improve/update tests

Makefile

@@ -1,16 +1,17 @@
 # BEGIN-EVAL makefile-parser --make-help Makefile
 
+.PHONY: help install
 help:
 	@echo ""
 	@echo "  Targets"
 	@echo ""
 	@echo "    install  Install with pip"
-	@echo "    model    Downloads the pre-trained models from qurator-data.de"
+	@echo "    models   Downloads the pre-trained models from qurator-data.de"
 	@echo "    test     Run tests"
+	@echo "    clean    Remove copies/results in test/assets"
 	@echo ""
 	@echo "  Variables"
 	@echo ""
-	@echo "    MODEL_DIR  Directory to store models"
 
 # END-EVAL
 
@@ -19,11 +20,26 @@ install:
 	pip install .
 
 # Downloads the pre-trained models from qurator-data.de
-.PHONY: model
-model:
-	ocrd resmgr download --allow-uninstalled --location cwd ocrd-sbb-binarize default
+.PHONY: models
+models:
+	ocrd resmgr download ocrd-sbb-binarize "*"
+
+repo/assets:
+	git submodule update --init repo/assets
+
+# Setup test data
+test/assets: repo/assets
+	@mkdir -p $@
+	cp -r -t $@ repo/assets/data/*
 
 # Run tests
-test: model
-	ocrd-sbb-binarize -m repo/assets/data/kant_aufklaerung_1784/data/mets.xml -I OCR-D-IMG -O BIN -P model default
-	ocrd-sbb-binarize -m repo/assets/data/kant_aufklaerung_1784-page-region/data/mets.xml -I OCR-D-IMG -O BIN -P model default -P operation_level region
+.PHONY: test
+test: test/assets models
+	ocrd-sbb-binarize -m test/assets/kant_aufklaerung_1784/data/mets.xml -I OCR-D-IMG -O BIN -P model default
+	ocrd-sbb-binarize -m test/assets/kant_aufklaerung_1784/data/mets.xml -I OCR-D-IMG -O BIN2 -P model default-2021-03-09
+	ocrd-sbb-binarize -m test/assets/kant_aufklaerung_1784-page-region/data/mets.xml -g phys_0001 -I OCR-D-GT-SEG-REGION -O BIN -P model default -P operation_level region
+	ocrd-sbb-binarize -m test/assets/kant_aufklaerung_1784-page-region/data/mets.xml -g phys_0001 -I OCR-D-GT-SEG-REGION -O BIN2 -P model default-2021-03-09 -P operation_level region
+
+.PHONY: clean
+clean:
+	-$(RM) -fr test/assets

README.md

@@ -18,7 +18,7 @@ Clone the repository, enter it and run
 
 ### Models
 
-Pre-trained models in  `HDF5` format can be downloaded from here:   
+Pre-trained models in HDF5 format can be downloaded from here:
 
 https://qurator-data.de/sbb_binarization/
 
@@ -26,6 +26,11 @@ We also provide a Tensorflow `saved_model` via Huggingface:
 
 https://huggingface.co/SBB/sbb_binarization
 
+With [OCR-D](https://ocr-d.de/), you can use the [Resource Manager](Tensorflow SavedModel) to deploy models, e.g.
+
+    ocrd resmgr download ocrd-sbb-binarize "*"
+
+
 ## Usage
 
 ```sh
@@ -39,11 +44,22 @@ Images containing a lot of border noise (black pixels) should be cropped beforeh
 
 ### Example
 
-```sh
-sbb_binarize -m /path/to/model/ myimage.tif myimage-bin.tif
-```
 
-To use the [OCR-D](https://ocr-d.de/) interface:
-```sh
-ocrd-sbb-binarize --overwrite -I INPUT_FILE_GRP -O OCR-D-IMG-BIN -P model "/var/lib/sbb_binarization"
-```
+    sbb_binarize -m /path/to/model/ myimage.tif myimage-bin.tif
+
+
+To use the [OCR-D](https://ocr-d.de/en/spec/cli) interface:
+
+    ocrd-sbb-binarize -I INPUT_FILE_GRP -O OCR-D-IMG-BIN -P model default
+
+
+## Testing
+
+For simple smoke tests, the following will
+- download models
+- download test data
+- run the OCR-D wrapper (on page and region level):
+
+
+    make model
+    make test