Merge pull request #138 from qurator-spk/extracting_images_only

Extracting images only

.github/workflows/test-eynollah.yml

@@ -1,7 +1,7 @@
 # This workflow will install Python dependencies, run tests and lint with a variety of Python versions
 # For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
 
-name: Python package
+name: Test
 
 on: [push]
 
@@ -14,8 +14,8 @@ jobs:
         python-version: ['3.8', '3.9', '3.10', '3.11']
 
     steps:
-    - uses: actions/checkout@v2
-    - uses: actions/cache@v2
+    - uses: actions/checkout@v4
+    - uses: actions/cache@v4
       id: model_cache
       with:
         path: models_eynollah
@@ -24,7 +24,7 @@ jobs:
       if: steps.model_cache.outputs.cache-hit != 'true'
       run: make models
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies

CHANGELOG.md

@@ -5,6 +5,14 @@ Versioned according to [Semantic Versioning](http://semver.org/).
 
 ## Unreleased
 
+## [0.3.1] - 2024-08-27
+
+Fixed:
+
+  * regression in OCR-D processor, #106
+  * Expected Ptrcv::UMat for argument 'contour', #110
+  * Memory usage explosion with very narrow images (e.g. book spine), #67
+
 ## [0.3.0] - 2023-05-13
 
 Changed:
@@ -117,6 +125,8 @@ Fixed:
 Initial release
 
 <!-- link-labels -->
+[0.3.1]: ../../compare/v0.3.1...v0.3.0
+[0.3.0]: ../../compare/v0.3.0...v0.2.0
 [0.2.0]: ../../compare/v0.2.0...v0.1.0
 [0.1.0]: ../../compare/v0.1.0...v0.0.11
 [0.0.11]: ../../compare/v0.0.11...v0.0.10

Makefile

@@ -22,16 +22,14 @@ help:
 models: models_eynollah
 
 models_eynollah: models_eynollah.tar.gz
-	# tar xf models_eynollah_renamed.tar.gz --transform 's/models_eynollah_renamed/models_eynollah/'
-	# tar xf models_eynollah_renamed.tar.gz
-	# tar xf 2022-04-05.SavedModel.tar.gz --transform 's/models_eynollah_renamed/models_eynollah/'
 	tar xf models_eynollah.tar.gz
 
 models_eynollah.tar.gz:
 	# wget 'https://qurator-data.de/eynollah/2021-04-25/models_eynollah.tar.gz'
 	# wget 'https://qurator-data.de/eynollah/2022-04-05/models_eynollah_renamed.tar.gz'
-	# wget 'https://ocr-d.kba.cloud/2022-04-05.SavedModel.tar.gz'
-	wget https://github.com/qurator-spk/eynollah/releases/download/v0.3.0/models_eynollah.tar.gz
+	# wget 'https://qurator-data.de/eynollah/2022-04-05/models_eynollah_renamed_savedmodel.tar.gz'
+	# wget 'https://github.com/qurator-spk/eynollah/releases/download/v0.3.0/models_eynollah.tar.gz'
+	wget 'https://github.com/qurator-spk/eynollah/releases/download/v0.3.1/models_eynollah.tar.gz'
 
 # Install with pip
 install:

README.md

@@ -1,10 +1,10 @@
 # Eynollah
-> Document Layout Analysis (segmentation) using pre-trained models and heuristics
+> Document Layout Analysis with Deep Learning and Heuristics
 
 [![PyPI Version](https://img.shields.io/pypi/v/eynollah)](https://pypi.org/project/eynollah/)
-[![CircleCI Build Status](https://circleci.com/gh/qurator-spk/eynollah.svg?style=shield)](https://circleci.com/gh/qurator-spk/eynollah)
 [![GH Actions Test](https://github.com/qurator-spk/eynollah/actions/workflows/test-eynollah.yml/badge.svg)](https://github.com/qurator-spk/eynollah/actions/workflows/test-eynollah.yml)
 [![License: ASL](https://img.shields.io/github/license/qurator-spk/eynollah)](https://opensource.org/license/apache-2-0/)
+[![DOI](https://img.shields.io/badge/DOI-10.1145%2F3604951.3605513-red)](https://doi.org/10.1145/3604951.3605513)
 
