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@ -0,0 +1,20 @@
version: 2.1
jobs:
black:
parameters:
python-version:
type: string
docker:
- image: cimg/python:<< parameters.python-version >>
steps:
- checkout
- run: pip3 install --upgrade pip
- run: pip3 install black
- run: black .
workflows:
black:
jobs:
- black:
python-version: "3.11"

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

@ -15,7 +15,7 @@ indent_size = 2
[*.json]
indent_size = 2
insert_final_newline = true
insert_final_newline = false
# trailing spaces in markdown indicate word wrap
[*.md]

@ -17,7 +17,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Upgrade pip
run: python3 -m pip install --upgrade pip
- name: Install setuptools
@ -32,7 +32,7 @@ jobs:
- name: Build package
run: python3 -m pip install --upgrade build && python3 -m build
- name: Upload dist
uses: actions/upload-artifact@v4
uses: actions/upload-artifact@v3
with:
name: dist
path: dist/
@ -42,7 +42,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Download dist
uses: actions/download-artifact@v4
uses: actions/download-artifact@v3
with:
name: dist
path: dist/
@ -61,7 +61,7 @@ jobs:
id-token: write # IMPORTANT: this permission is mandatory for trusted publishing
steps:
- name: Download dist
uses: actions/download-artifact@v4
uses: actions/download-artifact@v3
with:
name: dist
path: dist/

@ -1,4 +1,4 @@
name: 'Test'
name: test
on:
@ -6,10 +6,6 @@ on:
branches:
- master
pull_request:
branches:
- master
schedule:
- cron: "00 16 07 * *" # = monthly
@ -25,27 +21,30 @@ jobs:
strategy:
fail-fast: false
matrix:
python-version: [ "3.8", "3.9", "3.10", "3.11", "3.12", "3.13" ]
python-version: [ "3.6", "3.7", "3.8", "3.9", "3.10", "3.11" ]
runs-on: "ubuntu-latest"
# For Python 3.6, we need to fall back to Ubuntu 20.04
runs-on: ${{ matrix.python-version == '3.6' && 'ubuntu-20.04' || 'ubuntu-latest' }}
env:
test_results_dir: test-results-${{ matrix.python-version }}
steps:
- name: Set up Python
uses: actions/setup-python@v5
uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
allow-prereleases: true
- name: Checkout
uses: actions/checkout@v4
- name: Install possible lxml build requirements (if building from source)
run: sudo apt-get install -y libxml2-dev libxslt-dev python3-dev
- name: Install possible shapely build requirements (if building from source)
run: sudo apt-get install -y libgeos-dev
uses: actions/checkout@v3
- name: Update pip
run: python3 -m pip install -U pip
- name: Avoid compiling OpenCV and NumPy on Python 3.6
run: |
if python3 --version | grep -q "Python 3.6"; then
pip install --prefer-binary -U opencv-python-headless numpy
fi
- name: Install requirements*.txt
run: |
for requirements_txt in requirements*.txt; do
@ -55,10 +54,19 @@ jobs:
- name: Test
run: |
cd src
python3 -m pytest --junitxml=../${{matrix.python-version}}-junit.xml -o junit_family=legacy
mkdir -p ../$test_results_dir
python3 -m pytest --junitxml=../$test_results_dir/junit.xml -o junit_family=legacy
- name: Upload test results
uses: actions/upload-artifact@v4
uses: actions/upload-artifact@v3
if: success() || failure()
with:
name: ${{ env.test_results_dir }}
path: ${{ env.test_results_dir }}
- name: Report tests
uses: dorny/test-reporter@v1
if: success() || failure()
with:
name: test-results-${{matrix.python-version}}
path: ${{matrix.python-version}}-junit.xml
name: Results on Python ${{ matrix.python-version }}
path: "${{env.test_results_dir }}/junit.xml"
reporter: java-junit

@ -1,20 +0,0 @@
name: 'Test - Report results'
on:
workflow_run:
workflows: ['test']
types:
- completed
permissions:
contents: read
actions: read
checks: write
jobs:
report:
runs-on: ubuntu-latest
steps:
- uses: dorny/test-reporter@v1
with:
artifact: /test-results-(.*)/
name: 'test - Results ($1)'
path: '*junit.xml'
reporter: java-junit

2
.gitignore vendored

@ -25,8 +25,6 @@ dmypy.json
# User-specific stuff
.idea
.*.swp
# Build artifacts
/build
/dist

@ -1,16 +0,0 @@
variables:
http_proxy: "http://http-proxy.sbb.spk-berlin.de:3128/"
https_proxy: "http://http-proxy.sbb.spk-berlin.de:3128/"
HTTP_PROXY: "http://http-proxy.sbb.spk-berlin.de:3128/"
HTTPS_PROXY: "http://http-proxy.sbb.spk-berlin.de:3128/"
stages:
- triggers
mirror:
stage: triggers
trigger:
include: .gitlab/mirror.yml
strategy: depend
rules:
- if: $CI_COMMIT_BRANCH == $CI_DEFAULT_BRANCH

@ -1,47 +0,0 @@
stages:
- check
- pull
- push
default:
image: debian
check:
stage: check
script:
- whoami; env
- if [ -z "$CI_COMMIT_BRANCH" ]; then echo "Not on a branch" >&2; exit 3; fi
pull-gitlab:
stage: pull
script:
- echo "This is redundant"
pull-github:
stage: pull
before_script:
- apt-get update && apt-get install -y git && rm -rf /var/lib/apt/lists/*
script:
- git remote remove github 2>/dev/null || true
- git remote add github https://github.com/qurator-spk/dinglehopper.git
- git remote -v
- git pull github "$CI_COMMIT_BRANCH"
push-gitlab:
stage: push
before_script:
- apt-get update && apt-get install -y git && rm -rf /var/lib/apt/lists/*
script:
- git push origin "$CI_COMMIT_SHA":"$CI_COMMIT_BRANCH"
push-github:
stage: push
before_script:
- apt-get update && apt-get install -y git && rm -rf /var/lib/apt/lists/*
script:
- git push github "$CI_COMMIT_SHA":"$CI_COMMIT_BRANCH"

@ -1,6 +1,8 @@
# See https://pre-commit.com for more information
# See https://pre-commit.com/hooks.html for more hooks
repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v5.0.0
rev: v3.2.0
hooks:
- id: trailing-whitespace
- id: end-of-file-fixer
@ -11,37 +13,17 @@ repos:
- id: check-ast
- repo: https://github.com/psf/black
rev: 25.1.0
rev: 22.10.0
hooks:
- id: black
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.11.7
rev: v0.0.280
hooks:
- args:
- --fix
- --exit-non-zero-on-fix
id: ruff
- id: ruff
args: [--fix, --exit-non-zero-on-fix]
- repo: https://github.com/pre-commit/mirrors-mypy
rev: v1.15.0
rev: v1.4.1
hooks:
- additional_dependencies:
- types-setuptools
- types-lxml
- numpy # for numpy plugin
- attrs
- multimethod
- rapidfuzz
id: mypy
- repo: https://gitlab.com/vojko.pribudic.foss/pre-commit-update
rev: v0.6.1
hooks:
- id: pre-commit-update
- repo: https://github.com/dhatim/python-license-check
rev: 0.9.2
hooks:
- id: liccheck
language: system
- id: mypy

@ -1,38 +0,0 @@
ARG DOCKER_BASE_IMAGE
FROM $DOCKER_BASE_IMAGE
ARG VCS_REF
ARG BUILD_DATE
LABEL \
maintainer="https://github.com/qurator-spk/dinglehopper/issues" \
org.label-schema.vcs-ref=$VCS_REF \
org.label-schema.vcs-url="https://github.com/qurator-spk/dinglehopper" \
org.label-schema.build-date=$BUILD_DATE \
org.opencontainers.image.vendor="Staatsbibliothek zu BerlinSPK" \
org.opencontainers.image.title="dinglehopper" \
org.opencontainers.image.description="An OCR evaluation tool" \
org.opencontainers.image.source="https://github.com/qurator-spk/dinglehopper" \
org.opencontainers.image.documentation="https://github.com/qurator-spk/dinglehopper/blob/${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 . .
COPY ocrd-tool.json .
# prepackage ocrd-tool.json as ocrd-all-tool.json
RUN ocrd ocrd-tool ocrd-tool.json dump-tools > $(dirname $(ocrd bashlib filename))/ocrd-all-tool.json
RUN make install && rm -rf /build/dinglehopper
WORKDIR /data
VOLUME /data

@ -186,7 +186,7 @@
same "printed page" as the copyright notice for easier
identification within third-party archives.
Copyright 2019-2025 Staatsbibliothek zu BerlinSPK
Copyright 2019 qurator
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.

