%global _empty_manifest_terminate_build 0
Name:		python-pdqhash
Version:	0.2.3
Release:	1
Summary:	"Python bindings for Facebook's PDQ hash"
License:	MIT
URL:		https://github.com/faustomorales/pdqhash-python
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/e1/8b/7c4458eadda2a6224ea661bd835ecfe14b15f61feee2f7c2d08b06c1cdf9/pdqhash-0.2.3.tar.gz


%description
# pdqhash-python

These are Python bindings to the PDQ perceptual hash released by Facebook. Note that the bindings are provided under the MIT license but the PDQ source code is licensed separately under its own license (see the `ThreatExchange/hashing/pdq` folder).

## Installation

```
pip install pdqhash
```

## Usage

```python
import pdqhash

image = cv2.imread(os.path.join('tests', 'images', image_name))
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
hash_vector, quality = pdqhash.compute(image)

# Get all the rotations and flips in one pass.
# hash_vectors is a list of vectors in the following order
# - Original
# - Rotated 90 degrees
# - Rotated 180 degrees
# - Rotated 270 degrees
# - Flipped vertically
# - Flipped horizontally
# - Rotated 90 degrees and flipped vertically
# - Rotated 90 degrees and flipped horizontally
hash_vectors, quality = pdqhash.compute_dihedral(image)

# Get the floating point values of the hash.
hash_vector_float, quality = pdqhash.compute_float(image)
```

## Contributing

- Set up local development using `make init` (you need to have `pipenv` installed)
- Run tests using `make test`
- Run tests in Docker using `make docker_test`


%package -n python3-pdqhash
Summary:	"Python bindings for Facebook's PDQ hash"
Provides:	python-pdqhash
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
BuildRequires:	python3-cffi
BuildRequires:	gcc
BuildRequires:	gdb
%description -n python3-pdqhash
# pdqhash-python

These are Python bindings to the PDQ perceptual hash released by Facebook. Note that the bindings are provided under the MIT license but the PDQ source code is licensed separately under its own license (see the `ThreatExchange/hashing/pdq` folder).

## Installation

```
pip install pdqhash
```

## Usage

```python
import pdqhash

image = cv2.imread(os.path.join('tests', 'images', image_name))
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
hash_vector, quality = pdqhash.compute(image)

# Get all the rotations and flips in one pass.
# hash_vectors is a list of vectors in the following order
# - Original
# - Rotated 90 degrees
# - Rotated 180 degrees
# - Rotated 270 degrees
# - Flipped vertically
# - Flipped horizontally
# - Rotated 90 degrees and flipped vertically
# - Rotated 90 degrees and flipped horizontally
hash_vectors, quality = pdqhash.compute_dihedral(image)

# Get the floating point values of the hash.
hash_vector_float, quality = pdqhash.compute_float(image)
```

## Contributing

- Set up local development using `make init` (you need to have `pipenv` installed)
- Run tests using `make test`
- Run tests in Docker using `make docker_test`


%package help
Summary:	Development documents and examples for pdqhash
Provides:	python3-pdqhash-doc
%description help
# pdqhash-python

These are Python bindings to the PDQ perceptual hash released by Facebook. Note that the bindings are provided under the MIT license but the PDQ source code is licensed separately under its own license (see the `ThreatExchange/hashing/pdq` folder).

## Installation

```
pip install pdqhash
```

## Usage

```python
import pdqhash

image = cv2.imread(os.path.join('tests', 'images', image_name))
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
hash_vector, quality = pdqhash.compute(image)

# Get all the rotations and flips in one pass.
# hash_vectors is a list of vectors in the following order
# - Original
# - Rotated 90 degrees
# - Rotated 180 degrees
# - Rotated 270 degrees
# - Flipped vertically
# - Flipped horizontally
# - Rotated 90 degrees and flipped vertically
# - Rotated 90 degrees and flipped horizontally
hash_vectors, quality = pdqhash.compute_dihedral(image)

# Get the floating point values of the hash.
hash_vector_float, quality = pdqhash.compute_float(image)
```

## Contributing

- Set up local development using `make init` (you need to have `pipenv` installed)
- Run tests using `make test`
- Run tests in Docker using `make docker_test`


%prep
%autosetup -n pdqhash-0.2.3

%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-pdqhash -f filelist.lst
%dir %{python3_sitearch}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.2.3-1
- Package Spec generated