 ![](https://user-images.githubusercontent.com/952378/102350683-8a74db80-3fa5-11eb-8c7e-f743f7d6eae2.jpg)
 
@@ -14,16 +14,18 @@
 * Support for various image optimization operations:
   * cropping (border detection), binarization, deskewing, dewarping, scaling, enhancing, resizing
 * Text line segmentation to bounding boxes or polygons (contours) including for curved lines and vertical text
-* Detection of reading order
+* Detection of reading order (left-to-right or right-to-left)
 * Output in [PAGE-XML](https://github.com/PRImA-Research-Lab/PAGE-XML)
 * [OCR-D](https://github.com/qurator-spk/eynollah#use-as-ocr-d-processor) interface
 
+:warning: Development is currently focused on achieving the best possible quality of results for a wide variety of historical documents and therefore processing can be very slow. We aim to improve this, but contributions are welcome.
+
 ## Installation
-Python versions `3.8-3.11` with Tensorflow versions >=`2.12` are currently supported. 
+Python `3.8-3.11` with Tensorflow `2.12-2.15` on Linux are currently supported.
 
 For (limited) GPU support the CUDA toolkit needs to be installed.
 
-You can either install via 
+You can either install from PyPI
 
 ```
 pip install eynollah
@@ -39,45 +41,49 @@ cd eynollah; pip install -e .
 Alternatively, you can run `make install` or `make install-dev` for editable installation.
 
 ## Models
-Pre-trained models can be downloaded from [qurator-data.de](https://qurator-data.de/eynollah/).
+Pre-trained models can be downloaded from [qurator-data.de](https://qurator-data.de/eynollah/) or [huggingface](https://huggingface.co/SBB?search_models=eynollah). 
 
-In case you want to train your own model to use with Eynollah, have a look at [sbb_pixelwise_segmentation](https://github.com/qurator-spk/sbb_pixelwise_segmentation). 
+## Train
+🚧 **Work in progress**  
+
+In case you want to train your own model, have a look at [`sbb_pixelwise_segmentation`](https://github.com/qurator-spk/sbb_pixelwise_segmentation). 
 
 ## Usage
 The command-line interface can be called like this:
 