@ -1,33 +0,0 @@
PYTHON = python3
PIP = pip3
PYTHONIOENCODING=utf8
PYTEST_ARGS = -vv
DOCKER_BASE_IMAGE = docker.io/ocrd/core:v3.3.0
DOCKER_TAG = ocrd/dinglehopper
help:
@echo
@echo " Targets"
@echo
@echo " install Install full Python package via pip"
@echo " docker Build the ocrd/dinglehopper docker image"
# Install Python package via pip
install:
$(PIP) install .
install-dev:
$(PIP) install -e .
test:
pytest $(PYTEST_ARGS)
docker:
docker build \
--build-arg DOCKER_BASE_IMAGE=$(DOCKER_BASE_IMAGE) \
--build-arg VCS_REF=$$(git rev-parse --short HEAD) \
--build-arg BUILD_DATE=$$(date -u +"%Y-%m-%dT%H:%M:%SZ") \
-t $(DOCKER_TAG) .
.PHONY: help install install-dev test docker

@ -10,7 +10,6 @@ pytest
```
## Test running examples
Only unit tests:
```bash
pytest -m "not integration"
@ -37,21 +36,9 @@ pytest -k "not test" --mypy
pytest -k "not test" --ruff
```
# How to use pre-commit
## How to use pre-commit
This project optionally uses [pre-commit](https://pre-commit.com) to check commits. To use it:
- Install pre-commit, e.g. `pip install -r requirements-dev.txt`
- Install the repo-local git hooks: `pre-commit install`
# Releasing a new version
- Update `ocrd-tool.json`
- `git commit`
- `git tag vx.y.z`
- `git push && git push --tags`
- The GitHub Actions workflow `release` will now create
a. a new release on GitHub and
b. a new release on PyPI
- Currently requires a review for PYPI?

@ -8,7 +8,7 @@ compares a ground truth (GT) document page with a OCR result page to compute
metrics and a word/character differences report. It also supports batch processing by
generating, aggregating and summarizing multiple reports.
[![Tests](https://github.com/qurator-spk/dinglehopper/actions/workflows/test.yml/badge.svg)](https://github.com/qurator-spk/dinglehopper/actions?query=workflow:"test")
[![Tests](https://github.com/qurator-spk/dinglehopper/workflows/test/badge.svg)](https://github.com/qurator-spk/dinglehopper/actions?query=workflow:"test")
[![GitHub tag](https://img.shields.io/github/tag/qurator-spk/dinglehopper?include_prereleases=&sort=semver&color=blue)](https://github.com/qurator-spk/dinglehopper/releases/)
[![License](https://img.shields.io/badge/License-Apache-blue)](#license)
[![issues - dinglehopper](https://img.shields.io/github/issues/qurator-spk/dinglehopper)](https://github.com/qurator-spk/dinglehopper/issues)
@ -23,11 +23,10 @@ Goals
Installation
------------
It's best to use pip to install the package from PyPI, e.g.:
```
pip install dinglehopper
```
It's best to use pip, e.g.:
~~~
sudo pip install .
~~~
Usage
-----
@ -100,11 +99,11 @@ This generates `summary.html` and `summary.json` in the same `output_folder`.
If you are summarizing many reports and have used the `--differences` flag while
generating them, it may be useful to limit the number of differences reported by using
the `--occurrences-threshold` parameter. This will reduce the size of the generated HTML
the `--occurences-threshold` parameter. This will reduce the size of the generated HTML
report, making it easier to open and navigate. Note that the JSON report will still
contain all differences. Example:
~~~
dinglehopper-summarize output_folder/ --occurrences-threshold 10
dinglehopper-summarize output_folder/ --occurences-threshold 10
~~~
### dinglehopper-line-dirs
@ -112,13 +111,9 @@ You also may want to compare a directory of GT text files (i.e. `gt/line0001.gt.
with a directory of OCR text files (i.e. `ocr/line0001.some-ocr.txt`) with a separate
CLI interface:
```
~~~
dinglehopper-line-dirs gt/ ocr/
```
The CLI `dinglehopper-line-dirs` can also work with GT text files in the same
directories as the the OCR text files. You should read `dinglehopper-line-dirs --help`
in this case.
~~~
### dinglehopper-extract
The tool `dinglehopper-extract` extracts the text of the given input file on

@ -7,10 +7,9 @@ authors = [
{name = "Mike Gerber", email = "mike.gerber@sbb.spk-berlin.de"},
{name = "The QURATOR SPK Team", email = "qurator@sbb.spk-berlin.de"},
]
description = "An OCR evaluation tool"
description = "The OCR evaluation tool"
readme = "README.md"
license.file = "LICENSE"
requires-python = ">=3.8"
requires-python = ">=3.6"
keywords = ["qurator", "ocr", "evaluation", "ocr-d"]
dynamic = ["version", "dependencies", "optional-dependencies"]
@ -49,7 +48,7 @@ optional-dependencies.dev = {file = ["requirements-dev.txt"]}
where = ["src"]
[tool.setuptools.package-data]
dinglehopper = ["templates/*", "*.json"]
dinglehopper = ["*.json", "templates/*"]
[tool.pytest.ini_options]
@ -61,54 +60,11 @@ markers = [
[tool.mypy]
plugins = ["numpy.typing.mypy_plugin"]
ignore_missing_imports = true
strict = true
disallow_subclassing_any = false
# ❗ error: Class cannot subclass "Processor" (has type "Any")
disallow_any_generics = false
disallow_untyped_defs = false
disallow_untyped_calls = false
[tool.ruff.lint]
[tool.ruff]
select = ["E", "F", "I"]
[tool.liccheck]
authorized_licenses = [
"bsd",
"new bsd",
"bsd license",
"new bsd license",
"simplified bsd",
"apache",
"apache 2.0",
"apache software license",
"apache software",
"apache license 2.0",
"gnu lgpl",
"lgpl with exceptions or zpl",
"GNU Library or Lesser General Public License (LGPL)",
"GNU Lesser General Public License v3 (LGPLv3)",
"GNU Lesser General Public License v2 or later (LGPLv2+)",
"mit",
"mit license",
"mit-cmu",
"python software foundation",
"psf",
"psf-2.0",
"Historical Permission Notice and Disclaimer (HPND)",
"public domain",
'The Unlicense (Unlicense)',
"isc",
"ISC License (ISCL)",
'Mozilla Public License 2.0 (MPL 2.0)',
]
unauthorized_licenses = [
"gpl v3",
ignore = [
"F811", # multimethods are considered redefinitions by ruff
]

@ -1,14 +1,8 @@
pytest
pytest-cov
pytest-mypy
black
pre-commit
ruff
pytest-ruff
mypy
types-lxml
types-setuptools
pytest-mypy
liccheck
ruff ; python_version >= "3.7"
pytest-ruff ; python_version >= "3.7"

@ -1,14 +1,14 @@
click
jinja2
lxml
uniseg >= 0.8.0
uniseg
numpy
colorama
MarkupSafe
ocrd >= 3.3.0
ocrd >= 2.20.1
attrs
multimethod >= 1.3
multimethod == 1.3 # latest version to officially support Python 3.5
tqdm
rapidfuzz >= 2.7.0
rapidfuzz >= 2.4.2
six # XXX workaround OCR-D/core#730
chardet
importlib_resources

@ -1,4 +1,4 @@
from .align import align, score_hint, seq_align
from .align import align, seq_align
from .character_error_rate import character_error_rate, character_error_rate_n
from .edit_distance import distance, editops
from .extracted_text import ExtractedText
@ -16,7 +16,6 @@ __all__ = [
"editops",
"distance",
"align",
"score_hint",
"seq_align",
"character_error_rate",
"character_error_rate_n",

@ -1,10 +1,8 @@
import math
import unicodedata
from math import ceil
from typing import Optional
from rapidfuzz.distance import Levenshtein
from uniseg.graphemecluster import grapheme_clusters
from .edit_distance import grapheme_clusters
def align(t1, t2):
@ -14,27 +12,11 @@ def align(t1, t2):
return seq_align(s1, s2)
def score_hint(er: float, n: int) -> Optional[int]:
"""Calculate RapidFuzz score hint for a given error rate and count.
Gives the score hint for the distance functions (= expected distance) or None if
the error rate is inf.
"""
assert not math.isnan(er)
try:
score_hint = int(ceil(er * n))
except (OverflowError, ValueError):
# ceil(er * n) can be inf or NaN (for n == 0), so int() can throw an
# OverflowError and a ValueError.
score_hint = None
return score_hint
def seq_align(s1, s2, score_hint=None):
def seq_align(s1, s2):
"""Align general sequences."""
s1 = list(s1)
s2 = list(s2)
ops = Levenshtein.editops(s1, s2, score_hint=score_hint)
ops = Levenshtein.editops(s1, s2)
i = 0
j = 0

@ -1,5 +1,7 @@
from __future__ import division
import unicodedata
from typing import List, Tuple, TypeVar
from typing import Tuple
from multimethod import multimethod
from uniseg.graphemecluster import grapheme_clusters
@ -7,13 +9,9 @@ from uniseg.graphemecluster import grapheme_clusters
from .edit_distance import distance
from .extracted_text import ExtractedText
T = TypeVar("T")
@multimethod
def character_error_rate_n(
reference: List[str], compared: List[str]
) -> Tuple[float, int]:
def character_error_rate_n(reference: str, compared: str) -> Tuple[float, int]:
"""
Compute character error rate.
