https://github.com/srijan-singh/voter-verification
Automated voter verification with facial recognition to reduce human error by creating a client-server architecture as part of API development.
https://github.com/srijan-singh/voter-verification
api-rest docker docker-image face-recognition fastapi html-css-javascript microservices python uvicorn
Last synced: 5 months ago
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Automated voter verification with facial recognition to reduce human error by creating a client-server architecture as part of API development.
- Host: GitHub
- URL: https://github.com/srijan-singh/voter-verification
- Owner: srijan-singh
- Created: 2022-12-21T15:05:19.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2023-01-20T03:53:08.000Z (over 3 years ago)
- Last Synced: 2025-04-22T15:11:55.577Z (about 1 year ago)
- Topics: api-rest, docker, docker-image, face-recognition, fastapi, html-css-javascript, microservices, python, uvicorn
- Language: HTML
- Homepage: https://hub.docker.com/r/srijanverse/face-recognition-api
- Size: 1.26 MB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
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README
# Voter Verification
*Automated voter verification with facial recognition to reduce human error by reating a client-server architecture as part of API development.*
## INTRODUCTION
Face detection and face recognition are very important technologies these days, furthermore we noticed that they got have a variety of uses such as smart phones, army uses, and some high risk information offices. Our project will provide services which will allow them to predict and recognize faces.
## OBJECTIVES OF PROJECT WORK
The aim of the project is to create a program that can detect and predict faces from given images.
### Motivation of Project
- Snapchat and Instagram Face Filters
- Face Sorting Software
- Surveillance with Facial Recognition
## RESEARCH GAP
A generic and easy to use solution for all face prediction and recognition solution.
## PROBLEM STATEMENT
To create an API which can detect and recognize voter face from the provided images.
## PROPOSED PROJECT WORK
- ### Algorithm
1. Program will take image as an input.
2. It will detect whether there’s face is present in image.
3. If face is
- Detected it will move forward to predict the face present in the image.
- Not detected terminate the further execution
4. It will save the encoding of the detected face.
5. It will then compare the facial encoding of current image to all present facial encodings in the database.
6. If encodings
- Matched with the encodings in database print the label of the encoding (name of the person).
- Not matched then print unknown.
## Requests
Index (GET) : Homepage of API
Upload (POST) : Upload the image and label to be used as dataset.
Target (POST) : Target image on which prediction has to be done.
Prediction (GET) : Get the prediction.