https://github.com/saberglow/deja-vu
🎯 A facial recognition/detection app with Angular using Microsoft's Face API
https://github.com/saberglow/deja-vu
angular azure-cognitive-services face-api face-detection mdbootstrap model-training
Last synced: 6 months ago
JSON representation
🎯 A facial recognition/detection app with Angular using Microsoft's Face API
- Host: GitHub
- URL: https://github.com/saberglow/deja-vu
- Owner: SABERGLOW
- License: mit
- Created: 2022-04-21T17:59:30.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-08-06T12:57:06.000Z (about 3 years ago)
- Last Synced: 2025-04-30T15:14:47.849Z (6 months ago)
- Topics: angular, azure-cognitive-services, face-api, face-detection, mdbootstrap, model-training
- Language: TypeScript
- Homepage: https://saberglow.github.io/Deja-Vu/
- Size: 1.98 MB
- Stars: 5
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
Deja-Vu
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---
# Overview
Deja-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.
---
# Features and Capabilities
The application is capable of following functionalities, with room for improvement:
- **Detect:** Facial features and attributes of a single person can be detected by uploading an image.
- **Train:** A Person Group can be creaeted, withinn which, a Person can be created and his/her images can be trained.
- **Identify:** A person can be identified from a pre-existing and pre-trained Person Group.
*For more detail, please refer to [Azure Face API documentation](https://docs.microsoft.com/en-us/azure/cognitive-services/face/).*
*PRs and Contributions are welcome.*
---
# Tech Stack
The application is built using following technologies:
- **[Angular 13](https://angular.io/)**
- **[MDB (Material Design for Bootstrap 5 & Angular 13)](https://mdbootstrap.com/docs/b5/angular/)**
- **[Face API](https://azure.microsoft.com/en-us/services/cognitive-services/face/)**
- **[Compodoc](https://compodoc.app/)**
---
# Project Structure
A general overlay of Project Structure and it's components and assets.
---
## Development server
Run `ng serve` for a dev server. Navigate to `http://localhost:4200/`. The application will automatically reload if you change any of the source files.
## Build
Run `ng build` to build the project. The build artifacts will be stored in the `dist/` directory.
---
## Documentation [](https://github.com/SABERGLOW/Deja-Vu/actions/workflows/pages/pages-build-deployment)
Developer 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`.
---
## Sample Face Attrbutes Response
``` js
[
{
"faceId": "49d55c17-e018-4a42-ba7b-8cbbdfae7c6f",
"faceRectangle": {
"top": 131,
"left": 177,
"width": 162,
"height": 162
},
"faceAttributes": {
"smile": 0,
"headPose": {
"pitch": 0,
"roll": 0.1,
"yaw": -32.9
},
"gender": "female",
"age": 22.9,
"facialHair": {
"moustache": 0,
"beard": 0,
"sideburns": 0
},
"glasses": "NoGlasses",
"emotion": {
"anger": 0,
"contempt": 0,
"disgust": 0,
"fear": 0,
"happiness": 0,
"neutral": 0.986,
"sadness": 0.009,
"surprise": 0.005
},
"blur": {
"blurLevel": "low",
"value": 0.06
},
"exposure": {
"exposureLevel": "goodExposure",
"value": 0.67
},
"noise": {
"noiseLevel": "low",
"value": 0
},
"makeup": {
"eyeMakeup": true,
"lipMakeup": true
},
"accessories": [],
"occlusion": {
"foreheadOccluded": false,
"eyeOccluded": false,
"mouthOccluded": false
},
"hair": {
"bald": 0,
"invisible": false,
"hairColor": [
{
"color": "brown",
"confidence": 1
},
{
"color": "black",
"confidence": 0.87
},
{
"color": "other",
"confidence": 0.51
},
{
"color": "blond",
"confidence": 0.08
},
{
"color": "red",
"confidence": 0.08
},
{
"color": "gray",
"confidence": 0.02
}
]
}
}
}
]
```