@ -21,7 +19,7 @@ def character_error_rate_n(
"""
d = distance(reference, compared)
n = len(reference)
n = len(list(grapheme_clusters(unicodedata.normalize("NFC", reference))))
if d == 0:
return 0, n
@ -32,28 +30,18 @@ def character_error_rate_n(
# XXX Should we really count newlines here?
@character_error_rate_n.register
def _(reference: str, compared: str) -> Tuple[float, int]:
seq1 = list(grapheme_clusters(unicodedata.normalize("NFC", reference)))
seq2 = list(grapheme_clusters(unicodedata.normalize("NFC", compared)))
cer, n = character_error_rate_n(seq1, seq2)
return cer, n
@character_error_rate_n.register
def _(reference: ExtractedText, compared: ExtractedText) -> Tuple[float, int]:
cer, n = character_error_rate_n(
reference.grapheme_clusters, compared.grapheme_clusters
)
return cer, n
@multimethod
def character_error_rate_n(
reference: ExtractedText, compared: ExtractedText
) -> Tuple[float, int]:
return character_error_rate_n(reference.text, compared.text)
def character_error_rate(reference: T, compared: T) -> float:
def character_error_rate(reference, compared) -> float:
"""
Compute character error rate.
:return: character error rate
"""
cer: float
cer, _ = character_error_rate_n(reference, compared)
return cer

@ -1,13 +1,13 @@
import os
from collections import Counter
from typing import List
import click
from jinja2 import Environment, FileSystemLoader
from markupsafe import escape
from ocrd_utils import initLogging
from uniseg.graphemecluster import grapheme_clusters
from dinglehopper.align import score_hint, seq_align
from dinglehopper.align import seq_align
from dinglehopper.character_error_rate import character_error_rate_n
from dinglehopper.config import Config
from dinglehopper.extracted_text import ExtractedText
@ -15,9 +15,7 @@ from dinglehopper.ocr_files import extract
from dinglehopper.word_error_rate import word_error_rate_n, words_normalized
def gen_diff_report(
gt_in, ocr_in, css_prefix, joiner, none, *, differences=False, score_hint=None
):
def gen_diff_report(gt_in, ocr_in, css_prefix, joiner, none, differences=False):
gtx = ""
ocrx = ""
@ -44,8 +42,9 @@ def gen_diff_report(
if isinstance(gt_in, ExtractedText):
if not isinstance(ocr_in, ExtractedText):
raise TypeError()
gt_things = gt_in.grapheme_clusters
ocr_things = ocr_in.grapheme_clusters
# XXX splitting should be done in ExtractedText
gt_things = list(grapheme_clusters(gt_in.text))
ocr_things = list(grapheme_clusters(ocr_in.text))
else:
gt_things = gt_in
ocr_things = ocr_in
@ -54,7 +53,7 @@ def gen_diff_report(
o_pos = 0
found_differences = []
for k, (g, o) in enumerate(seq_align(gt_things, ocr_things, score_hint)):
for k, (g, o) in enumerate(seq_align(gt_things, ocr_things)):
css_classes = None
gt_id = None
ocr_id = None
@ -77,7 +76,7 @@ def gen_diff_report(
if o is not None:
o_pos += len(o)
counted_differences = dict(Counter(elem for elem in found_differences))
found_differences = dict(Counter(elem for elem in found_differences))
return (
"""
@ -88,7 +87,7 @@ def gen_diff_report(
""".format(
gtx, ocrx
),
counted_differences,
found_differences,
)
@ -106,56 +105,39 @@ def json_float(value):
def process(
gt: str,
ocr: str,
report_prefix: str,
reports_folder: str = ".",
gt,
ocr,
report_prefix,
reports_folder=".",
*,
metrics: bool = True,
differences: bool = False,
textequiv_level: str = "region",
plain_encoding: str = "autodetect",
) -> None:
metrics=True,
differences=False,
textequiv_level="region",
):
"""Check OCR result against GT.
The @click decorators change the signature of the decorated functions, so we keep
this undecorated version and use Click on a wrapper.
"""
gt_text = extract(
gt, textequiv_level=textequiv_level, plain_encoding=plain_encoding
)
ocr_text = extract(
ocr, textequiv_level=textequiv_level, plain_encoding=plain_encoding
)
gt_words: List[str] = list(words_normalized(gt_text))
ocr_words: List[str] = list(words_normalized(ocr_text))
gt_text = extract(gt, textequiv_level=textequiv_level)
ocr_text = extract(ocr, textequiv_level=textequiv_level)
assert isinstance(gt_text, ExtractedText)
assert isinstance(ocr_text, ExtractedText)
cer, n_characters = character_error_rate_n(gt_text, ocr_text)
wer, n_words = word_error_rate_n(gt_text, ocr_text)
char_diff_report, diff_c = gen_diff_report(
gt_text,
ocr_text,
css_prefix="c",
joiner="",
none="·",
score_hint=score_hint(cer, n_characters),
differences=differences,
gt_text, ocr_text, css_prefix="c", joiner="", none="·", differences=differences
)
# {gt,ocr}_words must not be a generator, so we don't drain it for the differences
# report.
assert isinstance(gt_words, list)
assert isinstance(ocr_words, list)
wer, n_words = word_error_rate_n(gt_words, ocr_words)
gt_words = words_normalized(gt_text)
ocr_words = words_normalized(ocr_text)
word_diff_report, diff_w = gen_diff_report(
gt_words,
ocr_words,
css_prefix="w",
joiner=" ",
none="",
score_hint=score_hint(wer, n_words),
differences=differences,
)
@ -192,16 +174,8 @@ def process(
def process_dir(
gt: str,
ocr: str,
report_prefix: str,
reports_folder: str = ".",
*,
metrics: bool = True,
differences: bool = False,
textequiv_level: str = "region",
plain_encoding: str = "autodetect",
) -> None:
gt, ocr, report_prefix, reports_folder, metrics, differences, textequiv_level
):
for gt_file in os.listdir(gt):
gt_file_path = os.path.join(gt, gt_file)
ocr_file_path = os.path.join(ocr, gt_file)
@ -215,7 +189,6 @@ def process_dir(
metrics=metrics,
differences=differences,
textequiv_level=textequiv_level,
plain_encoding=plain_encoding,
)
else:
print("Skipping {0} and {1}".format(gt_file_path, ocr_file_path))
@ -240,13 +213,7 @@ def process_dir(
help="PAGE TextEquiv level to extract text from",
metavar="LEVEL",
)
@click.option(
"--plain-encoding",
default="autodetect",
help='Encoding (e.g. "utf-8") of plain text files',
)
@click.option("--progress", default=False, is_flag=True, help="Show progress bar")
@click.version_option()
def main(
gt,
ocr,
@ -255,7 +222,6 @@ def main(
metrics,
differences,
textequiv_level,
plain_encoding,
progress,
):
"""
@ -290,10 +256,9 @@ def main(
ocr,
report_prefix,
reports_folder,
metrics=metrics,
differences=differences,
textequiv_level=textequiv_level,
plain_encoding=plain_encoding,
metrics,
differences,
textequiv_level,
)
else:
process(
@ -304,7 +269,6 @@ def main(
metrics=metrics,
differences=differences,
textequiv_level=textequiv_level,
plain_encoding=plain_encoding,
)

@ -12,12 +12,7 @@ from .ocr_files import extract
help="PAGE TextEquiv level to extract text from",
metavar="LEVEL",
)
@click.option(
"--plain-encoding",
default="autodetect",
help='Encoding (e.g. "utf-8") of plain text files',
)
def main(input_file, textequiv_level, plain_encoding):
def main(input_file, textequiv_level):
"""
Extract the text of the given INPUT_FILE.
@ -28,9 +23,7 @@ def main(input_file, textequiv_level, plain_encoding):
use "--textequiv-level line" to extract from the level of TextLine tags.
"""
initLogging()
input_text = extract(
input_file, textequiv_level=textequiv_level, plain_encoding=plain_encoding
).text
input_text = extract(input_file, textequiv_level=textequiv_level).text
print(input_text)

@ -1,53 +1,16 @@
import itertools
import os
from typing import Callable, Iterator, List, Optional, Tuple
import click
from jinja2 import Environment, FileSystemLoader
from ocrd_utils import initLogging
from .align import score_hint
from .character_error_rate import character_error_rate_n
from .cli import gen_diff_report, json_float
from .ocr_files import plain_extract
from .word_error_rate import word_error_rate_n, words_normalized
def removesuffix(text, suffix):
"""
Remove suffix from text.
Can be replaced with str.removesuffix when we only support Python >= 3.9.