 ```sh
 eynollah \
-  -i <image file> \
+  -i <single image file> | -di <directory containing image files> \
   -o <output directory> \
-  -m <path to directory containing model files> \
+  -m <directory containing model files> \
      [OPTIONS]
 ```
 
 The following options can be used to further configure the processing:
 
-| option   |      description      |
-|----------|:-------------|
-| `-fl`  | full layout analysis including all steps and segmentation classes |
-| `-light` | lighter and faster but simpler method for main region detection and deskewing |
-| `-tab` | apply table detection |
-| `-ae`  | apply enhancement (the resulting image is saved to the output directory) |
-| `-as`  | apply scaling |
-| `-cl`  | apply contour detection for curved text lines instead of bounding boxes |
-| `-ib`  | apply binarization (the resulting image is saved to the output directory)  |
-| `-ep`  | enable plotting (MUST always be used with `-sl`, `-sd`, `-sa`, `-si` or `-ae`) |
-| `-ho`  | ignore headers for reading order dectection |
-| `-di <directory>`  | process all images in a directory in batch mode |
-| `-si <directory>`  | save image regions detected to this directory |
-| `-sd <directory>`  | save deskewed image to this directory |
-| `-sl <directory>`  | save layout prediction as plot to this directory |
-| `-sp <directory>`  | save cropped page image to this directory |
-| `-sa <directory>`  | save all (plot, enhanced/binary image, layout) to this directory |
-
-If no option is set, the tool will perform layout detection of main regions (background, text, images, separators and marginals).
-The tool produces better quality output when RGB images are used as input than greyscale or binarized images.
+| option            | description                                                                    |
+|-------------------|:-------------------------------------------------------------------------------|
+| `-fl`             | full layout analysis including all steps and segmentation classes              |
+| `-light`          | lighter and faster but simpler method for main region detection and deskewing  |
+| `-tab`            | apply table detection                                                          |
+| `-ae`             | apply enhancement (the resulting image is saved to the output directory)       |
+| `-as`             | apply scaling                                                                  |
+| `-cl`             | apply contour detection for curved text lines instead of bounding boxes        |
+| `-ib`             | apply binarization (the resulting image is saved to the output directory)      |
+| `-ep`             | enable plotting (MUST always be used with `-sl`, `-sd`, `-sa`, `-si` or `-ae`) |
+| `-eoi`            | extract only images to output directory (other processing will not be done)    |
+| `-ho`             | ignore headers for reading order dectection                                    |
+| `-si <directory>` | save image regions detected to this directory                                  |
+| `-sd <directory>` | save deskewed image to this directory                                          |
+| `-sl <directory>` | save layout prediction as plot to this directory                               |
+| `-sp <directory>` | save cropped page image to this directory                                      |
+| `-sa <directory>` | save all (plot, enhanced/binary image, layout) to this directory               |
+
+If no option is set, the tool performs layout detection of main regions (background, text, images, separators and marginals).
+The best output quality is produced when RGB images are used as input rather than greyscale or binarized images.
 
 #### Use as OCR-D processor
+🚧 **Work in progress** 
 
 Eynollah ships with a CLI interface to be used as [OCR-D](https://ocr-d.de) processor. 
 
@@ -95,11 +101,14 @@ ocrd-eynollah-segment -I OCR-D-IMG-BIN -O SEG-LINE -P models
 
 uses the original (RGB) image despite any binarization that may have occured in previous OCR-D processing steps
 
+#### Additional documentation
+Please check the [wiki](https://github.com/qurator-spk/eynollah/wiki).
+
 ## How to cite
 If you find this tool useful in your work, please consider citing our paper:
 
 ```bibtex
-@inproceedings{rezanezhad2023eynollah,
+@inproceedings{hip23rezanezhad,
   title     = {Document Layout Analysis with Deep Learning and Heuristics},
   author    = {Rezanezhad, Vahid and Baierer, Konstantin and Gerber, Mike and Labusch, Kai and Neudecker, Clemens},
   booktitle = {Proceedings of the 7th International Workshop on Historical Document Imaging and Processing {HIP} 2023,

ocrd-tool.json

@@ -1 +1 @@
-qurator/eynollah/ocrd-tool.json
+src/eynollah/ocrd-tool.json

pyproject.toml

@@ -1,34 +1,43 @@
 [build-system]
-requires = ["setuptools>=61.0"]
-build-backend = "setuptools.build_meta"
+requires = ["setuptools>=61.0", "wheel", "setuptools-ocrd"]
 
 [project]
 name = "eynollah"
-version = "0.1.0"
-
-
-
-
-dependencies = [
-    "ocrd >= 2.23.3",
-    "tensorflow == 2.12.1",
-    "scikit-learn >= 0.23.2",
-    "imutils >= 0.5.3",
-    "numpy < 1.24.0",
-    "matplotlib",
-    "torch == 2.0.1",
-    "transformers == 4.30.2",
-    "numba == 0.58.1",
+authors = [
+    {name = "Vahid Rezanezhad"},
+    {name = "Staatsbibliothek zu Berlin - Preußischer Kulturbesitz"},
+]
+description = "Document Layout Analysis"
+readme = "README.md"
+license.file = "LICENSE"
+requires-python = ">=3.8"
+keywords = ["document layout analysis", "image segmentation"]
+
+dynamic = ["dependencies", "version"]
+
+classifiers = [
+    "Development Status :: 4 - Beta",
+    "Environment :: Console",
+    "Intended Audience :: Science/Research",
+    "License :: OSI Approved :: Apache Software License",
+    "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3 :: Only",
+    "Topic :: Scientific/Engineering :: Image Processing",
 ]
 
