From 5fb30a7a1f99830fafcaed700e1acf5116041cec Mon Sep 17 00:00:00 2001 From: "Gerber, Mike" Date: Mon, 9 Dec 2019 15:11:25 +0100 Subject: [PATCH] Revert "Merge branch 'master' of https://github.com/qurator-spk/sbb_textline_detector" This reverts commit 417b9235d55c0a98ebc665eeeed3844ed40a6c44, reversing changes made to a74974b7b68551135f77e9544fd6717dcaf762b8. --- .gitignore | 2 + LICENSE | 201 +++++++++++++++++++ README.md | 26 ++- qurator/sbb_textline_detector/main.py | 28 +-- qurator/sbb_textline_detector/ocrd-tool.json | 4 +- qurator/sbb_textline_detector/ocrd_cli.py | 4 +- requirements.txt | 4 +- setup.py | 2 +- 8 files changed, 235 insertions(+), 36 deletions(-) create mode 100644 .gitignore create mode 100644 LICENSE diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..3fafd07 --- /dev/null +++ b/.gitignore @@ -0,0 +1,2 @@ +__pycache__ +*.egg-info diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..261eeb9 --- /dev/null +++ b/LICENSE @@ -0,0 +1,201 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/README.md b/README.md index e7b28fd..46a8295 100644 --- a/README.md +++ b/README.md @@ -1,27 +1,25 @@ -# Textline-Recognition +# Textline Detection -*** -# Tool -This tool does textline detection of image and throw result as xml data. +## Introduction +This tool performs textline detection from document image data and returns the results as PAGE-XML. -# Models -In order to run this tool you need corresponding models. You can find them here: +## Installation -https://file.spk-berlin.de:8443/textline_detection/ - -# Installation - -sudo pip install . +`pip install .` -# Usage +## Models +In order to run this tool you also need trained models. You can download our pre-trained models from here: +https://file.spk-berlin.de:8443/textline_detection/ -sbb_textline_detector -i 'image file name' -o 'directory to write output xml' -m 'directory of models' +## Usage +`sbb_textline_detector -i -o -m ` ## Usage with OCR-D + ~~~ ocrd-example-binarize -I OCR-D-IMG -O OCR-D-IMG-BIN -ocrd_sbb_textline_detector -I OCR-D-IMG-BIN -O OCR-D-SEG-LINE-SBB \ +ocrd-sbb-textline-detector -I OCR-D-IMG-BIN -O OCR-D-SEG-LINE-SBB \ -p '{ "model": "/path/to/the/models/textline_detection" }' ~~~ diff --git a/qurator/sbb_textline_detector/main.py b/qurator/sbb_textline_detector/main.py index e70e475..7f1a425 100644 --- a/qurator/sbb_textline_detector/main.py +++ b/qurator/sbb_textline_detector/main.py @@ -34,11 +34,11 @@ with warnings.catch_warnings(): __doc__ = \ """ - tool to extract table form data from alto xml data + tool to extract text lines from document images """ -class textlineerkenner: +class textline_detector: def __init__(self, image_dir, dir_out, f_name, dir_models): self.image_dir = image_dir # XXX This does not seem to be a directory as the name suggests, but a file self.dir_out = dir_out @@ -70,7 +70,7 @@ class textlineerkenner: np.array([point for point in polygon.exterior.coords], dtype=np.uint)) return found_polygons_early - def filter_contours_area_of_image(self, image, contours, hirarchy, max_area, min_area): + def filter_contours_area_of_image(self, image, contours, hierarchy, max_area, min_area): found_polygons_early = list() jv = 0 @@ -81,13 +81,13 @@ class textlineerkenner: polygon = geometry.Polygon([point[0] for point in c]) area = polygon.area if area >= min_area * np.prod(image.shape[:2]) and area <= max_area * np.prod( - image.shape[:2]) and hirarchy[0][jv][3] == -1 : # and hirarchy[0][jv][3]==-1 : + image.shape[:2]) and hierarchy[0][jv][3] == -1 : # and hierarchy[0][jv][3]==-1 : found_polygons_early.append( np.array([ [point] for point in polygon.exterior.coords], dtype=np.uint)) jv += 1 return found_polygons_early - def filter_contours_area_of_image_interiors(self, image, contours, hirarchy, max_area, min_area): + def filter_contours_area_of_image_interiors(self, image, contours, hierarchy, max_area, min_area): found_polygons_early = list() jv = 0 @@ -98,7 +98,7 @@ class textlineerkenner: polygon = geometry.Polygon([point[0] for point in c]) area = polygon.area if area >= min_area * np.prod(image.shape[:2]) and area <= max_area * np.prod(image.shape[:2]) and \ - hirarchy[0][jv][3] != -1: + hierarchy[0][jv][3] != -1: # print(c[0][0][1]) found_polygons_early.append( np.array([point for point in polygon.exterior.coords], dtype=np.uint)) @@ -486,9 +486,9 @@ class