"""
if suffix and text.endswith(suffix):
return text[: -len(suffix)]
return text
def is_hidden(filepath):
filename = os.path.basename(os.path.abspath(filepath))
return filename.startswith(".")
def find_all_files(
dir_: str, pred: Optional[Callable[[str], bool]] = None, return_hidden: bool = False
) -> Iterator[str]:
"""
Find all files in dir_, returning filenames
If pred is given, pred(filename) must be True for the filename.
Does not return hidden files by default.
"""
for root, _, filenames in os.walk(dir_):
for fn in filenames:
if not return_hidden and is_hidden(fn):
continue
if pred and not pred(fn):
continue
yield os.path.join(root, fn)
def all_equal(iterable):
g = itertools.groupby(iterable)
return next(g, True) and not next(g, False)
@ -61,63 +24,15 @@ def common_suffix(its):
return reversed(common_prefix(reversed(it) for it in its))
def find_gt_and_ocr_files(
gt_dir: str, gt_suffix: str, ocr_dir: str, ocr_suffix: str
) -> Iterator[Tuple[str, str]]:
"""
Find GT files and matching OCR files.
Returns pairs of GT and OCR files.
"""
for gt_fn in find_all_files(gt_dir, lambda fn: fn.endswith(gt_suffix)):
ocr_fn = os.path.join(
ocr_dir,
removesuffix(os.path.relpath(gt_fn, start=gt_dir), gt_suffix) + ocr_suffix,
)
if not os.path.exists(ocr_fn):
raise RuntimeError(f"{ocr_fn} (matching {gt_fn}) does not exist")
yield gt_fn, ocr_fn
def find_gt_and_ocr_files_autodetect(gt_dir, ocr_dir):
"""
Find GT files and matching OCR files, autodetect suffixes.
This only works if gt_dir (or respectivley ocr_dir) only contains GT (OCR)
files with a common suffix. Currently the files must have a suffix, e.g.
".gt.txt" (e.g. ".ocr.txt").
Returns pairs of GT and OCR files.
"""
# Autodetect suffixes
gt_files = find_all_files(gt_dir)
gt_suffix = "".join(common_suffix(gt_files))
if len(gt_suffix) == 0:
raise RuntimeError(
f"Files in GT directory {gt_dir} do not have a common suffix"
)
ocr_files = find_all_files(ocr_dir)
ocr_suffix = "".join(common_suffix(ocr_files))
if len(ocr_suffix) == 0:
raise RuntimeError(
f"Files in OCR directory {ocr_dir} do not have a common suffix"
)
yield from find_gt_and_ocr_files(gt_dir, gt_suffix, ocr_dir, ocr_suffix)
def removesuffix(text, suffix):
if suffix and text.endswith(suffix):
return text[: -len(suffix)]
return text
def process(
gt_dir,
ocr_dir,
report_prefix,
*,
metrics=True,
gt_suffix=None,
ocr_suffix=None,
plain_encoding="autodetect",
):
def process(gt_dir, ocr_dir, report_prefix, *, metrics=True):
gt_suffix = "".join(common_suffix(os.listdir(gt_dir)))
ocr_suffix = "".join(common_suffix(os.listdir(ocr_dir)))
cer = None
n_characters = None
@ -126,20 +41,14 @@ def process(
n_words = None
word_diff_report = ""
if gt_suffix is not None and ocr_suffix is not None:
gt_ocr_files = find_gt_and_ocr_files(gt_dir, gt_suffix, ocr_dir, ocr_suffix)
else:
gt_ocr_files = find_gt_and_ocr_files_autodetect(gt_dir, ocr_dir)
for k, gt in enumerate(os.listdir(gt_dir)):
# Find a match by replacing the suffix
ocr = removesuffix(gt, gt_suffix) + ocr_suffix
for k, (gt_fn, ocr_fn) in enumerate(gt_ocr_files):
gt_text = plain_extract(
gt_fn, include_filename_in_id=True, encoding=plain_encoding
)
gt_text = plain_extract(os.path.join(gt_dir, gt), include_filename_in_id=True)
ocr_text = plain_extract(
ocr_fn, include_filename_in_id=True, encoding=plain_encoding
os.path.join(ocr_dir, ocr), include_filename_in_id=True
)
gt_words: List[str] = list(words_normalized(gt_text))
ocr_words: List[str] = list(words_normalized(ocr_text))
# Compute CER
l_cer, l_n_characters = character_error_rate_n(gt_text, ocr_text)
@ -153,7 +62,7 @@ def process(
n_characters = n_characters + l_n_characters
# Compute WER
l_wer, l_n_words = word_error_rate_n(gt_words, ocr_words)
l_wer, l_n_words = word_error_rate_n(gt_text, ocr_text)
if wer is None:
wer, n_words = l_wer, l_n_words
else:
@ -163,21 +72,13 @@ def process(
# Generate diff reports
char_diff_report += gen_diff_report(
gt_text,
ocr_text,
css_prefix="l{0}-c".format(k),
joiner="",
none="·",
score_hint=score_hint(l_cer, l_n_characters),
)[0]
gt_text, ocr_text, css_prefix="l{0}-c".format(k), joiner="", none="·"
)
gt_words = words_normalized(gt_text)
ocr_words = words_normalized(ocr_text)
word_diff_report += gen_diff_report(
gt_words,
ocr_words,
css_prefix="l{0}-w".format(k),
joiner=" ",
none="",
score_hint=score_hint(l_wer, l_n_words),
)[0]
gt_words, ocr_words, css_prefix="l{0}-w".format(k), joiner=" ", none=""
)
env = Environment(
loader=FileSystemLoader(
@ -211,30 +112,17 @@ def process(
@click.option(
"--metrics/--no-metrics", default=True, help="Enable/disable metrics and green/red"
)
@click.option("--gt-suffix", help="Suffix of GT line text files")
@click.option("--ocr-suffix", help="Suffix of OCR line text files")
@click.option(
"--plain-encoding",
default="autodetect",
help='Encoding (e.g. "utf-8") of plain text files',
)
def main(gt, ocr, report_prefix, metrics, gt_suffix, ocr_suffix, plain_encoding):
def main(gt, ocr, report_prefix, metrics):
"""
Compare the GT line text directory against the OCR line text directory.
This assumes that the GT line text directory contains textfiles with a common
suffix like ".gt.txt", and the OCR line text directory contains textfiles with
a common suffix like ".some-ocr.txt". The text files also need to be paired,
i.e. the GT filename "line001.gt.txt" needs to match a filename
"line001.some-ocr.txt" in the OCR lines directory.
GT and OCR directories may contain line text files in matching subdirectories,
e.g. "GT/goethe_faust/line1.gt.txt" and "OCR/goethe_faust/line1.pred.txt".
GT and OCR directories can also be the same directory, but in this case you need
to give --gt-suffix and --ocr-suffix explicitly.
i.e. the GT file "line001.gt.txt" needs to match a file "line001.some-ocr.txt"
in the OCT lines directory.
The GT and OCR directories are usually ground truth line texts and the results of
The GT and OCR directories are usually round truth line texts and the results of
an OCR software, but you may use dinglehopper to compare two OCR results. In
that case, use --no-metrics to disable the then meaningless metrics and also
change the color scheme from green/red to blue.
@ -243,19 +131,9 @@ def main(gt, ocr, report_prefix, metrics, gt_suffix, ocr_suffix, plain_encoding)
$REPORT_PREFIX defaults to "report". The reports include the character error
rate (CER) and the word error rate (WER).
It is recommended to specify the encoding of the text files, for example with
--plain-encoding utf-8. If this option is not given, we try to auto-detect it.
