{"id":20774358,"url":"https://github.com/saberglow/deja-vu","last_synced_at":"2025-04-30T15:14:51.604Z","repository":{"id":123184172,"uuid":"484153858","full_name":"SABERGLOW/Deja-Vu","owner":"SABERGLOW","description":"🎯 A facial recognition/detection app with Angular using Microsoft's Face API","archived":false,"fork":false,"pushed_at":"2022-08-06T12:57:06.000Z","size":2078,"stargazers_count":5,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-30T15:14:47.849Z","etag":null,"topics":["angular","azure-cognitive-services","face-api","face-detection","mdbootstrap","model-training"],"latest_commit_sha":null,"homepage":"https://saberglow.github.io/Deja-Vu/","language":"TypeScript","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/SABERGLOW.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":"2022-04-21T17:59:30.000Z","updated_at":"2023-06-14T07:54:37.000Z","dependencies_parsed_at":null,"dependency_job_id":"f71e42b3-d986-4827-97b8-f88fff47a63c","html_url":"https://github.com/SABERGLOW/Deja-Vu","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SABERGLOW%2FDeja-Vu","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SABERGLOW%2FDeja-Vu/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SABERGLOW%2FDeja-Vu/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SABERGLOW%2FDeja-Vu/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/SABERGLOW","download_url":"https://codeload.github.com/SABERGLOW/Deja-Vu/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251729734,"owners_count":21634281,"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":["angular","azure-cognitive-services","face-api","face-detection","mdbootstrap","model-training"],"created_at":"2024-11-17T12:29:13.565Z","updated_at":"2025-04-30T15:14:51.597Z","avatar_url":"https://github.com/SABERGLOW.png","language":"TypeScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ch1 align=\"center\"\u003eDeja-Vu\u003c/h1\u003e\n\n\u003cp align=\"center\"\u003e\n\n\u003cimg src=\"https://socialify.git.ci/SABERGLOW/Deja-Vu/image?description=1\u0026descriptionEditable=A%20facial%20recognition%2Fdetection%20app%20with%20Angular%20using%20Microsoft%27s%20Face%20API\u0026font=Raleway\u0026forks=1\u0026issues=1\u0026language=1\u0026logo=https%3A%2F%2Fgithub.com%2FSABERGLOW%2FDeja-Vu%2Fblob%2Fmain%2Fsrc%2Fassets%2Fimages%2FDeja-Vu.png%3Fraw%3Dtrue\u0026name=1\u0026owner=1\u0026pattern=Circuit%20Board\u0026pulls=1\u0026stargazers=1\u0026theme=Dark\" alt=\"Deja-Vu Banner\"\u003e\n\n\u003c/p\u003e\n\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\n---\n\n# Overview\n\nDeja-Vu is a client side application generated with [Angular CLI](https://github.com/angular/angular-cli) version 13. The core function of this application is to detect, recognize and analyze human faces by uploading images to the web application with the help of Microsoft's Face API; An AI service that analyzes faces in images. Face API's features include face detection that perceives facial features and attributes—such as a face mask, glasses, or face location—in an image, and identification of a person by a match to your private repository or via photo ID.\n\n---\n\n# Features and Capabilities\n\nThe application is capable of following functionalities, with room for improvement:\n\n- **Detect:** Facial features and attributes of a single person can be detected by uploading an image.\n- **Train:** A Person Group can be creaeted, withinn which, a Person can be created and his/her images can be trained.\n- **Identify:** A person can be identified from a pre-existing and pre-trained Person Group.\n\n*For more detail, please refer to [Azure Face API documentation](https://docs.microsoft.com/en-us/azure/cognitive-services/face/).