textlineerkenner: _, thresh = cv2.threshold(imgray, 0, 255, 0) - contours, hirarchy = cv2.findContours(thresh.copy(), cv2.cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) + contours, hierarchy = cv2.findContours(thresh.copy(), cv2.cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) - main_contours = self.filter_contours_area_of_image(thresh, contours, hirarchy, max_area=1, min_area=0.00001) + main_contours = self.filter_contours_area_of_image(thresh, contours, hierarchy, max_area=1, min_area=0.00001) self.boxes = [] for jj in range(len(main_contours)): @@ -916,8 +916,8 @@ class textlineerkenner: image_box_tabels=image_box_tabels.astype(np.uint8) imgray = cv2.cvtColor(image_box_tabels, cv2.COLOR_BGR2GRAY) ret, thresh = cv2.threshold(imgray, 0, 255, 0) - contours,hierachy=cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE) - return contours,hierachy + contours,hierarchy=cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE) + return contours,hierarchy def find_contours_mean_y_diff(self,contours_main): M_main=[cv2.moments(contours_main[j]) for j in range(len(contours_main))] @@ -1236,9 +1236,9 @@ class textlineerkenner: # create the file structure data = ET.Element('PcGts') - data.set('xmlns',"http://schema.primaresearch.org/PAGE/gts/pagecontent/2017-07-15") + data.set('xmlns',"http://schema.primaresearch.org/PAGE/gts/pagecontent/2019-07-15") data.set('xmlns:xsi',"http://www.w3.org/2001/XMLSchema-instance") - data.set('xsi:schemaLocation',"http://schema.primaresearch.org/PAGE/gts/pagecontent/2017-07-15") + data.set('xsi:schemaLocation',"http://schema.primaresearch.org/PAGE/gts/pagecontent/2019-07-15") @@ -1378,7 +1378,7 @@ class textlineerkenner: def run(self): - #get image and sclaes, then extract the page of scanned image + #get image and scales, then extract the page of scanned image t1=time.time() self.get_image_and_scales() image_page,page_coord=self.extract_page() @@ -1475,7 +1475,7 @@ class textlineerkenner: def main(image, out, model): possibles = globals() # XXX unused? possibles.update(locals()) - x = textlineerkenner(image, out, None, model) + x = textline_detector(image, out, None, model) x.run() diff --git a/qurator/sbb_textline_detector/ocrd-tool.json b/qurator/sbb_textline_detector/ocrd-tool.json index b76f439..241f551 100644 --- a/qurator/sbb_textline_detector/ocrd-tool.json +++ b/qurator/sbb_textline_detector/ocrd-tool.json @@ -1,8 +1,8 @@ { "version": "0.0.1", "tools": { - "ocrd_sbb_textline_detector": { - "executable": "ocrd_sbb_textline_detector", + "ocrd-sbb-textline-detector": { + "executable": "ocrd-sbb-textline-detector", "description": "Detect lines", "steps": ["layout/segmentation/line"], "input_file_grp": [ diff --git a/qurator/sbb_textline_detector/ocrd_cli.py b/qurator/sbb_textline_detector/ocrd_cli.py index d090e46..272d671 100644 --- a/qurator/sbb_textline_detector/ocrd_cli.py +++ b/qurator/sbb_textline_detector/ocrd_cli.py @@ -12,7 +12,7 @@ from ocrd_models.ocrd_page_generateds import MetadataItemType, LabelsType, Label from ocrd_utils import concat_padded, getLogger, MIMETYPE_PAGE from pkg_resources import resource_string -from qurator.sbb_textline_detector import textlineerkenner +from qurator.sbb_textline_detector import textline_detector log = getLogger('processor.OcrdSbbTextlineDetectorRecognize') @@ -67,7 +67,7 @@ class OcrdSbbTextlineDetectorRecognize(Processor): # Segment the image image_file = self._resolve_image_file(input_file) model = self.parameter['model'] - x = textlineerkenner(image_file, tmp_dirname, file_id, model) + x = textline_detector(image_file, tmp_dirname, file_id, model) x.run() # Read segmentation results diff --git a/requirements.txt b/requirements.txt index 42de57a..9240226 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,5 +1,4 @@ -opencv-python -numpy +opencv-python-headless matplotlib seaborn tqdm @@ -8,5 +7,4 @@ shapely scikit-learn tensorflow-gpu < 2.0 scipy -click ocrd >= 2.0.0 diff --git a/setup.py b/setup.py index 1c9075f..92c88cf 100644 --- a/setup.py +++ b/setup.py @@ -24,7 +24,7 @@ setup( entry_points={ 'console_scripts': [ "sbb_textline_detector=qurator.sbb_textline_detector:main", - "ocrd_sbb_textline_detector=qurator.sbb_textline_detector:ocrd_sbb_textline_detector", + "ocrd-sbb-textline-detector=qurator.sbb_textline_detector:ocrd_sbb_textline_detector", ] }, python_requires='>=3.6.0',