"""
initLogging()
process(
gt,
ocr,
report_prefix,
metrics=metrics,
gt_suffix=gt_suffix,
ocr_suffix=ocr_suffix,
plain_encoding=plain_encoding,
)
process(gt, ocr, report_prefix, metrics=metrics)
if __name__ == "__main__":

@ -1,6 +1,5 @@
import json
import os
from typing import Dict
import click
from jinja2 import Environment, FileSystemLoader
@ -14,8 +13,8 @@ def process(reports_folder, occurrences_threshold=1):
wer_list = []
cer_sum = 0
wer_sum = 0
diff_c: Dict[str, int] = {}
diff_w: Dict[str, int] = {}
diff_c = {}
diff_w = {}
for report in os.listdir(reports_folder):
if report.endswith(".json"):
@ -35,15 +34,10 @@ def process(reports_folder, occurrences_threshold=1):
cer_sum += cer
wer_sum += wer
try:
for key, value in report_data["differences"][
"character_level"
].items():
for key, value in report_data["differences"]["character_level"].items():
diff_c[key] = diff_c.get(key, 0) + value
for key, value in report_data["differences"]["word_level"].items():
diff_w[key] = diff_w.get(key, 0) + value
except KeyError:
pass
if len(cer_list) == 0:
click.echo(f"No reports found in folder '{os.path.abspath(reports_folder)}'")

@ -1,5 +1,6 @@
from __future__ import division, print_function
import unicodedata
from typing import List
from multimethod import multimethod
from rapidfuzz.distance import Levenshtein
@ -9,18 +10,7 @@ from .extracted_text import ExtractedText
@multimethod
def distance(seq1: List[str], seq2: List[str]) -> int:
"""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)
@distance.register
def _(s1: str, s2: str) -> int:
def distance(s1: str, s2: str):
"""Compute the Levenshtein edit distance between two Unicode strings
Note that this is different from levenshtein() as this function knows about Unicode
@ -32,9 +22,9 @@ def _(s1: str, s2: str) -> int:
return Levenshtein.distance(seq1, seq2)
@distance.register
def _(s1: ExtractedText, s2: ExtractedText) -> int:
return Levenshtein.distance(s1.grapheme_clusters, s2.grapheme_clusters)
@multimethod
def distance(s1: ExtractedText, s2: ExtractedText):
return distance(s1.text, s2.text)
def editops(word1, word2):

@ -1,16 +1,14 @@
import enum
import functools
import re
import unicodedata
from contextlib import suppress
from itertools import repeat
from typing import Any, Dict, List, Optional
from typing import Optional
import attr
import numpy as np
from lxml import etree as ET
from ocrd_utils import getLogger
from uniseg.graphemecluster import grapheme_clusters
class Normalization(enum.Enum):
@ -122,7 +120,7 @@ class ExtractedText:
segment_id = attr.ib(type=Optional[str])
@segment_id.validator
def is_valid_segment_id(self, _, value):
def check(self, _, value):
if value is None:
return
if not re.match(r"[\w\d_-]+", value):
@ -132,85 +130,33 @@ class ExtractedText:
# a. _text itself
# b. or segments (ExtractedText) and a joiner
segments = attr.ib(type=Optional[List["ExtractedText"]])
segments = attr.ib(type=Optional[list], converter=attr.converters.optional(list))
joiner = attr.ib(type=Optional[str])
_text = attr.ib(type=Optional[str])
_grapheme_clusters = attr.ib(type=Optional[List[str]])
@segments.validator
def cant_set_both_segments_and_text(self, _, value):
def check(self, _, value):
if value is not None and self._text is not None:
raise ValueError("Can't have both segments and text")
@joiner.validator
def is_valid_joiner(self, _, value):
if self.segments is None:
if value is not None:
raise ValueError("Can't have joiner without segments to join")
if self.segments is not None:
if value not in ("", " ", "\n"):
raise ValueError(f"Unexpected segment joiner value {repr(value)}")
@_text.validator
def is_valid_text(self, _, value):
if value is None:
return
if self.segments is not None:
def check(self, _, value):
if value is not None and self.segments is not None:
raise ValueError("Can't have both segments and text")
if unicodedata.normalize("NFC", value) != value:
if value is not None and unicodedata.normalize("NFC", value) != value:
raise ValueError('String "{}" is not in NFC.'.format(value))
if normalize(value, self.normalization) != value:
if value is not None and normalize(value, self.normalization) != value:
raise ValueError('String "{}" is not normalized.'.format(value))
if self._grapheme_clusters is None:
raise ValueError("Requires both text and grapheme clusters to be set")
@_grapheme_clusters.validator
def are_valid_grapheme_clusters(self, _, value):
if value is not None and self._text is None:
raise ValueError("Requires both text and grapheme clusters to be set")
normalization = attr.ib(converter=Normalization, default=Normalization.NFC_SBB)
@property
def text(self) -> str:
def text(self):
if self._text is not None:
return self._text
else:
assert self.joiner is not None and self.segments is not None
return self.joiner.join(s.text for s in self.segments)
@functools.cached_property
def _joiner_grapheme_cluster(self):
"""We need the joiner as a list of 0 or 1 grapheme clusters.
This property is cached.
"""
assert self.joiner is not None
if len(self.joiner) > 0:
joiner_grapheme_cluster = list(grapheme_clusters(self.joiner))
assert len(joiner_grapheme_cluster) == 1 # see joiner's check above
elif len(self.joiner) == 0:
joiner_grapheme_cluster = []
else:
joiner_grapheme_cluster = None
return joiner_grapheme_cluster
@property
def grapheme_clusters(self):
if self._text is not None:
return self._grapheme_clusters
else:
# TODO Test with text extracted at glyph level (joiner == "")
clusters = []
assert self.segments is not None
for seg in self.segments:
clusters += seg.grapheme_clusters + self._joiner_grapheme_cluster
clusters = clusters[:-1]
return clusters
_segment_id_for_pos = None
def segment_id_for_pos(self, pos):
@ -221,7 +167,6 @@ class ExtractedText:
else:
# Recurse
segment_id_for_pos = []
assert self.joiner is not None and self.segments is not None
for s in self.segments:
seg_ids = [s.segment_id_for_pos(i) for i in range(len(s.text))]
segment_id_for_pos.extend(seg_ids)
@ -235,7 +180,7 @@ class ExtractedText:
return self._segment_id_for_pos[pos]
@classmethod
def from_text_segment(cls, text_segment, nsmap, *, textequiv_level="region"):
def from_text_segment(cls, text_segment, nsmap, textequiv_level="region"):
"""Build an ExtractedText from a PAGE content text element"""
localname_for_textequiv_level = {"region": "TextRegion", "line": "TextLine"}
@ -252,8 +197,7 @@ class ExtractedText:
# FIXME hardcoded SBB normalization
segment_text = normalize_sbb(segment_text)
segment_text = segment_text or ""
clusters = list(grapheme_clusters(segment_text))
return cls(segment_id, None, None, segment_text, clusters)
return cls(segment_id, None, None, segment_text)
else:
# Recurse
sub_localname = children_for_localname[localname]
@ -268,15 +212,12 @@ class ExtractedText:
)
)
joiner = joiner_for_textequiv_level[sub_textequiv_level]
return cls(segment_id, segments, joiner, None, None)
return cls(segment_id, segments, joiner, None)
@classmethod
def from_str(cls, text, normalization=Normalization.NFC_SBB):
normalized_text = normalize(text, normalization)
clusters = list(grapheme_clusters(normalized_text))
return cls(
None, None, None, normalized_text, clusters, normalization=normalization
)
return cls(None, None, None, normalized_text, normalization=normalization)
def invert_dict(d):
@ -284,7 +225,7 @@ def invert_dict(d):
return {v: k for k, v in d.items()}
def get_textequiv_unicode(text_segment: Any, nsmap: Dict[str, str]) -> str:
def get_textequiv_unicode(text_segment, nsmap) -> str:
"""Get the TextEquiv/Unicode text of the given PAGE text element."""
segment_id = text_segment.attrib["id"]
textequivs = text_segment.findall("./page:TextEquiv", namespaces=nsmap)
@ -308,7 +249,7 @@ def get_first_textequiv(textequivs, segment_id):
if np.any(~nan_mask):
if np.any(nan_mask):
log.warning("TextEquiv without index in %s.", segment_id)
index = int(np.nanargmin(indices))
index = np.nanargmin(indices)
else:
# try ordering by conf
confidences = np.array([get_attr(te, "conf") for te in textequivs], dtype=float)
@ -317,7 +258,7 @@ def get_first_textequiv(textequivs, segment_id):
"No index attributes, use 'conf' attribute to sort TextEquiv in %s.",
segment_id,
)
index = int(np.nanargmax(confidences))
index = np.nanargmax(confidences)
else:
# fallback to first entry in case of neither index or conf present
log.warning("No index attributes, use first TextEquiv in %s.", segment_id)
@ -325,11 +266,11 @@ def get_first_textequiv(textequivs, segment_id):
return textequivs[index]
def get_attr(te: Any, attr_name: str) -> float:
def get_attr(te, attr_name) -> float:
"""Extract the attribute for the given name.
Note: currently only handles numeric values!
Other or non existent values are encoded as np.nan.
Other or non existend values are encoded as np.nan.
"""
attr_value = te.attrib.get(attr_name)
try:

@ -22,7 +22,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"dinglehopper used to have its own (very inefficient) Levenshtein edit distance implementation, but now uses RapidFuzz."
"dinglehopper uses to have its own (very inefficient) Levenshtein edit distance implementation, but now uses RapidFuzz."
]
},
{
@ -391,7 +391,7 @@
"\\text{CER} = \\frac{i + s + d}{n}\n",
"$$\n",
"\n",
"where $i$ is the number of inserts, $s$ the number of substitutions, $d$ the number of deletions and $n$ is the number of characters in the reference text. (The text is not super clear about $n$ being the number of characters in the reference text, but it seems appropriate as they *are* clear about this when computing the word error rate.)"
"where $i$ is the number of inserts, $s$ the number of substitutions, $d$ the number of deletions and $n$ is the number of characters in the reference text. (The text is not super clear about $n$ being the number of characters in the reference text, but it seems appropiate as they *are* clear about this when computing the word error rate.)"
