Merge ba45129abf into 071e6a8bd1

.dockerignore

@@ -0,0 +1,5 @@
+src/dinglehopper/tests
+dist
+build
+*.egg-info
+.git

Dockerfile

@@ -6,17 +6,33 @@ LABEL \
     maintainer="https://github.com/qurator-spk/dinglehopper/issues" \
     org.label-schema.vcs-ref=$VCS_REF \
     org.label-schema.vcs-url="https://github.com/qurator-spk/dinglehopper" \
-    org.label-schema.build-date=$BUILD_DATE
+    org.label-schema.build-date=$BUILD_DATE \
+    org.opencontainers.image.vendor="DFG-Funded Initiative for Optical Character Recognition Development" \
+    org.opencontainers.image.title="dinglehopper" \
+    org.opencontainers.image.description="The OCR evaluation tool" \
+    org.opencontainers.image.source="https://github.com/qurator-spk/dinglehopper" \
+    org.opencontainers.image.documentation="https://github.com/qurator-spk/dinglehopper/blob/${VCS_REF}/README.md" \
+    org.opencontainers.image.revision=$VCS_REF \
+    org.opencontainers.image.created=$BUILD_DATE \
+    org.opencontainers.image.base.name=ocrd/core
+
+ENV LANG=C.UTF-8
+ENV LC_ALL=C.UTF-8
+
+# avoid HOME/.local/share (hard to predict USER here)
+# so let XDG_DATA_HOME coincide with fixed system location
+# (can still be overridden by derived stages)
+ENV XDG_DATA_HOME /usr/local/share
+# avoid the need for an extra volume for persistent resource user db
+# (i.e. XDG_CONFIG_HOME/ocrd/resources.yml)
+ENV XDG_CONFIG_HOME /usr/local/share/ocrd-resources
 
 WORKDIR /build/dinglehopper
-COPY pyproject.toml .
+COPY . .
-COPY src/dinglehopper/ocrd-tool.json .
+COPY ocrd-tool.json .
-COPY src ./src
+# prepackage ocrd-tool.json as ocrd-all-tool.json
-COPY requirements.txt .
+RUN ocrd ocrd-tool ocrd-tool.json dump-tools > $(dirname $(ocrd bashlib filename))/ocrd-all-tool.json
-COPY README.md .
+RUN make install && rm -rf /build/dinglehopper
-COPY Makefile .
-RUN make install
-RUN rm -rf /build/dinglehopper
 
 WORKDIR /data
-VOLUME ["/data"]
+VOLUME /data

Makefile

@@ -1,8 +1,9 @@
 PYTHON = python3
 PIP = pip3
 PYTHONIOENCODING=utf8
+PYTEST_ARGS = -vv
 
-DOCKER_BASE_IMAGE = docker.io/ocrd/core:v2.69.0
+DOCKER_BASE_IMAGE = docker.io/ocrd/core:v3.3.0
 DOCKER_TAG = ocrd/dinglehopper
 
 help:
@@ -16,6 +17,12 @@ help:
 install:
 	$(PIP) install .
 
+install-dev:
+	$(PIP) install -e .
+
+test:
+	pytest $(PYTEST_ARGS)
+
 docker:
 	docker build \
 	--build-arg DOCKER_BASE_IMAGE=$(DOCKER_BASE_IMAGE) \

requirements.txt

@@ -1,14 +1,16 @@
 click
 jinja2
 lxml
-uniseg >= 0.8.0
+# FIXME
+uniseg == 0.8.1
 numpy
 colorama
 MarkupSafe
-ocrd >= 2.65.0
+ocrd >= 3.3.0
 attrs
 multimethod >= 1.3
 tqdm
-rapidfuzz >= 2.7.0
+# FIXME
+rapidfuzz >= 2.7.0, < 3
 chardet
 importlib_resources

src/dinglehopper/character_error_rate.py

@@ -20,14 +20,7 @@ def character_error_rate_n(
     :return: character error rate and length of the reference
     """
 
-    d = distance(reference, compared)
+    return distance(reference, compared), len(reference)
-    n = len(reference)
-
-    if d == 0:
-        return 0, n
-    if n == 0:
-        return float("inf"), n
-    return d / n, n
 
     # XXX Should we really count newlines here?
 

src/dinglehopper/edit_distance.py

@@ -9,18 +9,18 @@ from .extracted_text import ExtractedText
 
 
 @multimethod
-def distance(seq1: List[str], seq2: List[str]) -> int:
+def distance(seq1: List[str], seq2: List[str]) -> float:
     """Compute the Levenshtein edit distance between two lists of grapheme clusters.
 
     This assumes that the grapheme clusters are already normalized.
 
