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+%global _empty_manifest_terminate_build 0
+Name:		python-table-ocr
+Version:	0.2.5
+Release:	1
+Summary:	Extract text from tables in images.
+License:	MIT License
+URL:		https://github.com/eihli/image-table-ocr
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/0c/80/6825837bd2f8c4d49a19f77ed71106f8635205719b2df476dcf544c27f26/table_ocr-0.2.5.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-pytesseract
+Requires:	python3-opencv-python
+Requires:	python3-numpy
+Requires:	python3-requests
+
+%description
+━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+                TABLE DETECTION IN IMAGES AND OCR TO CSV
+
+                               Eric Ihli
+               ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+
+
+Table of Contents
+─────────────────
+
+1. Overview
+2. Requirements
+3. Demo
+4. Modules
+
+
+
+
+
+1 Overview
+══════════
+
+  This python package contains modules to help with finding and
+  extracting tabular data from a PDF or image into a CSV format.
+
+  Given an image that contains a table…
+
+  <file:resources/examples/example-page.png>
+
+  Extract the the text into a CSV format…
+
+  ┌────
+  │ PRIZE,ODDS 1 IN:,# OF WINNERS*
+  │ $3,9.09,"282,447"
+  │ $5,16.66,"154,097"
+  │ $7,40.01,"64,169"
+  │ $10,26.67,"96,283"
+  │ $20,100.00,"25,677"
+  │ $30,290.83,"8,829"
+  │ $50,239.66,"10,714"
+  │ $100,919.66,"2,792"
+  │ $500,"6,652.07",386
+  │ "$40,000","855,899.99",3
+  │ 1,i223,
+  │ Toa,,
+  │ ,,
+  │ ,,"* Based upon 2,567,700"
+  └────
+
+
+2 Requirements
+══════════════
+
+  Along with the python requirements that are listed in setup.py and
+  that are automatically installed when installing this package through
+  pip, there are a few external requirements for some of the modules.
+
+  I haven’t looked into the minimum required versions of these
+  dependencies, but I’ll list the versions that I’m using.
+
+  • `pdfimages' 20.09.0 of [Poppler]
+  • `tesseract' 5.0.0 of [Tesseract]
+  • `mogrify' 7.0.10 of [ImageMagick]
+
+
+[Poppler] <https://poppler.freedesktop.org/>
+
+[Tesseract] <https://github.com/tesseract-ocr/tesseract>
+
+[ImageMagick] <https://imagemagick.org/index.php>
+
+
+3 Demo
+══════
+
+  There is a demo module that will download an image given a URL and try
+  to extract tables from the image and process the cells into a CSV. You
+  can try it out with one of the images included in this repo.
+
+  1. `pip3 install table_ocr'
+  2. `python3 -m table_ocr.demo
+     https://raw.githubusercontent.com/eihli/image-table-ocr/master/resources/test_data/simple.png'
+
+  That will run against the following image:
+
+  <file:resources/test_data/simple.png>
+
+  The following should be printed to your terminal after running the
+  above commands.
+
+  ┌────
+  │ Running `extract_tables.main([/tmp/demo_p9on6m8o/simple.png]).`
+  │ Extracted the following tables from the image:
+  │ [('/tmp/demo_p9on6m8o/simple.png', ['/tmp/demo_p9on6m8o/simple/table-000.png'])]
+  │ Processing tables for /tmp/demo_p9on6m8o/simple.png.
+  │ Processing table /tmp/demo_p9on6m8o/simple/table-000.png.
+  │ Extracted 18 cells from /tmp/demo_p9on6m8o/simple/table-000.png
+  │ Cells:
+  │ /tmp/demo_p9on6m8o/simple/cells/000-000.png: Cell
+  │ /tmp/demo_p9on6m8o/simple/cells/000-001.png: Format
+  │ /tmp/demo_p9on6m8o/simple/cells/000-002.png: Formula
+  │ ...
+  │ 
+  │ Here is the entire CSV output:
+  │ 
+  │ Cell,Format,Formula
+  │ B4,Percentage,None
+  │ C4,General,None
+  │ D4,Accounting,None
+  │ E4,Currency,"=PMT(B4/12,C4,D4)"
+  │ F4,Currency,=E4*C4
+  └────
+
+
+4 Modules
+═════════
+
+  The package is split into modules with narrow focuses.
+
+  • `pdf_to_images' uses Poppler and ImageMagick to extract images from
+    a PDF.
+  • `extract_tables' finds and extracts table-looking things from an
+    image.
