automatic import of python-dhash

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diff --git a/.gitignore b/.gitignore
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@@ -0,0 +1 @@
+/dhash-1.4.tar.gz
diff --git a/python-dhash.spec b/python-dhash.spec
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+++ b/python-dhash.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-dhash
+Version:	1.4
+Release:	1
+Summary:	Calculate difference hash (perceptual hash) for a given image, useful for detecting duplicates
+License:	MIT License
+URL:		https://github.com/benhoyt/dhash
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/45/1b/68986e7d0e1fff5e154d96bf5c420f9933571f1d13f788b3d1b05f978267/dhash-1.4.tar.gz
+BuildArch:	noarch
+
+
+%description
+dhash is a Python library that generates a "difference hash" for a given image
+-- a `perceptual hash`_ based on Neal Krawetz's dHash algorithm in `this
+"Hacker Factor" blog entry`_.
+The library is `on the Python Package Index (PyPI)`_ and works on both Python
+3 and Python 2.7. To install it, fire up a command prompt, activate your
+virtual environment if you're using one, and type:
+    pip install dhash
+The algorithm to create a difference hash is very simple:
+* Convert the image to grayscale
+* Downsize it to a 9x9 thumbnail (size=8 means an 8+1 by 8+1 image)
+* Produce a 64-bit "row hash": a 1 bit means the pixel intensity is increasing
+  in the x direction, 0 means it's decreasing
+* Do the same to produce a 64-bit "column hash" in the y direction
+* Combine the two values to produce the final 128-bit hash value
+The library defaults to producing a size 8 dhash, but you can override this
+easily by passing ``size=N`` as a keyword argument to most functions. For
+example, you can produce a more accurate (but slower to work with) dhash of
+512 bits by specifying ``size=16``.
+I've found that dhash is great for detecting near duplicates (we
+found dupes using a size 8 dhash with a maximum delta of 2
+bits). But because of the simplicity of the algorithm, it's not great at
+finding similar images or duplicate-but-cropped images -- you'd need a more
+sophisticated image fingerprint if you want that. However, the dhash is good
+for finding exact duplicates and near duplicates, for example, the same image
+with slightly altered lighting, a few pixels of cropping, or very light
+photoshopping.
+To use the dhash library, you need either the `wand`_ ImageMagick binding or
+the `Pillow (PIL)`_ library installed. Pick one and stick with it -- they will
+produce slightly different dhash values due to differences in their grayscale
+conversion and resizing algorithms.
+If you have both libraries installed, dhash will use wand by default. To
+override this and force use of Pillow/PIL, call ``dhash.force_pil()`` before
+using the library.
+To produce a dhash value using wand:
+    import dhash
+    from wand.image import Image
+    with Image(filename='dhash-test.jpg') as image:
+        row, col = dhash.dhash_row_col(image)
+    print(dhash.format_hex(row, col))
+To produce a dhash value using Pillow:
+    import dhash
+    from PIL import Image
+    image = Image.open('dhash-test.jpg')
+    row, col = dhash.dhash_row_col(image)
+    print(dhash.format_hex(row, col))
+If you have your own library to convert an image to grayscale and downsize it
+to 9x9 (or 17x17 for size=16), you can pass ``dhash_row_col()`` a list of
+integer pixel intensities (for example, from 0 to 255). For example:
+    >>> import dhash
+    >>> row, col = dhash.dhash_row_col([0,0,1,1,1, 0,1,1,3,4, 0,1,6,6,7, 7,7,7,7,9, 8,7,7,8,9], size=4)
+    >>> format(row, '016b')
+    '0100101111010001'
+    >>> format(col, '016b')
+    '0101001111111001'
+To produce the hash value as a 128-bit integer directly, use
+``dhash_int(image, size=N)``. To format the hash value in various ways, use
+the ``format_*`` functions:
+    >>> row, col = (13962536140006260880, 9510476289765573406)
+    >>> dhash.format_bytes(row, col)
+    b'\xc1\xc4\xe4\xa4\x84\xa0\x80\x90\x83\xfb\xff\xcc\x00@\x83\x1e'
+    >>> dhash.format_hex(row, col)
+    'c1c4e4a484a0809083fbffcc0040831e'
+To compute the number of bits different (hamming distance) between two
+hashes, you can use the ``get_num_bits_different(hash1, hash2)`` helper
+function:
+    >>> import dhash
+    >>> dhash.get_num_bits_different(0x4bd1, 0x5bd2)
+    3
+You can also use dhash to generate the difference hash for a specific image
+from the command line:
+    $ python -m dhash dhash-test.jpg
+    c1c4e4a484a0809083fbffcc0040831e
+    $ python -m dhash --format=decimal dhash-test.jpg
+    13962536140006260880 9510476289765573406
+    # show the 8x8 row and column grids
+    $ python -m dhash --format=matrix dhash-test.jpg
+    * * . . . . . * 
+    * * . . . * . . 