     Use distance(str, str) instead if you need to compare two Unicode strings.
     """
-    return Levenshtein.distance(seq1, seq2)
+    return Levenshtein.normalized_distance(seq1, seq2)
 
 
 @distance.register
-def _(s1: str, s2: str) -> int:
+def _(s1: str, s2: str) -> float:
     """Compute the Levenshtein edit distance between two Unicode strings
 
     Note that this is different from levenshtein() as this function knows about Unicode
@@ -29,12 +29,12 @@ def _(s1: str, s2: str) -> int:
     """
     seq1 = list(grapheme_clusters(unicodedata.normalize("NFC", s1)))
     seq2 = list(grapheme_clusters(unicodedata.normalize("NFC", s2)))
-    return Levenshtein.distance(seq1, seq2)
+    return Levenshtein.normalized_distance(seq1, seq2)
 
 
 @distance.register
-def _(s1: ExtractedText, s2: ExtractedText) -> int:
+def _(s1: ExtractedText, s2: ExtractedText) -> float:
-    return Levenshtein.distance(s1.grapheme_clusters, s2.grapheme_clusters)
+    return Levenshtein.normalized_distance(s1.grapheme_clusters, s2.grapheme_clusters)
 
 
 def editops(word1, word2):

src/dinglehopper/ocrd-tool.json

@@ -1,17 +1,13 @@
 {
   "version": "0.9.7",
   "git_url": "https://github.com/qurator-spk/dinglehopper",
+  "dockerhub": "ocrd/dinglehopper",
   "tools": {
     "ocrd-dinglehopper": {
       "executable": "ocrd-dinglehopper",
+      "input_file_grp_cardinality": 2,
+      "output_file_grp_cardinality": 1,
       "description": "Evaluate OCR text against ground truth with dinglehopper",
-      "input_file_grp": [
-        "OCR-D-GT-PAGE",
-        "OCR-D-OCR"
-      ],
-      "output_file_grp": [
-        "OCR-D-OCR-EVAL"
-      ],
       "categories": [
         "Quality assurance"
       ],

src/dinglehopper/ocrd_cli.py

@@ -1,53 +1,43 @@
-import json
+from functools import cached_property
 import os
+from typing import Optional
 
 import click
-import importlib_resources
+from ocrd_models import OcrdFileType
 from ocrd import Processor
 from ocrd.decorators import ocrd_cli_options, ocrd_cli_wrap_processor
-from ocrd_utils import assert_file_grp_cardinality, getLogger, make_file_id
+from ocrd_utils import make_file_id
 
 from .cli import process as cli_process
 
-OCRD_TOOL = json.loads(
-    importlib_resources.files(__name__)
-    .joinpath("ocrd-tool.json")
-    .read_text(encoding="utf-8", errors="strict")
-)
-
-
 @click.command()
 @ocrd_cli_options
 def ocrd_dinglehopper(*args, **kwargs):
     return ocrd_cli_wrap_processor(OcrdDinglehopperEvaluate, *args, **kwargs)
 
-
 class OcrdDinglehopperEvaluate(Processor):
-    def __init__(self, *args, **kwargs):
-        kwargs["ocrd_tool"] = OCRD_TOOL["tools"]["ocrd-dinglehopper"]
-        kwargs["version"] = OCRD_TOOL["version"]
-        super(OcrdDinglehopperEvaluate, self).__init__(*args, **kwargs)
 
-    def process(self):
+    @cached_property
-        assert_file_grp_cardinality(self.input_file_grp, 2, "GT and OCR")
+    def executable(self):
-        assert_file_grp_cardinality(self.output_file_grp, 1)
+        return 'ocrd-dinglehopper'
 
-        log = getLogger("processor.OcrdDinglehopperEvaluate")
+    def process_page_file(self, *input_files: Optional[OcrdFileType]) -> None:
 
+        assert self.parameter
         metrics = self.parameter["metrics"]
         textequiv_level = self.parameter["textequiv_level"]
-        gt_grp, ocr_grp = self.input_file_grp.split(",")
 
-        input_file_tuples = self.zip_input_files(on_error="abort")
+        try:
-        for n, (gt_file, ocr_file) in enumerate(input_file_tuples):
+            gt_file, ocr_file = input_files
-            if not gt_file or not ocr_file:
+            assert gt_file, 'missing GT file'
-                # file/page was not found in this group
+            assert ocr_file, 'missing OCR file'
-                continue
+            assert gt_file.local_filename
-            gt_file = self.workspace.download_file(gt_file)
+            assert ocr_file.local_filename
-            ocr_file = self.workspace.download_file(ocr_file)
+        except (ValueError, AssertionError) as err:
-            page_id = gt_file.pageId
+            self.logger.warning(f'Missing either GT file, OCR file or both: {err}') # TODO how to log which page?
+            return
 
-            log.info("INPUT FILES %i / %s↔ %s", n, gt_file, ocr_file)
+        page_id = gt_file.pageId
 
         file_id = make_file_id(ocr_file, self.output_file_grp)
         report_prefix = os.path.join(self.output_file_grp, file_id)

src/dinglehopper/tests/test_character_error_rate.py

@@ -14,9 +14,9 @@ def test_character_error_rate():
     assert character_error_rate("Foo", "") == 3 / 3
 
     assert character_error_rate("", "") == 0
-    assert math.isinf(character_error_rate("", "Foo"))
+    assert character_error_rate("", "Foo") == 3 / 3
 