+  • `extract_cells' extracts and orders cells from a table.
+  • `ocr_image' uses Tesseract to OCR the text from an image of a cell.
+  • `ocr_to_csv' converts into a CSV the directory structure that
+    `ocr_image' outputs.
+
+  The outputs of a previous module can be used by a subsequent module so
+  that they can be chained together to create the entire workflow, as
+  demonstrated by the following shell script.
+
+  ┌────
+  │ #!/bin/sh
+  │ 
+  │ PDF=$1
+  │ 
+  │ python -m table_ocr.pdf_to_images $PDF | grep .png > /tmp/pdf-images.txt
+  │ cat /tmp/pdf-images.txt | xargs -I{} python -m table_ocr.extract_tables {}  | grep table > /tmp/extracted-tables.txt
+  │ cat /tmp/extracted-tables.txt | xargs -I{} python -m table_ocr.extract_cells {} | grep cells > /tmp/extracted-cells.txt
+  │ cat /tmp/extracted-cells.txt | xargs -I{} python -m table_ocr.ocr_image {}
+  │ 
+  │ for image in $(cat /tmp/extracted-tables.txt); do
+  │     dir=$(dirname $image)
+  │     python -m table_ocr.ocr_to_csv $(find $dir/cells -name "*.txt")
+  │ done
+  └────
+
+
+  The package was written in a [literate programming] style. The source
+  code at
+  <https://eihli.github.io/image-table-ocr/pdf_table_extraction_and_ocr.html>
+  is meant to act as the documentation and reference material.
+
+
+[literate programming]
+<https://en.wikipedia.org/wiki/Literate_programming>
+
+
+
+
+%package -n python3-table-ocr
+Summary:	Extract text from tables in images.
+Provides:	python-table-ocr
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-table-ocr
+━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+                TABLE DETECTION IN IMAGES AND OCR TO CSV
+
+                               Eric Ihli
+               ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+
+
+Table of Contents
+─────────────────
+
+1. Overview
+2. Requirements
+3. Demo
+4. Modules
+
+
+
+
+
+1 Overview
+══════════
+
+  This python package contains modules to help with finding and
+  extracting tabular data from a PDF or image into a CSV format.
+
+  Given an image that contains a table…
+
+  <file:resources/examples/example-page.png>
+
+  Extract the the text into a CSV format…
+
+  ┌────
+  │ PRIZE,ODDS 1 IN:,# OF WINNERS*
+  │ $3,9.09,"282,447"
+  │ $5,16.66,"154,097"
+  │ $7,40.01,"64,169"
+  │ $10,26.67,"96,283"
+  │ $20,100.00,"25,677"
+  │ $30,290.83,"8,829"
+  │ $50,239.66,"10,714"
+  │ $100,919.66,"2,792"
+  │ $500,"6,652.07",386
+  │ "$40,000","855,899.99",3
+  │ 1,i223,
+  │ Toa,,
+  │ ,,
+  │ ,,"* Based upon 2,567,700"
+  └────
+
+
+2 Requirements
+══════════════
+
+  Along with the python requirements that are listed in setup.py and
+  that are automatically installed when installing this package through
+  pip, there are a few external requirements for some of the modules.
+
+  I haven’t looked into the minimum required versions of these
+  dependencies, but I’ll list the versions that I’m using.
+
+  • `pdfimages' 20.09.0 of [Poppler]
+  • `tesseract' 5.0.0 of [Tesseract]
+  • `mogrify' 7.0.10 of [ImageMagick]
+
+
+[Poppler] <https://poppler.freedesktop.org/>
+
+[Tesseract] <https://github.com/tesseract-ocr/tesseract>
+
+[ImageMagick] <https://imagemagick.org/index.php>
+
+
+3 Demo
+══════
+
+  There is a demo module that will download an image given a URL and try
+  to extract tables from the image and process the cells into a CSV. You
+  can try it out with one of the images included in this repo.
+
+  1. `pip3 install table_ocr'
+  2. `python3 -m table_ocr.demo
+     https://raw.githubusercontent.com/eihli/image-table-ocr/master/resources/test_data/simple.png'
+
+  That will run against the following image:
+
+  <file:resources/test_data/simple.png>
+
+  The following should be printed to your terminal after running the
+  above commands.
+
+  ┌────
+  │ Running `extract_tables.main([/tmp/demo_p9on6m8o/simple.png]).`
+  │ Extracted the following tables from the image:
+  │ [('/tmp/demo_p9on6m8o/simple.png', ['/tmp/demo_p9on6m8o/simple/table-000.png'])]
+  │ Processing tables for /tmp/demo_p9on6m8o/simple.png.
