opencv-python-related/flake.nix

{
  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 = import nixpkgs {
          system = system;
          config.allowUnfree = true;
          config.cudaSupport = true;
        };
        # pkgs = nixpkgs.legacyPackages.${system};

        pythonPackages = pkgs.python312Packages;

        custom-opencv4 = pythonPackages.opencv4.override {
          enableGtk3 = true;
          enableFfmpeg =
            true; # here is how to add ffmpeg and other compilation flags
          ffmpeg = pkgs.ffmpeg-full;
        };

        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 = with pythonPackages; [ numpy ];

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

          meta = with pkgs.lib; {
            description = "Linear Assignment Problem solver (LAPJV/LAPMOD).";
            homepage = "https://github.com/rathaROG/lapx";
            license = pkgs.lib.licenses.bsd2;
            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 = with pythonPackages; [ numpy torch ];

          nativeBuildInputs = with pythonPackages; [
            setuptools
            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.agpl3Only;
            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 = with pythonPackages; [
            requests
            pyyaml
            torch
            tqdm
            psutil
            torchvision
            pandas
            matplotlib
            seaborn
            py-cpuinfo
            custom-opencv4

            ultralytics-thop
          ];

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

          nativeBuildInputs = with pythonPackages; [
            setuptools
            setuptools-scm
            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.agpl3Only;
            maintainers = with maintainers; [ ];
          };
        };

        # boxmot
        boxmot = pkgs.python3Packages.buildPythonPackage rec {
          version = "0.5.11";
          pname = "lapx";
          pyproject = true;
          src = pkgs.fetchFromGitHub {
            owner = "mikel-brostrom";
            repo = "boxmot";
            rev = "5cbcd86b2716db5c70519b41e12907d351d7f5ff";
            hash = "sha256-fb5qRdR75szHpFwil/uJz3/KAutYtrDVjyYJRZhI3pA=";
            fetchSubmodules = true;
          };

          propagatedBuildInputs = with pythonPackages; [
            loguru
            numpy
            pandas
            pyyaml
            torch
            yacs
            torchvision
            ftfy
            filterpy
            gdown
            regex
            scikit-learn
            gitpython
            custom-opencv4
            pip
            lapx
          ];

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

          nativeBuildInputs = with pythonPackages; [
            setuptools
            setuptools-scm
            poetry-core
          ];

          meta = with pkgs.lib; {
            description = "Linear Assignment Problem solver (LAPJV/LAPMOD).";
            homepage = "https://github.com/mikel-brostrom/boxmot";
            license = pkgs.lib.licenses.agpl3Only;
            maintainers = with maintainers; [ ];
          };
        };

      in {
        packages = {
          python312Packages.lapx = lapx;
          python312Packages.ultralytics-thop = ultralytics-thop;
          python312Packages.ultralytics = ultralytics;
          python312Packages.boxmot = boxmot;
          python312Packages.opencv4 = custom-opencv4;
        };
        devShells.default = pkgs.mkShell {
          buildInputs = [ (pkgs.python312.withPackages (ps: [ ])) ];
        };
      });
}