]
},
{
@ -680,7 +680,7 @@
" return cat in unwanted_categories or subcat in unwanted_subcategories\n",
"\n",
" # We follow Unicode Standard Annex #29 on Unicode Text Segmentation here: Split on word boundaries using\n",
" # uniseg.wordbreak.words() and ignore all \"words\" that contain only whitespace, punctuation \"or similar characters.\"\n",
" # uniseg.wordbreak.words() and ignore all \"words\" that contain only whitespace, punctation \"or similar characters.\"\n",
" for word in uniseg.wordbreak.words(s):\n",
" if all(unwanted(c) for c in word):\n",
" pass\n",

@ -1,56 +1,44 @@
from __future__ import division, print_function
import os
import sys
from typing import Dict, Iterator, Optional
from typing import Iterator
import chardet
from lxml import etree as ET
from lxml.etree import XMLSyntaxError
from ocrd_utils import getLogger
from uniseg.graphemecluster import grapheme_clusters
from .extracted_text import ExtractedText, normalize_sbb
log = getLogger("processor.OcrdDinglehopperEvaluate")
def alto_namespace(tree: ET._ElementTree) -> Optional[str]:
def alto_namespace(tree: ET.ElementTree) -> str:
"""Return the ALTO namespace used in the given ElementTree.
This relies on the assumption that, in any given ALTO file, the root element has the
local name "alto". We do not check if the file uses any valid ALTO namespace.
local name "alto". We do not check if the files uses any valid ALTO namespace.
"""
root_name = ET.QName(tree.getroot().tag)
if root_name.localname == "alto":
assert isinstance(root_name.namespace, str)
return root_name.namespace
else:
raise ValueError("Not an ALTO tree")
def alto_nsmap(tree: ET._ElementTree) -> Dict[str, str]:
alto_ns = alto_namespace(tree)
if alto_ns is None:
raise ValueError("Could not determine ALTO namespace")
return {"alto": alto_ns}
def alto_extract_lines(tree: ET._ElementTree) -> Iterator[ExtractedText]:
nsmap = alto_nsmap(tree)
def alto_extract_lines(tree: ET.ElementTree) -> Iterator[ExtractedText]:
nsmap = {"alto": alto_namespace(tree)}
for line in tree.iterfind(".//alto:TextLine", namespaces=nsmap):
line_id = line.attrib.get("ID")
line_text = " ".join(
string.attrib.get("CONTENT", "")
string.attrib.get("CONTENT")
for string in line.iterfind("alto:String", namespaces=nsmap)
)
normalized_text = normalize_sbb(line_text)
clusters = list(grapheme_clusters(normalized_text))
yield ExtractedText(line_id, None, None, normalized_text, clusters)
yield ExtractedText(line_id, None, None, normalize_sbb(line_text))
# FIXME hardcoded SBB normalization
def alto_extract(tree: ET._ElementTree) -> ExtractedText:
def alto_extract(tree: ET.ElementTree) -> ExtractedText:
"""Extract text from the given ALTO ElementTree."""
return ExtractedText(None, list(alto_extract_lines(tree)), "\n", None, None)
return ExtractedText(None, list(alto_extract_lines(tree)), "\n", None)
def alto_text(tree):
@ -99,7 +87,7 @@ def page_extract(tree, *, textequiv_level="region"):
# Filter empty region texts
regions = [r for r in regions if r.text != ""]
return ExtractedText(None, regions, "\n", None, None)
return ExtractedText(None, regions, "\n", None)
def extract_texts_from_reading_order_group(group, tree, nsmap, textequiv_level):
@ -109,7 +97,7 @@ def extract_texts_from_reading_order_group(group, tree, nsmap, textequiv_level):
if ET.QName(group.tag).localname in ["OrderedGroup", "OrderedGroupIndexed"]:
ro_children = list(group)
ro_children = [child for child in ro_children if "index" in child.attrib.keys()]
ro_children = filter(lambda child: "index" in child.attrib.keys(), ro_children)
ro_children = sorted(ro_children, key=lambda child: int(child.attrib["index"]))
elif ET.QName(group.tag).localname in ["UnorderedGroup", "UnorderedGroupIndexed"]:
ro_children = list(group)
@ -152,44 +140,33 @@ def detect_encoding(filename):
return chardet.detect(open(filename, "rb").read(1024))["encoding"]
def plain_extract(filename, include_filename_in_id=False, encoding="autodetect"):
def plain_extract(filename, include_filename_in_id=False):
id_template = "{filename} - line {no}" if include_filename_in_id else "line {no}"
def make_segment(no, line):
normalized_text = normalize_sbb(line)
clusters = list(grapheme_clusters(normalized_text))
fileencoding = detect_encoding(filename)
with open(filename, "r", encoding=fileencoding) as f:
return ExtractedText(
None,
[
ExtractedText(
id_template.format(filename=os.path.basename(filename), no=no),
None,
None,
normalized_text,
clusters,
normalize_sbb(line),
)
if encoding == "autodetect":
fileencoding = detect_encoding(filename)
log.warning(
f"Autodetected encoding as '{fileencoding}'"
", it is recommended to specify it explicitly with --plain-encoding"
)
else:
fileencoding = encoding
with open(filename, "r", encoding=fileencoding) as f:
return ExtractedText(
None,
[make_segment(no, line.strip()) for no, line in enumerate(f.readlines())],
for no, line in enumerate(f.readlines())
],
"\n",
None,
None,
)
# XXX hardcoded SBB normalization
def plain_text(filename, encoding="autodetect"):
return plain_extract(filename, encoding=encoding).text
def plain_text(filename):
return plain_extract(filename).text
def extract(filename, *, textequiv_level="region", plain_encoding="autodetect"):
def extract(filename, *, textequiv_level="region"):
"""Extract the text from the given file.
Supports PAGE, ALTO and falls back to plain text.
@ -197,7 +174,7 @@ def extract(filename, *, textequiv_level="region", plain_encoding="autodetect"):
try:
tree = ET.parse(filename)
except (XMLSyntaxError, UnicodeDecodeError):
return plain_extract(filename, encoding=plain_encoding)
return plain_extract(filename)
try:
return page_extract(tree, textequiv_level=textequiv_level)
except ValueError:

@ -1,13 +1,17 @@
{
"version": "0.11.0",
"version": "0.9.1",
"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"
],
@ -25,11 +29,6 @@
"enum": ["region", "line"],
"default": "region",
"description": "PAGE XML hierarchy level to extract the text from"
},
"plain_encoding": {
"type": "string",
"default": "autodetect",
"description": "Encoding (e.g. \"utf-8\") of plain text files"
}
}
}

@ -1,59 +1,63 @@
from functools import cached_property
import json
import os
from typing import Optional
import click
from ocrd_models import OcrdFileType
from ocrd import Processor
from ocrd.decorators import ocrd_cli_options, ocrd_cli_wrap_processor
from ocrd_utils import make_file_id
from ocrd_utils import assert_file_grp_cardinality, getLogger, make_file_id
from pkg_resources import resource_string
from .cli import process as cli_process
OCRD_TOOL = json.loads(resource_string(__name__, "ocrd-tool.json").decode("utf8"))
@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"]
super(OcrdDinglehopperEvaluate, self).__init__(*args, **kwargs)
@cached_property
def executable(self):
return 'ocrd-dinglehopper'
def process(self):
assert_file_grp_cardinality(self.input_file_grp, 2, "GT and OCR")
assert_file_grp_cardinality(self.output_file_grp, 1)
def process_page_file(self, *input_files: Optional[OcrdFileType]) -> None:
log = getLogger("processor.OcrdDinglehopperEvaluate")
assert self.parameter
metrics = self.parameter["metrics"]
textequiv_level = self.parameter["textequiv_level"]
plain_encoding = self.parameter["plain_encoding"]
gt_grp, ocr_grp = self.input_file_grp.split(",")
# wrong number of inputs: let fail
gt_file, ocr_file = input_files
# missing on either side: skip (zip_input_files already warned)
input_file_tuples = self.zip_input_files(on_error="abort")
for n, (gt_file, ocr_file) in enumerate(input_file_tuples):
if not gt_file or not ocr_file:
return
# missing download (i.e. OCRD_DOWNLOAD_INPUT=false):
if not gt_file.local_filename:
if config.OCRD_MISSING_INPUT == 'ABORT':
raise MissingInputFile(gt_file.fileGrp, gt_file.pageId, gt_file.mimetype)
return
if not ocr_file.local_filename:
if config.OCRD_MISSING_INPUT == 'ABORT':
raise MissingInputFile(ocr_file.fileGrp, ocr_file.pageId, ocr_file.mimetype)
return
# file/page was not found in this group
continue
gt_file = self.workspace.download_file(gt_file)
ocr_file = self.workspace.download_file(ocr_file)
page_id = gt_file.pageId
log.info("INPUT FILES %i / %s%s", n, gt_file, ocr_file)
file_id = make_file_id(ocr_file, self.output_file_grp)
report_prefix = os.path.join(self.output_file_grp, file_id)
# Process the files
try:
os.mkdir(self.output_file_grp)
except FileExistsError:
pass
cli_process(
gt_file.local_filename,
ocr_file.local_filename,
file_id,
self.output_file_grp,
report_prefix,
metrics=metrics,
textequiv_level=textequiv_level,
plain_encoding=plain_encoding,
)
# Add reports to the workspace
@ -61,16 +65,12 @@ class OcrdDinglehopperEvaluate(Processor):
[".html", "text/html"],
[".json", "application/json"],
]:
output_file_id = file_id + report_suffix
output_file = next(self.workspace.mets.find_files(ID=output_file_id), None)
if output_file and config.OCRD_EXISTING_OUTPUT != 'OVERWRITE':
