{
  description = "Pre-built CPU-only OpenCV packages for Python.  ";
  inputs = {
    nixpkgs.url = "github:NixOS/nixpkgs/nixpkgs-unstable";
    flake-utils.url = "github:numtide/flake-utils";
  };

  outputs = { self, nixpkgs, flake-utils }:
    flake-utils.lib.eachDefaultSystem (system:
      let
        pkgs = nixpkgs.legacyPackages.${system};
        pythonPackages = pkgs.python312Packages;

        lapx = pkgs.python3Packages.buildPythonPackage rec {
          version = "0.5.11";
          pname = "lapx";
          pyproject = true;
          src = pkgs.fetchFromGitHub {
            owner = "rathaROG";
            repo = "lapx";
            rev = "be6f998e7cbe8746f75d9743a9de168d3788998f";
            hash = "sha256-7TUorvC/h9myQ+ZMOPABfqXx4D0mKYB1meszhpIeWWs=";
            fetchSubmodules = true;
          };

          propagatedBuildInputs =
            [ pythonPackages.numpy pythonPackages.cython ];

          nativeBuildInputs = [
            pythonPackages.setuptools
            pythonPackages.setuptools-scm
            pythonPackages.cython
          ];

          meta = with pkgs.lib; {
            description = ''
              THOP offers an intuitive API to profile PyTorch models
              by calculating the number of MACs and parameters. This
              functionality is crucial for assessing the computational
              efficiency and memory footprint of deep learning models.
            '';
            homepage = "https://github.com/rathaROG/lapx";
            license = pkgs.lib.licenses.mit;
            maintainers = with maintainers; [ ];
          };
        };

        ultralytics-thop = pkgs.python3Packages.buildPythonPackage rec {
          version = "2.0.9";
          pname = "ultralytics-htop";
          pyproject = true;
          src = pkgs.fetchFromGitHub {
            owner = "ultralytics";
            repo = "thop";
            rev = "d304cebcc81f65a7b0d4304290f2abb100407ec0";
            hash = "sha256-FzjxEk6yiG+IWwQEzsHcEAB4iVQT1QsyoGlG4I9lSwU=";
            fetchSubmodules = true;
          };

          propagatedBuildInputs = [ pythonPackages.numpy pythonPackages.torch ];

          nativeBuildInputs =
            [ pythonPackages.setuptools pythonPackages.setuptools-scm ];

          meta = with pkgs.lib; {
            description = ''
              THOP offers an intuitive API to profile PyTorch models
              by calculating the number of MACs and parameters. This
              functionality is crucial for assessing the computational
              efficiency and memory footprint of deep learning models.
            '';
            homepage = "https://github.com/ultralytics/thop";
            license = pkgs.lib.licenses.mit;
            maintainers = with maintainers; [ ];
          };
        };

        ultralytics = pkgs.python3Packages.buildPythonPackage rec {
          version = "8.3.13";
          pname = "ultralytics";
          pyproject = true;
          src = pkgs.fetchFromGitHub {
            owner = "ultralytics";
            repo = "ultralytics";
            rev = "15e6133534d82ec6845308f1e258d77c1b9bab36";
            hash = "sha256-Wq2pCD0l0AbdQ2IPfEfxPffSxgv/5qFadB4BHAExEbU=";
            fetchSubmodules = true;
          };
          # doCheck = false;

          propagatedBuildInputs = [
            pythonPackages.requests
            pythonPackages.pyyaml
            pythonPackages.torch
            pythonPackages.tqdm
            pythonPackages.psutil
            pythonPackages.torchvision
            pythonPackages.pandas
            pythonPackages.matplotlib
            pythonPackages.seaborn
            pythonPackages.py-cpuinfo
            pythonPackages.opencv4

            ultralytics-thop
          ];

          pythonRelaxDeps = [ "torchvision" ];
          pythonRemoveDeps = [ "opencv-python" ];

          nativeBuildInputs = [
            pythonPackages.setuptools
            pythonPackages.setuptools-scm
            pythonPackages.pip
          ];

          # nativeCheckInputs = [ ];

          meta = with pkgs.lib; {
            description = ''
              Ultralytics YOLO for SOTA object detection,
              multi-object tracking, instance segmentation,
              pose estimation and image classification.
            '';
            homepage = "https://github.com/ultralytics/ultralytics";
            license = pkgs.lib.licenses.mit;
            maintainers = with maintainers; [ ];
          };
        };

        env = pkgs.python312.withPackages (ps: [ lapx ]);

      in {
        packages = {
          default = pkgs.python312Packages.path;
          env = env;
        };
        devShells.default = pkgs.mkShell { buildInputs = [ env ]; };
      });
}