{"id":23863139,"url":"https://github.com/cnuahs/motion-clouds","last_synced_at":"2025-10-11T00:32:10.684Z","repository":{"id":84775079,"uuid":"163292105","full_name":"cnuahs/motion-clouds","owner":"cnuahs","description":"A Matlab class for generating motion clouds (spatio-temporal random textures).","archived":false,"fork":false,"pushed_at":"2018-12-28T01:47:36.000Z","size":69,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-10-11T00:31:59.641Z","etag":null,"topics":["matlab","motion-cloud","motion-detection","motion-estimation","motion-perception","perception","stimuli","texture-synthesis"],"latest_commit_sha":null,"homepage":"","language":"MATLAB","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/cnuahs.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2018-12-27T12:29:23.000Z","updated_at":"2018-12-28T03:28:49.000Z","dependencies_parsed_at":null,"dependency_job_id":"161cc6b4-836a-46e6-8fa0-7455eaaa0860","html_url":"https://github.com/cnuahs/motion-clouds","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/cnuahs/motion-clouds","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cnuahs%2Fmotion-clouds","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cnuahs%2Fmotion-clouds/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cnuahs%2Fmotion-clouds/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cnuahs%2Fmotion-clouds/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cnuahs","download_url":"https://codeload.github.com/cnuahs/motion-clouds/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cnuahs%2Fmotion-clouds/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279005657,"owners_count":26083942,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-10T02:00:06.843Z","response_time":62,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["matlab","motion-cloud","motion-detection","motion-estimation","motion-perception","perception","stimuli","texture-synthesis"],"created_at":"2025-01-03T07:47:36.302Z","updated_at":"2025-10-11T00:32:10.644Z","avatar_url":"https://github.com/cnuahs.png","language":"MATLAB","funding_links":[],"categories":[],"sub_categories":[],"readme":"# motion-clouds\n\nA Matlab implementation of Laurent Perrinet's (INT - CNRS) motion cloud spatio-temporal random textures.\n\nMotion clouds are a class of random phase textures. Here they are implemented as dense mixtures of localized drifting gratings with random positions.\n\nFor a formal description see:\n\n  Sanz Leon et al., [Motion clouds: model-based stimulus synthesis of\n  natural-like random textures for the study of motion perception](https://www.physiology.org/doi/pdf/10.1152/jn.00737.2011).\n  J. Neurophysiol. 107:3217-3226, 2012.\n\nFor Laurent Perrinet's Python implementation see:\n\n  https://github.com/NeuralEnsemble/MotionClouds.git\n\nExample usage:\n```\nimport motionclouds.*\n\nm = motioncloud(256,256,120);     % 256 x 256 texels, 120 frames\n\n% override default parameters\nm.th = pi/3;                      % mean orientation (radians)\n[m.Vx,m.Vy] = pol2cart(m.th,1.0); % mean horiz. and vert. speed\nm.sf = 32/m.Nx;                   % mean spatial frequency (32 cycles per frame)\nm.alpha = 1.0;                    % 1/f noise spectral density\nm.contrast = 0.12;                % contrast energy\nm.method = 'ENERGY';\n\n% generate the spatio-temporal image sequence\ns = m.getSequence();\n\n% preview it...\nfigure; colormap(gray(256));\nfor ii = 1:m.Nt % loop over frames\n  imagesc(s(:,:,ii); axis image\n  delay(0.020);\nend\n```\n\nThe example above produces a spatio-temporal texture, the first 5 frames of which look something like:\n![example motion cloud](./images/example.png \"Example Motion Cloud\")\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcnuahs%2Fmotion-clouds","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcnuahs%2Fmotion-clouds","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcnuahs%2Fmotion-clouds/lists"}