raise FileExistsError(f"A file with ID=={output_file_id} already exists {output_file} and neither force nor ignore are set")
self.workspace.add_file(
file_id=output_file_id,
file_id=file_id + report_suffix,
file_grp=self.output_file_grp,
page_id=page_id,
mimetype=mimetype,
local_filename=file_id + report_suffix,
local_filename=report_prefix + report_suffix,
)

@ -138,17 +138,17 @@
<mets:fileSec>
<mets:fileGrp USE="OCR-D-GT-PAGE">
<mets:file MIMETYPE="application/xml" ID="OCR-D-GT-PAGE_00000024">
<mets:FLocat xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="OCR-D-GT-PAGE/00000024.page.xml" LOCTYPE="OTHER" OTHERLOCTYPE="FILE"/>
<mets:FLocat xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="OCR-D-GT-PAGE/00000024.page.xml"/>
</mets:file>
</mets:fileGrp>
<mets:fileGrp USE="OCR-D-OCR-CALAMARI">
<mets:file MIMETYPE="application/vnd.prima.page+xml" ID="OCR-D-OCR-CALAMARI_0001">
<mets:FLocat xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="OCR-D-OCR-CALAMARI/OCR-D-OCR-CALAMARI_0001.xml" LOCTYPE="OTHER" OTHERLOCTYPE="FILE"/>
<mets:FLocat xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="OCR-D-OCR-CALAMARI/OCR-D-OCR-CALAMARI_0001.xml"/>
</mets:file>
</mets:fileGrp>
<mets:fileGrp USE="OCR-D-OCR-TESS">
<mets:file MIMETYPE="application/vnd.prima.page+xml" ID="OCR-D-OCR-TESS_0001">
<mets:FLocat xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="OCR-D-OCR-TESS/OCR-D-OCR-TESS_0001.xml" LOCTYPE="OTHER" OTHERLOCTYPE="FILE"/>
<mets:FLocat xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="OCR-D-OCR-TESS/OCR-D-OCR-TESS_0001.xml"/>
</mets:file>
</mets:fileGrp>
</mets:fileSec>

@ -13,13 +13,12 @@ def test_text():
test1 = ExtractedText(
None,
[
ExtractedText("s0", None, None, "foo", grapheme_clusters("foo")),
ExtractedText("s1", None, None, "bar", grapheme_clusters("bar")),
ExtractedText("s2", None, None, "bazinga", grapheme_clusters("bazinga")),
ExtractedText("s0", None, None, "foo"),
ExtractedText("s1", None, None, "bar"),
ExtractedText("s2", None, None, "bazinga"),
],
" ",
None,
None,
)
assert test1.text == "foo bar bazinga"
@ -30,20 +29,8 @@ def test_text():
def test_normalization_check():
with pytest.raises(ValueError, match=r".*is not in NFC.*"):
ExtractedText(
"foo",
None,
None,
unicodedata.normalize("NFD", "Schlyñ"),
grapheme_clusters(unicodedata.normalize("NFD", "Schlyñ")),
)
assert ExtractedText(
"foo",
None,
None,
unicodedata.normalize("NFC", "Schlyñ"),
grapheme_clusters(unicodedata.normalize("NFC", "Schlyñ")),
)
ExtractedText("foo", None, None, unicodedata.normalize("NFD", "Schlyñ"))
assert ExtractedText("foo", None, None, unicodedata.normalize("NFC", "Schlyñ"))
AlignmentElement = namedtuple("AlignmentElement", "left right left_id right_id")
@ -60,27 +47,25 @@ def test_align():
test1 = ExtractedText(
None,
[
ExtractedText("s0", None, None, "foo", grapheme_clusters("foo")),
ExtractedText("s1", None, None, "bar", grapheme_clusters("bar")),
ExtractedText("s2", None, None, "batzinga", grapheme_clusters("batzinga")),
ExtractedText("s0", None, None, "foo"),
ExtractedText("s1", None, None, "bar"),
ExtractedText("s2", None, None, "batzinga"),
],
" ",
None,
None,
)
test2 = ExtractedText(
None,
[
ExtractedText("x0", None, None, "foo", grapheme_clusters("foo")),
ExtractedText("x1", None, None, "bar", grapheme_clusters("bar")),
ExtractedText("x0", None, None, "foo"),
ExtractedText("x1", None, None, "bar"),
# extra .
ExtractedText("x2", None, None, ".", grapheme_clusters(".")),
ExtractedText("x2", None, None, "."),
# deletion + different grapheme cluster, m̃ also is two Python characters
ExtractedText("x3", None, None, "bazim̃ga", grapheme_clusters("bazim̃ga")),
ExtractedText("x3", None, None, "bazim̃ga"),
],
" ",
None,
None,
)
left_pos = 0

@ -1,8 +1,6 @@
import math
import pytest
from .. import align, distance, score_hint, seq_align
from .. import align, distance, seq_align
from .util import unzip
@ -185,8 +183,3 @@ def test_lines_similar():
# Test __eq__ (i.e. is it a substitution or a similar string?)
assert list(left)[0] == list(right)[0]
def test_score_hint():
assert score_hint(0.5, 23) == 12 # int(ceil())
assert score_hint(math.inf, 12345) is None

@ -21,9 +21,9 @@ def test_cli_directory(tmp_path):
os.path.join(data_dir, "directory-test", "ocr"),
"report",
str(tmp_path / "reports"),
metrics=False,
differences=True,
textequiv_level="line",
False,
True,
"line",
)
assert os.path.exists(tmp_path / "reports/1.xml-report.json")
@ -45,9 +45,9 @@ def test_cli_fail_without_gt(tmp_path):
os.path.join(data_dir, "directory-test", "ocr"),
"report",
str(tmp_path / "reports"),
metrics=False,
differences=True,
textequiv_level="line",
False,
True,
"line",
)
assert len(os.listdir(tmp_path / "reports")) == 2 * 2

@ -1,61 +0,0 @@
import json
import os.path
import re
import pytest
from ..cli_line_dirs import process
from .util import working_directory
data_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "data")
@pytest.mark.integration
def test_cli_line_dirs_basic(tmp_path):
"""Test that the cli/process() produces a good report"""
with working_directory(tmp_path):
gt_dir = os.path.join(data_dir, "line_dirs/basic/gt")
ocr_dir = os.path.join(data_dir, "line_dirs/basic/ocr")
process(gt_dir, ocr_dir, "report")
with open("report.json", "r") as jsonf:
print(jsonf.read())
with open("report.json", "r") as jsonf:
j = json.load(jsonf)
assert j["cer"] == pytest.approx(0.1071429)
assert j["wer"] == pytest.approx(0.5)
@pytest.mark.integration
def test_cli_line_dirs_basic_report_diff(tmp_path):
"""Test that the cli/process() produces a report wiff char+word diff"""
with working_directory(tmp_path):
gt_dir = os.path.join(data_dir, "line_dirs/basic/gt")
ocr_dir = os.path.join(data_dir, "line_dirs/basic/ocr")
process(gt_dir, ocr_dir, "report")
with open("report.html", "r") as htmlf:
html_report = htmlf.read()
# Counting GT lines in the diff
assert len(re.findall(r"gt.*l\d+-cdiff", html_report)) == 2
assert len(re.findall(r"gt.*l\d+-wdiff", html_report)) == 2
@pytest.mark.integration
def test_cli_line_dirs_merged(tmp_path):
"""Test that the cli/process() produces a good report"""
with working_directory(tmp_path):
gt_dir = os.path.join(data_dir, "line_dirs/merged")
ocr_dir = os.path.join(data_dir, "line_dirs/merged")
process(
gt_dir, ocr_dir, "report", gt_suffix=".gt.txt", ocr_suffix=".some-ocr.txt"
)
with open("report.json", "r") as jsonf:
print(jsonf.read())
with open("report.json", "r") as jsonf:
j = json.load(jsonf)
assert j["cer"] == pytest.approx(0.1071429)
assert j["wer"] == pytest.approx(0.5)

@ -1,5 +1,4 @@
import json
import re
import pytest
@ -41,25 +40,3 @@ def test_cli_json_cer_is_infinity(tmp_path):
with open("report.json", "r") as jsonf:
j = json.load(jsonf)
assert j["cer"] == pytest.approx(float("inf"))
@pytest.mark.integration
def test_cli_html(tmp_path):
"""Test that the cli/process() yields complete HTML report"""
with working_directory(tmp_path):
with open("gt.txt", "w") as gtf:
gtf.write("AAAAA")
with open("ocr.txt", "w") as ocrf:
ocrf.write("AAAAB")
process("gt.txt", "ocr.txt", "report")
with open("report.html", "r") as htmlf:
html_report = htmlf.read()
print(html_report)
assert re.search(r"CER: 0\.\d+", html_report)
assert re.search(r"WER: 1\.0", html_report)
assert len(re.findall("gt.*cdiff", html_report)) == 1
assert len(re.findall("gt.*wdiff", html_report)) == 1

@ -1,35 +0,0 @@
from __future__ import division, print_function
import math
import pytest
from .. import character_error_rate, plain_text
from .util import working_directory
@pytest.mark.integration
@pytest.mark.parametrize(
"gt_file_content,ocr_file_content,cer_expected",
[
("", "Lorem ipsum", math.inf),
("Lorem ipsum", "", 1.0),
("\ufeff", "Lorem ipsum", math.inf),
("Lorem ipsum", "\ufeff", 1.0),
("", "", 0.0),
("\ufeff", "", 0.0),
("", "\ufeff", 0.0),
],
)
def test_empty_files(tmp_path, gt_file_content, ocr_file_content, cer_expected):
with working_directory(tmp_path):
with open("gt.txt", "w") as gtf:
gtf.write(gt_file_content)
with open("ocr.txt", "w") as ocrf:
ocrf.write(ocr_file_content)
gt_text = plain_text("gt.txt")
ocr_text = plain_text("ocr.txt")
assert character_error_rate(gt_text, ocr_text) == cer_expected

@ -34,8 +34,9 @@ def test_ocrd_cli(tmp_path):
"-O",
"OCR-D-OCR-CALAMARI-EVAL",
]
# Hack to satisfy ocrd_cli_wrap_processor() check for arguments
sys.argv[1:] = args
sys.argv[
1:
] = args # XXX Hack to satisfy ocrd_cli_wrap_processor() check for arguments
result = runner.invoke(ocrd_dinglehopper, args)
assert result.exit_code == 0
result_json = list((test_workspace_dir / "OCR-D-OCR-CALAMARI-EVAL").glob("*.json"))

@ -1,71 +0,0 @@
import os
from ..cli_line_dirs import find_gt_and_ocr_files, find_gt_and_ocr_files_autodetect
data_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "data")
def test_basic():
"""Test the dumb method: User gives directories and suffixes."""
