{"id":15015500,"url":"https://github.com/olafenwamoses/intellip","last_synced_at":"2025-04-12T09:19:22.461Z","repository":{"id":110143805,"uuid":"126251635","full_name":"OlafenwaMoses/IntelliP","owner":"OlafenwaMoses","description":"IntelliP (Intelligent Photos) is a Windows photo gallery that intelligently organizes the  pictures in your computer into 12 unique and related categories.","archived":false,"fork":false,"pushed_at":"2018-07-25T23:53:42.000Z","size":3796,"stargazers_count":21,"open_issues_count":0,"forks_count":11,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-04-12T09:19:10.900Z","etag":null,"topics":["artificial-intelligence","artificial-neural-networks","imageai","kivy","machine-learning","offline-capable","playground","python","python3","resnet-50","windows"],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/OlafenwaMoses.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":"2018-03-21T23:13:41.000Z","updated_at":"2024-06-11T18:46:42.000Z","dependencies_parsed_at":"2023-04-19T20:18:17.511Z","dependency_job_id":null,"html_url":"https://github.com/OlafenwaMoses/IntelliP","commit_stats":{"total_commits":9,"total_committers":2,"mean_commits":4.5,"dds":"0.11111111111111116","last_synced_commit":"cc2d682aac5936ea95644becd92db8e3d431b154"},"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OlafenwaMoses%2FIntelliP","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OlafenwaMoses%2FIntelliP/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OlafenwaMoses%2FIntelliP/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OlafenwaMoses%2FIntelliP/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/OlafenwaMoses","download_url":"https://codeload.github.com/OlafenwaMoses/IntelliP/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248543836,"owners_count":21121838,"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","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":["artificial-intelligence","artificial-neural-networks","imageai","kivy","machine-learning","offline-capable","playground","python","python3","resnet-50","windows"],"created_at":"2024-09-24T19:47:33.161Z","updated_at":"2025-04-12T09:19:22.430Z","avatar_url":"https://github.com/OlafenwaMoses.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# IntelliP\nIntelliP (Intelligent Photos) is a Windows photo gallery that intelligently organizes the  pictures in your computer into 12 unique and related categories.\n\u003chr\u003e\n\u003cdiv style=\"font-family: Calibri;\" \u003e\u003cbr\u003e\u003cspan\u003e\n        It works by scanning through\n        the pictures in your Windows download folder, documents folder, desktop folder, videos folder, pictures\n         folder and it's subfolders. It obtains the pictures and run a self-contained \u003cb\u003eIntelligence Module\u003c/b\u003e prediction\n          on each picture and store the pictures in their respective categories. The \u003cb\u003eIntelligence Module\u003c/b\u003e\n           is made possible by the \u003cb\u003e\u003ca href=\"https://github.com/OlafenwaMoses/ImageAI\" style=\"text-decoration: none;\" \u003eImageAI\u003c/a\u003e\u003c/b\u003e library\n        , that enables applications and systems built with Python to have self-contained image prediction\n         capabilities. \u003cbr\u003e \u003cbr\u003eYou can download the IntelliP Windows installer via this \u003cb\u003e\u003ca href=\"https://github.com/OlafenwaMoses/IntelliP/releases/download/v1/IntelliP.Installer.exe\"\u003elink\u003c/a\u003e\u003c/b\u003e. \u003cbr\u003e\u003cbr\u003e\u003c/span\u003e\n    \u003cbr\u003e\n     \u003cimg src=\"one.jpg\" style=\"width: 200px; height: auto; margin-right: 20px;\" /\u003e\n    \n\u003ch3\u003e\u003cb\u003eDependencies\u003c/b\u003e\u003c/h3\u003e\n\u003chr\u003e\nIntelliP was built using Python 3.5, Kivy (Python UI framework) and \u003cb\u003e\u003ca