Luke Granger-Brown
57725ef3ec
git-subtree-dir: third_party/nixpkgs git-subtree-split: 76612b17c0ce71689921ca12d9ffdc9c23ce40b2
43 lines
1.3 KiB
Nix
43 lines
1.3 KiB
Nix
{ lib
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, stdenv
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, eigen
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, fetchFromGitHub
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, cmake
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}:
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stdenv.mkDerivation (finalAttrs: {
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pname = "opengv";
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version = "0-unstable-2020-08-06";
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src = fetchFromGitHub {
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owner = "laurentkneip";
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repo = "opengv";
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rev = "91f4b19c73450833a40e463ad3648aae80b3a7f3";
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hash = "sha256-LfnylJ9NCHlqjT76Tgku4NwxULJ+WDAcJQ2lDKGWSI4=";
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};
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nativeBuildInputs = [
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cmake
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];
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buildInputs = [
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eigen
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];
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meta = {
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description = "Collection of computer vision methods for solving geometric vision problems";
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homepage = "https://github.com/laurentkneip/opengv";
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license = lib.licenses.bsd2;
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longDescription = ''
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OpenGV is a collection of computer vision methods for solving
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geometric vision problems. It contains absolute-pose, relative-pose,
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triangulation, and point-cloud alignment methods for the calibrated
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case. All problems can be solved with central or non-central cameras,
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and embedded into a random sample consensus or nonlinear optimization
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context. Matlab and Python interfaces are implemented as well. The link
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to the above pages also shows links to precompiled Matlab mex-libraries.
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Please consult the documentation for more information.
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'';
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maintainers = [ lib.maintainers.locochoco ];
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platforms = lib.platforms.all;
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};
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})
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