pairs = list(
find_gt_and_ocr_files(
os.path.join(data_dir, "line_dirs/basic/gt"),
".gt.txt",
os.path.join(data_dir, "line_dirs/basic/ocr"),
".some-ocr.txt",
)
)
assert len(pairs) == 2
def test_basic_autodetect():
"""Test autodetect: User gives directories, suffixes are autodetected if possible"""
pairs = list(
find_gt_and_ocr_files_autodetect(
os.path.join(data_dir, "line_dirs/basic/gt"),
os.path.join(data_dir, "line_dirs/basic/ocr"),
)
)
assert len(pairs) == 2
def test_subdirs():
"""Test the dumb method: Should also work when subdirectories are involved."""
pairs = list(
find_gt_and_ocr_files(
os.path.join(data_dir, "line_dirs/subdirs/gt"),
".gt.txt",
os.path.join(data_dir, "line_dirs/subdirs/ocr"),
".some-ocr.txt",
)
)
assert len(pairs) == 2
def test_subdirs_autodetect():
"""Test the autodetect method: Should also work when subdirectories are involved."""
pairs = list(
find_gt_and_ocr_files_autodetect(
os.path.join(data_dir, "line_dirs/subdirs/gt"),
os.path.join(data_dir, "line_dirs/subdirs/ocr"),
)
)
assert len(pairs) == 2
def test_merged():
"""Test the dumb method: GT and OCR texts are in the same directories."""
pairs = list(
find_gt_and_ocr_files(
os.path.join(data_dir, "line_dirs/merged"),
".gt.txt",
os.path.join(data_dir, "line_dirs/merged"),
".some-ocr.txt",
)
)
assert len(pairs) == 2

@ -177,20 +177,8 @@ def test_text():
def test_plain(tmp_path):
with working_directory(tmp_path):
with open("ocr.txt", "w") as ocrf:
ocrf.write("First, a line.\nAnd a second line.\n")
ocrf.write("AAAAB")
result = plain_text("ocr.txt")
expected = "First, a line.\nAnd a second line."
assert result == expected
def test_plain_BOM(tmp_path):
"""Test that plain text files with BOM are read correctly."""
BOM = "\ufeff"
with working_directory(tmp_path):
with open("ocr.txt", "w") as ocrf:
ocrf.write(BOM + "First, a line.\nAnd a second line.\n")
result = plain_text("ocr.txt")
expected = "First, a line.\nAnd a second line."
expected = "AAAAB"
assert result == expected

@ -1,5 +1,7 @@
from __future__ import division
import unicodedata
from typing import Generator, Iterable, Tuple, TypeVar
from typing import Iterable, Tuple
import uniseg.wordbreak
from multimethod import multimethod
@ -7,8 +9,6 @@ from rapidfuzz.distance import Levenshtein
from .extracted_text import ExtractedText
T = TypeVar("T")
# Did we patch uniseg.wordbreak.word_break already?
word_break_patched = False
@ -21,17 +21,12 @@ def patch_word_break():
https://www.unicode.org/Public/UCD/latest/ucd/auxiliary/WordBreakProperty.txt
"""
old_word_break = uniseg.wordbreak.word_break
if hasattr(uniseg.wordbreak, 'Word_Break'):
aletter = uniseg.wordbreak.Word_Break.ALetter
else:
# uniseg<0.9
aletter = uniseg.wordbreak.WordBreak.ALETTER
def new_word_break(c):
def new_word_break(c, index=0):
if 0xE000 <= ord(c) <= 0xF8FF: # Private Use Area
return aletter
return "ALetter"
else:
return old_word_break(c)
return old_word_break(c, index)
uniseg.wordbreak.word_break = new_word_break
global word_break_patched
@ -39,7 +34,7 @@ def patch_word_break():
@multimethod
def words(s: str) -> Generator[str, None, None]:
def words(s: str):
"""Extract words from a string"""
global word_break_patched
@ -59,7 +54,7 @@ def words(s: str) -> Generator[str, None, None]:
# We follow Unicode Standard Annex #29 on Unicode Text Segmentation here: Split on
# word boundaries using uniseg.wordbreak.words() and ignore all "words" that contain
# only whitespace, punctuation "or similar characters."
# only whitespace, punctation "or similar characters."
for word in uniseg.wordbreak.words(s):
if all(unwanted(c) for c in word):
pass
@ -67,37 +62,37 @@ def words(s: str) -> Generator[str, None, None]:
yield word
@words.register
def _(s: ExtractedText) -> Generator[str, None, None]:
yield from words(s.text)
@multimethod
def words(s: ExtractedText):
return words(s.text)
@multimethod
def words_normalized(s: str) -> Generator[str, None, None]:
yield from words(unicodedata.normalize("NFC", s))
def words_normalized(s: str):
return words(unicodedata.normalize("NFC", s))
@words_normalized.register
def _(s: ExtractedText) -> Generator[str, None, None]:
yield from words_normalized(s.text)
@multimethod
def words_normalized(s: ExtractedText):
return words_normalized(s.text)
@multimethod
def word_error_rate_n(reference: str, compared: str) -> Tuple[float, int]:
reference_seq = list(words_normalized(reference))
compared_seq = list(words_normalized(compared))
wer, n = word_error_rate_n(reference_seq, compared_seq)
return wer, n
return word_error_rate_n(reference_seq, compared_seq)
@word_error_rate_n.register
def _(reference: ExtractedText, compared: ExtractedText) -> Tuple[float, int]:
wer, n = word_error_rate_n(reference.text, compared.text)
return wer, n
@multimethod
def word_error_rate_n(
reference: ExtractedText, compared: ExtractedText
) -> Tuple[float, int]:
return word_error_rate_n(reference.text, compared.text)
@word_error_rate_n.register
def _(reference: Iterable[T], compared: Iterable[T]) -> Tuple[float, int]:
@multimethod
def word_error_rate_n(reference: Iterable, compared: Iterable) -> Tuple[float, int]:
reference_seq = list(reference)
compared_seq = list(compared)
@ -111,7 +106,6 @@ def _(reference: Iterable[T], compared: Iterable[T]) -> Tuple[float, int]:
return d / n, n
def word_error_rate(reference: T, compared: T) -> float:
wer: float
def word_error_rate(reference, compared) -> float:
wer, _ = word_error_rate_n(reference, compared)
return wer

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