+  │ Processing table /tmp/demo_p9on6m8o/simple/table-000.png.
+  │ Extracted 18 cells from /tmp/demo_p9on6m8o/simple/table-000.png
+  │ Cells:
+  │ /tmp/demo_p9on6m8o/simple/cells/000-000.png: Cell
+  │ /tmp/demo_p9on6m8o/simple/cells/000-001.png: Format
+  │ /tmp/demo_p9on6m8o/simple/cells/000-002.png: Formula
+  │ ...
+  │ 
+  │ Here is the entire CSV output:
+  │ 
+  │ Cell,Format,Formula
+  │ B4,Percentage,None
+  │ C4,General,None
+  │ D4,Accounting,None
+  │ E4,Currency,"=PMT(B4/12,C4,D4)"
+  │ F4,Currency,=E4*C4
+  └────
+
+
+4 Modules
+═════════
+
+  The package is split into modules with narrow focuses.
+
+  • `pdf_to_images' uses Poppler and ImageMagick to extract images from
+    a PDF.
+  • `extract_tables' finds and extracts table-looking things from an
+    image.
+  • `extract_cells' extracts and orders cells from a table.
+  • `ocr_image' uses Tesseract to OCR the text from an image of a cell.
+  • `ocr_to_csv' converts into a CSV the directory structure that
+    `ocr_image' outputs.
+
+  The outputs of a previous module can be used by a subsequent module so
+  that they can be chained together to create the entire workflow, as
+  demonstrated by the following shell script.
+
+  ┌────
+  │ #!/bin/sh
+  │ 
+  │ PDF=$1
+  │ 
+  │ python -m table_ocr.pdf_to_images $PDF | grep .png > /tmp/pdf-images.txt
+  │ cat /tmp/pdf-images.txt | xargs -I{} python -m table_ocr.extract_tables {}  | grep table > /tmp/extracted-tables.txt
+  │ cat /tmp/extracted-tables.txt | xargs -I{} python -m table_ocr.extract_cells {} | grep cells > /tmp/extracted-cells.txt
+  │ cat /tmp/extracted-cells.txt | xargs -I{} python -m table_ocr.ocr_image {}
+  │ 
+  │ for image in $(cat /tmp/extracted-tables.txt); do
+  │     dir=$(dirname $image)
+  │     python -m table_ocr.ocr_to_csv $(find $dir/cells -name "*.txt")
+  │ done
+  └────
+
+
+  The package was written in a [literate programming] style. The source
+  code at
+  <https://eihli.github.io/image-table-ocr/pdf_table_extraction_and_ocr.html>
+  is meant to act as the documentation and reference material.
+
+
+[literate programming]
+<https://en.wikipedia.org/wiki/Literate_programming>
+
+
+
+
+%package help
+Summary:	Development documents and examples for table-ocr
+Provides:	python3-table-ocr-doc
+%description help
+━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+                TABLE DETECTION IN IMAGES AND OCR TO CSV
+
+                               Eric Ihli
+               ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+
+
+Table of Contents
+─────────────────
+
+1. Overview
+2. Requirements
+3. Demo
+4. Modules
+
+
+
+
+
+1 Overview
+══════════
+
+  This python package contains modules to help with finding and
+  extracting tabular data from a PDF or image into a CSV format.
+
+  Given an image that contains a table…
+
+  <file:resources/examples/example-page.png>
+
+  Extract the the text into a CSV format…
+
+  ┌────
+  │ PRIZE,ODDS 1 IN:,# OF WINNERS*
+  │ $3,9.09,"282,447"
+  │ $5,16.66,"154,097"
+  │ $7,40.01,"64,169"
+  │ $10,26.67,"96,283"
+  │ $20,100.00,"25,677"
+  │ $30,290.83,"8,829"
+  │ $50,239.66,"10,714"
+  │ $100,919.66,"2,792"
+  │ $500,"6,652.07",386
+  │ "$40,000","855,899.99",3
+  │ 1,i223,
+  │ Toa,,
+  │ ,,
+  │ ,,"* Based upon 2,567,700"
+  └────
+
+
+2 Requirements
+══════════════
+
+  Along with the python requirements that are listed in setup.py and
+  that are automatically installed when installing this package through
+  pip, there are a few external requirements for some of the modules.
+
+  I haven’t looked into the minimum required versions of these
+  dependencies, but I’ll list the versions that I’m using.