-    assert character_error_rate("Foo", "Food") == 1 / 3
+    assert character_error_rate("Foo", "Food") == 1 / 4
     assert character_error_rate("Fnord", "Food") == 2 / 5
     assert character_error_rate("Müll", "Mull") == 1 / 4
     assert character_error_rate("Abstand", "Sand") == 4 / 7

src/dinglehopper/tests/test_edit_distance.py

@@ -6,8 +6,8 @@ from .. import distance
 
 
 def test_distance():
-    assert distance("Fnord", "Food") == 2
+    assert distance("Fnord", "Food") == 2 / 5
-    assert distance("Müll", "Mull") == 1
+    assert distance("Müll", "Mull") == 1 / 4
 
     word1 = unicodedata.normalize("NFC", "Schlyñ")
     word2 = unicodedata.normalize("NFD", "Schlyñ")  # Different, decomposed!
@@ -21,4 +21,4 @@ def test_distance():
     assert (
         len(word2) == 7
     )  # This, OTOH, ends with LATIN SMALL LETTER M + COMBINING TILDE, 7 code points
-    assert distance(word1, word2) == 1
+    assert distance(word1, word2) == 1 / 6

src/dinglehopper/tests/test_integ_character_error_rate_ocr.py

@@ -56,4 +56,4 @@ def test_character_error_rate_between_page_alto_2():
         )
     )
 
-    assert character_error_rate(gt, ocr) == 8 / 591  # Manually verified
+    assert character_error_rate(gt, ocr) == 8 / 594  # Manually verified

src/dinglehopper/tests/test_integ_cli_valid_json.py

@@ -32,11 +32,11 @@ def test_cli_json_cer_is_infinity(tmp_path):
 
     with working_directory(tmp_path):
         with open("gt.txt", "w") as gtf:
-            gtf.write("")  # Empty to yield CER == inf
+            gtf.write("")
         with open("ocr.txt", "w") as ocrf:
             ocrf.write("Not important")
 
         process("gt.txt", "ocr.txt", "report")
         with open("report.json", "r") as jsonf:
             j = json.load(jsonf)
-            assert j["cer"] == pytest.approx(float("inf"))
+            assert j["cer"] == pytest.approx(1.0)

src/dinglehopper/tests/test_integ_edit_distance_ocr.py

@@ -17,7 +17,7 @@ def test_distance_between_page_files():
     # → 2 differences
     gt = page_text(ET.parse(os.path.join(data_dir, "test-gt.page2018.xml")))
     ocr = page_text(ET.parse(os.path.join(data_dir, "test-fake-ocr.page2018.xml")))
-    assert distance(gt, ocr) == 2
+    assert distance(gt, ocr) == 2 / 827
 
 
 @pytest.mark.integration
@@ -52,4 +52,4 @@ def test_distance_between_page_alto_2():
         )
     )
 
-    assert distance(gt, ocr) == 8  # Manually verified
+    assert distance(gt, ocr) == 8 / 594  # Manually verified

src/dinglehopper/tests/test_integ_empty_files.py

@@ -12,9 +12,9 @@ from .util import working_directory
 @pytest.mark.parametrize(
     "gt_file_content,ocr_file_content,cer_expected",
     [
-        ("", "Lorem ipsum", math.inf),
+        ("", "Lorem ipsum", 1.0),
         ("Lorem ipsum", "", 1.0),
-        ("\ufeff", "Lorem ipsum", math.inf),
+        ("\ufeff", "Lorem ipsum", 1.0),
         ("Lorem ipsum", "\ufeff", 1.0),
         ("", "", 0.0),
         ("\ufeff", "", 0.0),

src/dinglehopper/tests/test_integ_word_error_rate_ocr.py

@@ -64,5 +64,5 @@ def test_word_error_rate_between_page_alto_2():
     )
 
     assert (
-        word_error_rate(gt, ocr) == 7 / gt_word_count
+        word_error_rate(gt, ocr) == 7 / (gt_word_count + 1)
     )  # Manually verified, 6 words are wrong, 1 got split (=2 errors)

src/dinglehopper/tests/test_word_error_rate.py

@@ -76,7 +76,7 @@ def test_word_error_rate():
     )
 
     assert word_error_rate("Dies ist ein Beispielsatz!", "") == 4 / 4
-    assert math.isinf(word_error_rate("", "Dies ist ein Beispielsatz!"))
+    assert word_error_rate("", "Dies ist ein Beispielsatz!") == 4 / 4
     assert word_error_rate("", "") == 0
 
     assert (

src/dinglehopper/word_error_rate.py

@@ -96,15 +96,10 @@ def _(reference: Iterable[T], compared: Iterable[T]) -> Tuple[float, int]:
     reference_seq = list(reference)
     compared_seq = list(compared)
 
-    d = Levenshtein.distance(reference_seq, compared_seq)
+    d = Levenshtein.normalized_distance(reference_seq, compared_seq)
     n = len(reference_seq)
 
-    if d == 0:
+    return d, n
-        return 0, n
-    if n == 0:
-        return float("inf"), n
-    return d / n, n
-
 
 def word_error_rate(reference: T, compared: T) -> float:
     wer: float