+    * * * . . * . . 
+    * . * . . * . . 
+    * . . . . * . . 
+    * . * . . . . . 
+    * . . . . . . . 
+    * . . * . . . . 
+    * . . . . . * * 
+    * * * * * . * * 
+    * * * * * * * * 
+    * * . . * * . . 
+    . . . . . . . . 
+    . * . . . . . . 
+    * . . . . . * * 
+    . . . * * * * . 
+    # compute the bit delta between two images
+    $ python -m dhash dhash-test.jpg similar.jpg
+    1 bit differs out of 128 (0.8%)
+Read the code in `dhash.py`_ for more details – it's pretty small!
+dhash was written by `Ben Hoyt`_ and is licensed with a
+permissive MIT license (see `LICENSE.txt`_).
+
+%package -n python3-dhash
+Summary:	Calculate difference hash (perceptual hash) for a given image, useful for detecting duplicates
+Provides:	python-dhash
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-dhash
+dhash is a Python library that generates a "difference hash" for a given image
+-- a `perceptual hash`_ based on Neal Krawetz's dHash algorithm in `this
+"Hacker Factor" blog entry`_.
+The library is `on the Python Package Index (PyPI)`_ and works on both Python
+3 and Python 2.7. To install it, fire up a command prompt, activate your
+virtual environment if you're using one, and type:
+    pip install dhash
+The algorithm to create a difference hash is very simple:
+* Convert the image to grayscale
+* Downsize it to a 9x9 thumbnail (size=8 means an 8+1 by 8+1 image)
+* Produce a 64-bit "row hash": a 1 bit means the pixel intensity is increasing
+  in the x direction, 0 means it's decreasing
+* Do the same to produce a 64-bit "column hash" in the y direction
+* Combine the two values to produce the final 128-bit hash value
+The library defaults to producing a size 8 dhash, but you can override this
+easily by passing ``size=N`` as a keyword argument to most functions. For
+example, you can produce a more accurate (but slower to work with) dhash of
+512 bits by specifying ``size=16``.
+I've found that dhash is great for detecting near duplicates (we
+found dupes using a size 8 dhash with a maximum delta of 2
+bits). But because of the simplicity of the algorithm, it's not great at
+finding similar images or duplicate-but-cropped images -- you'd need a more
+sophisticated image fingerprint if you want that. However, the dhash is good
+for finding exact duplicates and near duplicates, for example, the same image
+with slightly altered lighting, a few pixels of cropping, or very light
+photoshopping.
+To use the dhash library, you need either the `wand`_ ImageMagick binding or
+the `Pillow (PIL)`_ library installed. Pick one and stick with it -- they will
+produce slightly different dhash values due to differences in their grayscale
+conversion and resizing algorithms.
+If you have both libraries installed, dhash will use wand by default. To
+override this and force use of Pillow/PIL, call ``dhash.force_pil()`` before
+using the library.