+
+  • `pdfimages' 20.09.0 of [Poppler]
+  • `tesseract' 5.0.0 of [Tesseract]
+  • `mogrify' 7.0.10 of [ImageMagick]
+
+
+[Poppler] <https://poppler.freedesktop.org/>
+
+[Tesseract] <https://github.com/tesseract-ocr/tesseract>
+
+[ImageMagick] <https://imagemagick.org/index.php>
+
+
+3 Demo
+══════
+
+  There is a demo module that will download an image given a URL and try
+  to extract tables from the image and process the cells into a CSV. You
+  can try it out with one of the images included in this repo.
+
+  1. `pip3 install table_ocr'
+  2. `python3 -m table_ocr.demo
+     https://raw.githubusercontent.com/eihli/image-table-ocr/master/resources/test_data/simple.png'
+
+  That will run against the following image:
+
+  <file:resources/test_data/simple.png>
+
+  The following should be printed to your terminal after running the
+  above commands.
+
+  ┌────
+  │ Running `extract_tables.main([/tmp/demo_p9on6m8o/simple.png]).`
+  │ Extracted the following tables from the image:
+  │ [('/tmp/demo_p9on6m8o/simple.png', ['/tmp/demo_p9on6m8o/simple/table-000.png'])]
+  │ Processing tables for /tmp/demo_p9on6m8o/simple.png.
+  │ Processing table /tmp/demo_p9on6m8o/simple/table-000.png.
+  │ Extracted 18 cells from /tmp/demo_p9on6m8o/simple/table-000.png
+  │ Cells:
+  │ /tmp/demo_p9on6m8o/simple/cells/000-000.png: Cell
+  │ /tmp/demo_p9on6m8o/simple/cells/000-001.png: Format
+  │ /tmp/demo_p9on6m8o/simple/cells/000-002.png: Formula
+  │ ...
+  │ 
+  │ Here is the entire CSV output:
+  │ 
+  │ Cell,Format,Formula
+  │ B4,Percentage,None
+  │ C4,General,None
+  │ D4,Accounting,None
+  │ E4,Currency,"=PMT(B4/12,C4,D4)"
+  │ F4,Currency,=E4*C4
+  └────
+
+
+4 Modules
+═════════
+
+  The package is split into modules with narrow focuses.
+
+  • `pdf_to_images' uses Poppler and ImageMagick to extract images from
+    a PDF.
+  • `extract_tables' finds and extracts table-looking things from an
+    image.
+  • `extract_cells' extracts and orders cells from a table.
+  • `ocr_image' uses Tesseract to OCR the text from an image of a cell.
+  • `ocr_to_csv' converts into a CSV the directory structure that
+    `ocr_image' outputs.
+
+  The outputs of a previous module can be used by a subsequent module so
+  that they can be chained together to create the entire workflow, as
+  demonstrated by the following shell script.
+
+  ┌────
+  │ #!/bin/sh
+  │ 
+  │ PDF=$1
+  │ 
+  │ python -m table_ocr.pdf_to_images $PDF | grep .png > /tmp/pdf-images.txt
+  │ cat /tmp/pdf-images.txt | xargs -I{} python -m table_ocr.extract_tables {}  | grep table > /tmp/extracted-tables.txt
+  │ cat /tmp/extracted-tables.txt | xargs -I{} python -m table_ocr.extract_cells {} | grep cells > /tmp/extracted-cells.txt
+  │ cat /tmp/extracted-cells.txt | xargs -I{} python -m table_ocr.ocr_image {}
+  │ 
+  │ for image in $(cat /tmp/extracted-tables.txt); do
+  │     dir=$(dirname $image)
+  │     python -m table_ocr.ocr_to_csv $(find $dir/cells -name "*.txt")
+  │ done
+  └────
+
+
+  The package was written in a [literate programming] style. The source
+  code at
+  <https://eihli.github.io/image-table-ocr/pdf_table_extraction_and_ocr.html>
+  is meant to act as the documentation and reference material.
+
+
+[literate programming]
+<https://en.wikipedia.org/wiki/Literate_programming>
+
+
+
+
+%prep
+%autosetup -n table-ocr-0.2.5
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+if [ -d usr/lib ]; then
+	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/lib64 ]; then
+	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/bin ]; then
+	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/sbin ]; then
+	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+touch doclist.lst
+if [ -d usr/share/man ]; then
+	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
+fi
+popd
+mv %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-table-ocr -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed May 17 2023 Python_Bot <Python_Bot@openeuler.org> - 0.2.5-1
+- Package Spec generated