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{
lib,
buildPythonPackage,
fetchFromGitHub,
# build-system
setuptools,
# dependencies
joblib,
keras,
lz4,
pythonAtLeast,
distutils,
# tests
pytestCheckHook,
}:
buildPythonPackage rec {
pname = "mtcnn";
version = "1.0.0";
pyproject = true;
src = fetchFromGitHub {
owner = "ipazc";
repo = "mtcnn";
tag = "v${version}";
hash = "sha256-gp+jfa1arD3PpJpuRFKIUznV0Lyjt3DPn/HHUviDXhk=";
};
build-system = [ setuptools ];
dependencies = [
joblib
lz4
]
++ lib.optionals (pythonAtLeast "3.12") [
distutils
];
pythonImportsCheck = [ "mtcnn" ];
nativeCheckInputs = [
keras
pytestCheckHook
];
disabledTests = [
# Failing since keras 3.13.0.
# ValueError: Exception encountered when calling Conv2D.call().
# The convolution operation resulted in an empty output. Output shape: (0, 48, 48, 3).
# This can happen if the input is too small for the given kernel size, strides, dilation rate,
# and padding mode. Please check the input shape and convolution parameters.
"test_detect_no_faces"
];
meta = {
description = "MTCNN face detection implementation for TensorFlow";
homepage = "https://github.com/ipazc/mtcnn";
changelog = "https://github.com/ipazc/mtcnn/releases/tag/v${version}";
license = lib.licenses.mit;
maintainers = with lib.maintainers; [ derdennisop ];
};
}
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