*\n*PRs and Contributions are welcome.*\n\n---\n\n# Tech Stack\n\nThe application is built using following technologies:\n\n- **[Angular 13](https://angular.io/)**\n- **[MDB (Material Design for Bootstrap 5 \u0026 Angular 13)](https://mdbootstrap.com/docs/b5/angular/)**\n- **[Face API](https://azure.microsoft.com/en-us/services/cognitive-services/face/)**\n- **[Compodoc](https://compodoc.app/)**\n\n---\n\n# Project Structure\n\nA general overlay of Project Structure and it's components and assets.\n\n\u003cp align=\"left\"\u003e\n\n\u003cimg src=\"./src/assets/images/ProjectStructureTree.png\" alt=\"Project Structure\" width=\"40%\"/\u003e\n\n\u003c/p\u003e\n\n---\n\n## Development server\n\nRun `ng serve` for a dev server. Navigate to `http://localhost:4200/`. The application will automatically reload if you change any of the source files.\n\n## Build\n\nRun `ng build` to build the project. The build artifacts will be stored in the `dist/` directory.\n\n---\n\n## Documentation [![GitHub Pages Deployment](https://github.com/SABERGLOW/Deja-Vu/actions/workflows/pages/pages-build-deployment/badge.svg?branch=main)](https://github.com/SABERGLOW/Deja-Vu/actions/workflows/pages/pages-build-deployment)\n\nDeveloper Documentation is available through `compodoc`. The documentation website can be served locally by running `npm run compodoc`, and is accessible at `http://127.0.0.1:8080`.\n\n---\n\n## Sample Face Attrbutes Response\n\n``` js\n[\n  {\n    \"faceId\": \"49d55c17-e018-4a42-ba7b-8cbbdfae7c6f\",\n    \"faceRectangle\": {\n      \"top\": 131,\n      \"left\": 177,\n      \"width\": 162,\n      \"height\": 162\n    },\n    \"faceAttributes\": {\n      \"smile\": 0,\n      \"headPose\": {\n        \"pitch\": 0,\n        \"roll\": 0.1,\n        \"yaw\": -32.9\n      },\n      \"gender\": \"female\",\n      \"age\": 22.9,\n      \"facialHair\": {\n        \"moustache\": 0,\n        \"beard\": 0,\n        \"sideburns\": 0\n      },\n      \"glasses\": \"NoGlasses\",\n      \"emotion\": {\n        \"anger\": 0,\n        \"contempt\": 0,\n        \"disgust\": 0,\n        \"fear\": 0,\n        \"happiness\": 0,\n        \"neutral\": 0.986,\n        \"sadness\": 0.009,\n        \"surprise\": 0.005\n      },\n      \"blur\": {\n        \"blurLevel\": \"low\",\n        \"value\": 0.06\n      },\n      \"exposure\": {\n        \"exposureLevel\": \"goodExposure\",\n        \"value\": 0.67\n      },\n      \"noise\": {\n        \"noiseLevel\": \"low\",\n        \"value\": 0\n      },\n      \"makeup\": {\n        \"eyeMakeup\": true,\n        \"lipMakeup\": true\n      },\n      \"accessories\": [],\n      \"occlusion\": {\n        \"foreheadOccluded\": false,\n        \"eyeOccluded\": false,\n        \"mouthOccluded\": false\n      },\n      \"hair\": {\n        \"bald\": 0,\n        \"invisible\": false,\n        \"hairColor\": [\n          {\n            \"color\": \"brown\",\n            \"confidence\": 1\n          },\n          {\n            \"color\": \"black\",\n            \"confidence\": 0.87\n          },\n          {\n            \"color\": \"other\",\n            \"confidence\": 0.51\n          },\n          {\n            \"color\": \"blond\",\n            \"confidence\": 0.08\n          },\n          {\n            \"color\": \"red\",\n            \"confidence\": 0.08\n          },\n          {\n            \"color\": \"gray\",\n            \"confidence\": 0.02\n          }\n        ]\n      }\n    }\n  }\n]\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaberglow%2Fdeja-vu","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsaberglow%2Fdeja-vu","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaberglow%2Fdeja-vu/lists"}