# -*- coding: utf-8; mode: tcl; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- vim:fenc=utf-8:ft=tcl:et:sw=4:ts=4:sts=4

PortSystem          1.0
PortGroup           python 1.0

name                py-imagehash
python.rootname     ImageHash
version             4.3.1

categories-append   devel graphics
platforms           {darwin any}
supported_archs     noarch
license             BSD
maintainers         nomaintainer

description         Perceptual Image Hashing Module
long_description    Image hashes tell whether two images look nearly \
                    identical. This is different from cryptographic \
                    hashing algorithms (like MD5, SHA-1) where tiny \
                    changes in the image give completely different \
                    hashes. In image fingerprinting, we actually want \
                    our similar inputs to have similar output hashes \
                    as well. The image hash algorithms (average, \
                    perceptual, difference, wavelet) analyse the image \
                    structure on luminance (without color \
                    information). The color hash algorithm analyses \
                    the color distribution and black & gray fractions \
                    (without position information).

homepage            https://github.com/JohannesBuchner/imagehash

checksums           rmd160  46c6a282f7ebb9c3fb5256a318259699fdb9e817 \
                    sha256  7038d1b7f9e0585beb3dd8c0a956f02b95a346c0b5f24a9e8cc03ebadaf0aa70 \
                    size    296989

python.versions     39 310 311 312

if {${subport} ne ${name}} {
    depends_run-append \
                    port:py${python.version}-numpy \
                    port:py${python.version}-Pillow \
                    port:py${python.version}-pywavelets \
                    port:py${python.version}-scipy
}