+ls gt4histocr-calamari1
 ```
 
 ## Example Usage
@@ -50,7 +50,7 @@ Before using `ocrd-calamari-recognize` get some example data and model, and
 prepare the document for OCR:
 ```
 # Download model and example data
-make gt4histocr-calamari
+make gt4histocr-calamari1
 make actevedef_718448162
 
 # Create binarized images and line segmentation using other OCR-D projects
@@ -62,7 +62,7 @@ ocrd-tesserocr-segment-line -I OCR-D-SEG-REGION -O OCR-D-SEG-LINE
 
 Finally recognize the text using ocrd_calamari and the downloaded model:
 ```
-ocrd-calamari-recognize -p '{ "checkpoint": "../gt4histocr-calamari/*.ckpt.json" }' -I OCR-D-SEG-LINE -O OCR-D-OCR-CALAMARI
+ocrd-calamari-recognize -p '{ "checkpoint": "../gt4histocr-calamari1/*.ckpt.json" }' -I OCR-D-SEG-LINE -O OCR-D-OCR-CALAMARI
 ```
 
 You may want to have a look at the [ocrd-tool.json](ocrd_calamari/ocrd-tool.json) descriptions

test/test_recognize.py

@@ -14,7 +14,7 @@ from .base import assets
 
 METS_KANT = assets.url_of('kant_aufklaerung_1784-page-region-line-word_glyph/data/mets.xml')
 WORKSPACE_DIR = '/tmp/test-ocrd-calamari'
-CHECKPOINT = os.path.join(os.getcwd(), 'gt4histocr-calamari/*.ckpt.json')
+CHECKPOINT = os.path.join(os.getcwd(), 'gt4histocr-calamari1/*.ckpt.json')
 
 # Because XML namespace versions are so much fun, we not only use one, we use TWO!
 NSMAP = { "pc": "http://schema.primaresearch.org/PAGE/gts/pagecontent/2019-07-15" }