href=\"https://github.com/OlafenwaMoses/ImageAI\" style=\"text-decoration: none;\" \u003eImageAI\u003c/a\u003e\u003c/b\u003e. The ResNet model is the computer vision model used to power the image prediction. \u003cbr\u003eThe entire source code and resources used in building the \u003cb\u003eIntelliP\u003c/b\u003e application is included in  this repository. The source code have the following dependencies: \u003cbr\u003e\n \u003cspan\u003e\u003cb\u003e- Python 3.5  \u003c/b\u003e\u003c/span\u003e \u003cbr\u003e \n          \u003cspan\u003e\u003cb\u003e- Tensorflow 1.4.0 \u003c/b\u003e\u003c/span\u003e\u003cbr\u003e\n          \u003cspan\u003e\u003cb\u003e- Numpy 1.14.2 \u003c/b\u003e \u003c/span\u003e \u003cbr\u003e\n          \u003cspan\u003e\u003cb\u003e- SciPy 1.0.0 \u003c/b\u003e\u003c/span\u003e \u003cbr\u003e\n          \u003cspan\u003e\u003cb\u003e- ImageAI 1.0.1 \u003c/b\u003e\u003c/span\u003e \u003cbr\u003e\n          \u003cspan\u003e\u003cb\u003e- Kivy 1.10.0 \u003c/b\u003e\u003c/span\u003e \u003cbr\u003e\n          \u003cspan\u003e\u003cb\u003e- Kivy Glew 0.1.9 \u003c/b\u003e\u003c/span\u003e \u003cbr\u003e\n          \u003cspan\u003e\u003cb\u003e- Kivy SDL2 0.1.17 \u003c/b\u003e\u003c/span\u003e \u003cbr\u003e \u003cbr\u003e \u003cspan\u003eIn addition to the files contained in this repository, follow this \u003ca href=\"https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels.h5\"\u003elink\u003c/a\u003e\u003c/span\u003e to \ndownload the ResNet model used in the Intelligence Module. \u003cbr\u003e \u003cbr\u003e\n\u003ch3\u003e\u003cb\u003eContact Developers\u003c/b\u003e\u003c/h3\u003e\n\u003chr\u003e\nThis application was built to demonstrate the potentials contained in the \u003cb\u003e\u003ca href=\"https://github.com/OlafenwaMoses/ImageAI\" style=\"text-decoration: none;\" \u003eImageAI\u003c/a\u003e\u003c/b\u003e\n python library for application and systems developements. You can reach to us via our contacts below:\n \u003cbr\u003e\u003cbr\u003e\n  \u003cb\u003eMoses Olafenwa\u003c/b\u003e \u003cbr\u003e\n \u003ci\u003eWebsite: \u003c/i\u003e  \u003ca style=\"text-decoration: none;\" href=\"https://moses.specpal.science\"\u003e https://moses.specpal.science\u003c/a\u003e \u003cbr\u003e\n \u003ci\u003eTwitter: \u003c/i\u003e    \u003ca style=\"text-decoration: none;\" href=\"https://twitter.com/OlafenwaMoses\"\u003e @OlafenwaMoses\u003c/a\u003e \u003cbr\u003e\n      \u003ci\u003eMedium : \u003c/i\u003e    \u003ca style=\"text-decoration: none;\" href=\"https://medium.com/@guymodscientist\"\u003e @guymodscientist\u003c/a\u003e \u003cbr\u003e\n      \u003ci\u003eFacebook : \u003c/i\u003e    \u003ca style=\"text-decoration: none;\" href=\"https://facebook.com/moses.olafenwa\"\u003e moses.olafenwa\u003c/a\u003e \u003cbr\u003e\n\u003cbr\u003e\u003cbr\u003e\n      \u003cb\u003eJohn Olafenwa\u003c/b\u003e \u003cbr\u003e\n      \u003ci\u003eWebsite: \u003c/i\u003e    \u003ca style=\"text-decoration: none;\" href=\"https://john.specpal.science\"\u003e https://john.specpal.science\u003c/a\u003e \u003cbr\u003e\n      \u003ci\u003eTwitter: \u003c/i\u003e    \u003ca style=\"text-decoration: none;\" href=\"https://twitter.com/johnolafenwa\"\u003e @johnolafenwa\u003c/a\u003e \u003cbr\u003e\n      \u003ci\u003eMedium : \u003c/i\u003e    \u003ca style=\"text-decoration: none;\" href=\"https://medium.com/@johnolafenwa\"\u003e @johnolafenwa\u003c/a\u003e \u003cbr\u003e\n      \u003ci\u003eFacebook : \u003c/i\u003e    \u003ca style=\"text-decoration: none;\" href=\"https://facebook.com/olafenwajohn\"\u003e olafenwajohn\u003c/a\u003e \u003cbr\u003e\n\n\u003c/div\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Folafenwamoses%2Fintellip","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Folafenwamoses%2Fintellip","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Folafenwamoses%2Fintellip/lists"}