 [project.scripts]
-eynollah = "qurator.eynollah.cli:main"
-ocrd-eynollah-segment="qurator.eynollah.ocrd_cli:main"
+eynollah = "eynollah.cli:main"
+ocrd-eynollah-segment = "eynollah.ocrd_cli:main"
+
+[project.urls]
+Homepage = "https://github.com/qurator-spk/eynollah"
+Repository = "https://github.com/qurator-spk/eynollah.git"
 
+[tool.setuptools.dynamic]
+dependencies = {file = ["requirements.txt"]}
 
 [tool.setuptools.packages.find]
-where = ["."]
-include = ["qurator"]
+where = ["src"]
 
 [tool.setuptools.package-data]
 "*" = ["*.json", '*.yml', '*.xml', '*.xsd']

qurator/eynollah/cli.py → src/eynollah/cli.py

@@ -1,8 +1,9 @@
 import sys
 import click
 from ocrd_utils import initLogging, setOverrideLogLevel
-from qurator.eynollah.eynollah import Eynollah
-from qurator.eynollah.sbb_binarize import SbbBinarizer
+from eynollah.eynollah import Eynollah
+from eynollah.eynollah import Eynollah
+from eynollah.sbb_binarize import SbbBinarizer
 
 @click.group()
 def main():
@@ -146,6 +147,12 @@ def binarization(patches, model_dir, input_image, output_image, dir_in, dir_out)
     is_flag=True,
     help="If set, will plot intermediary files and images",
 )
+@click.option(
+    "--extract_only_images/--disable-extracting_only_images",
+    "-eoi/-noeoi",
+    is_flag=True,
+    help="If a directory is given, only images in documents will be cropped and saved there and the other processing will not be done",
+)
 @click.option(
     "--allow-enhancement/--no-allow-enhancement",
     "-ae/-noae",
@@ -247,7 +254,7 @@ def binarization(patches, model_dir, input_image, output_image, dir_in, dir_out)
     help="Override log level globally to this",
 )
 
-def layout(image, out, dir_in, model, save_images, save_layout, save_deskewed, save_all, save_page, enable_plotting, allow_enhancement, curved_line, textline_light, full_layout, tables, right2left, input_binary, allow_scaling, headers_off, light_version, reading_order_machine_based, do_ocr, num_col_upper, num_col_lower, skip_layout_and_reading_order, ignore_page_extraction, log_level):
+def layout(image, out, dir_in, model, save_images, save_layout, save_deskewed, save_all, extract_only_images, save_page, enable_plotting, allow_enhancement, curved_line, textline_light, full_layout, tables, right2left, input_binary, allow_scaling, headers_off, light_version, reading_order_machine_based, do_ocr, num_col_upper, num_col_lower, skip_layout_and_reading_order, ignore_page_extraction, log_level):
     if log_level:
         setOverrideLogLevel(log_level)
     initLogging()
@@ -260,6 +267,9 @@ def layout(image, out, dir_in, model, save_images, save_layout, save_deskewed, s
     if textline_light and not light_version:
         print('Error: You used -tll to enable light textline detection but -light is not enabled')
         sys.exit(1)
+
+    if extract_only_images and  (allow_enhancement or allow_scaling or light_version or curved_line or textline_light or full_layout or tables or right2left or headers_off) :
+        print('Error: You used -eoi which can not be enabled alongside light_version -light or allow_scaling -as or allow_enhancement -ae or curved_line -cl or textline_light -tll or full_layout -fl or tables -tab or right2left -r2l or headers_off -ho')
     if light_version and not textline_light:
         print('Error: You used -light without -tll. Light version need light textline to be enabled.')
         sys.exit(1)
@@ -269,6 +279,7 @@ def layout(image, out, dir_in, model, save_images, save_layout, save_deskewed, s
         dir_in=dir_in,
         dir_models=model,
         dir_of_cropped_images=save_images,
+        extract_only_images=extract_only_images,
         dir_of_layout=save_layout,
         dir_of_deskewed=save_deskewed,
         dir_of_all=save_all,