+To produce a dhash value using wand:
+    import dhash
+    from wand.image import Image
+    with Image(filename='dhash-test.jpg') as image:
+        row, col = dhash.dhash_row_col(image)
+    print(dhash.format_hex(row, col))
+To produce a dhash value using Pillow:
+    import dhash
+    from PIL import Image
+    image = Image.open('dhash-test.jpg')
+    row, col = dhash.dhash_row_col(image)
+    print(dhash.format_hex(row, col))
+If you have your own library to convert an image to grayscale and downsize it
+to 9x9 (or 17x17 for size=16), you can pass ``dhash_row_col()`` a list of
+integer pixel intensities (for example, from 0 to 255). For example:
+    >>> import dhash
+    >>> row, col = dhash.dhash_row_col([0,0,1,1,1, 0,1,1,3,4, 0,1,6,6,7, 7,7,7,7,9, 8,7,7,8,9], size=4)
+    >>> format(row, '016b')
+    '0100101111010001'
+    >>> format(col, '016b')
+    '0101001111111001'
+To produce the hash value as a 128-bit integer directly, use
+``dhash_int(image, size=N)``. To format the hash value in various ways, use
+the ``format_*`` functions:
+    >>> row, col = (13962536140006260880, 9510476289765573406)
+    >>> dhash.format_bytes(row, col)
+    b'\xc1\xc4\xe4\xa4\x84\xa0\x80\x90\x83\xfb\xff\xcc\x00@\x83\x1e'
+    >>> dhash.format_hex(row, col)
+    'c1c4e4a484a0809083fbffcc0040831e'
+To compute the number of bits different (hamming distance) between two
+hashes, you can use the ``get_num_bits_different(hash1, hash2)`` helper
+function:
+    >>> import dhash
+    >>> dhash.get_num_bits_different(0x4bd1, 0x5bd2)
+    3
+You can also use dhash to generate the difference hash for a specific image
+from the command line:
+    $ python -m dhash dhash-test.jpg
+    c1c4e4a484a0809083fbffcc0040831e
+    $ python -m dhash --format=decimal dhash-test.jpg
+    13962536140006260880 9510476289765573406
+    # show the 8x8 row and column grids
+    $ python -m dhash --format=matrix dhash-test.jpg
+    * * . . . . . * 
+    * * . . . * . . 
+    * * * . . * . . 
+    * . * . . * . . 
+    * . . . . * . . 
+    * . * . . . . . 
+    * . . . . . . . 
+    * . . * . . . . 
+    * . . . . . * * 
+    * * * * * . * * 
+    * * * * * * * * 
+    * * . . * * . . 
+    . . . . . . . . 
+    . * . . . . . . 
+    * . . . . . * * 
+    . . . * * * * . 
+    # compute the bit delta between two images
+    $ python -m dhash dhash-test.jpg similar.jpg
+    1 bit differs out of 128 (0.8%)
+Read the code in `dhash.py`_ for more details – it's pretty small!
+dhash was written by `Ben Hoyt`_ and is licensed with a
+permissive MIT license (see `LICENSE.txt`_).
+
+%package help
+Summary:	Development documents and examples for dhash
+Provides:	python3-dhash-doc
+%description help
+dhash is a Python library that generates a "difference hash" for a given image
+-- a `perceptual hash`_ based on Neal Krawetz's dHash algorithm in `this
+"Hacker Factor" blog entry`_.
+The library is `on the Python Package Index (PyPI)`_ and works on both Python
+3 and Python 2.7. To install it, fire up a command prompt, activate your
+virtual environment if you're using one, and type:
+    pip install dhash
+The algorithm to create a difference hash is very simple:
+* Convert the image to grayscale
+* Downsize it to a 9x9 thumbnail (size=8 means an 8+1 by 8+1 image)
+* Produce a 64-bit "row hash": a 1 bit means the pixel intensity is increasing
+  in the x direction, 0 means it's decreasing
+* Do the same to produce a 64-bit "column hash" in the y direction
+* Combine the two values to produce the final 128-bit hash value
+The library defaults to producing a size 8 dhash, but you can override this
+easily by passing ``size=N`` as a keyword argument to most functions. For
+example, you can produce a more accurate (but slower to work with) dhash of
+512 bits by specifying ``size=16``.
+I've found that dhash is great for detecting near duplicates (we
+found dupes using a size 8 dhash with a maximum delta of 2
+bits). But because of the simplicity of the algorithm, it's not great at
+finding similar images or duplicate-but-cropped images -- you'd need a more
+sophisticated image fingerprint if you want that. However, the dhash is good
+for finding exact duplicates and near duplicates, for example, the same image
+with slightly altered lighting, a few pixels of cropping, or very light
+photoshopping.
+To use the dhash library, you need either the `wand`_ ImageMagick binding or
+the `Pillow (PIL)`_ library installed. Pick one and stick with it -- they will
+produce slightly different dhash values due to differences in their grayscale
+conversion and resizing algorithms.
+If you have both libraries installed, dhash will use wand by default. To
+override this and force use of Pillow/PIL, call ``dhash.force_pil()`` before
+using the library.
+To produce a dhash value using wand:
+    import dhash
+    from wand.image import Image
+    with Image(filename='dhash-test.jpg') as image:
+        row, col = dhash.dhash_row_col(image)
+    print(dhash.format_hex(row, col))
+To produce a dhash value using Pillow:
+    import dhash
+    from PIL import Image
+    image = Image.open('dhash-test.jpg')
+    row, col = dhash.dhash_row_col(image)
+    print(dhash.format_hex(row, col))
+If you have your own library to convert an image to grayscale and downsize it
+to 9x9 (or 17x17 for size=16), you can pass ``dhash_row_col()`` a list of
+integer pixel intensities (for example, from 0 to 255). For example:
+    >>> import dhash
+    >>> row, col = dhash.dhash_row_col([0,0,1,1,1, 0,1,1,3,4, 0,1,6,6,7, 7,7,7,7,9, 8,7,7,8,9], size=4)
+    >>> format(row, '016b')
+    '0100101111010001'
+    >>> format(col, '016b')
+    '0101001111111001'
+To produce the hash value as a 128-bit integer directly, use
+``dhash_int(image, size=N)``. To format the hash value in various ways, use
+the ``format_*`` functions:
+    >>> row, col = (13962536140006260880, 9510476289765573406)
+    >>> dhash.format_bytes(row, col)
+    b'\xc1\xc4\xe4\xa4\x84\xa0\x80\x90\x83\xfb\xff\xcc\x00@\x83\x1e'
+    >>> dhash.format_hex(row, col)
+    'c1c4e4a484a0809083fbffcc0040831e'
+To compute the number of bits different (hamming distance) between two
+hashes, you can use the ``get_num_bits_different(hash1, hash2)`` helper
+function:
+    >>> import dhash
+    >>> dhash.get_num_bits_different(0x4bd1, 0x5bd2)
+    3
+You can also use dhash to generate the difference hash for a specific image
+from the command line:
+    $ python -m dhash dhash-test.jpg
+    c1c4e4a484a0809083fbffcc0040831e
+    $ python -m dhash --format=decimal dhash-test.jpg
+    13962536140006260880 9510476289765573406
+    # show the 8x8 row and column grids
+    $ python -m dhash --format=matrix dhash-test.jpg
+    * * . . . . . * 
+    * * . . . * . . 
+    * * * . . * . . 
+    * . * . . * . . 
+    * . . . . * . . 
+    * . * . . . . . 
+    * . . . . . . . 
+    * . . * . . . . 
+    * . . . . . * * 
+    * * * * * . * * 
+    * * * * * * * * 
+    * * . . * * . . 
+    . . . . . . . . 
+    . * . . . . . . 
+    * . . . . . * * 
+    . . . * * * * . 
+    # compute the bit delta between two images
+    $ python -m dhash dhash-test.jpg similar.jpg
+    1 bit differs out of 128 (0.8%)
+Read the code in `dhash.py`_ for more details – it's pretty small!
+dhash was written by `Ben Hoyt`_ and is licensed with a
+permissive MIT license (see `LICENSE.txt`_).
+
+%prep
+%autosetup -n dhash-1.4
+
+%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-dhash -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 1.4-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..46cf7b3
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+841c75e51278f6922ab1dc3ab0a6a426  dhash-1.4.tar.gz