https://github.com/aashishrai3799/face-detection-and-tracking

Detect Faces in images, videos and live camera feed.
https://github.com/aashishrai3799/face-detection-and-tracking

cnn-classification deep-learning face-detection mtcnn-face-detection opencv3-python tensorflow-examples

Last synced: about 1 month ago
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Detect Faces in images, videos and live camera feed.

• Host: GitHub
• URL: https://github.com/aashishrai3799/face-detection-and-tracking
• Owner: aashishrai3799
• License: mit
• Created: 2019-07-01T14:36:52.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2019-09-14T10:39:58.000Z (over 5 years ago)
• Last Synced: 2025-01-22T15:35:02.490Z (3 months ago)
• Topics: cnn-classification, deep-learning, face-detection, mtcnn-face-detection, opencv3-python, tensorflow-examples
• Language: Python
• Homepage:
• Size: 1.92 MB
• Stars: 3
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Face-detection-MTCNN

Detect Faces in images and live webcam feed

## Introduction

MTCNN (Multi-task Cascaded Convolutional Neural Networks) is an algorithm consisting of 3 stages, which detects the bounding boxes of faces in an image along with their 5 Point Face Landmarks. Each stage gradually improves the detection results by passing it’s inputs through a CNN, which returns candidate bounding boxes with their scores, followed by non max suppression.

## Working

This is an implementation of MTCNN. MTCNN gives 5 keypoints in a face, using those 5 keypoints, this code generates 4 more keypoints. It can detect multiple faces in an image or in live webcam feed. 

## Libraries

* opencv _ _ _ _ _ _ 4.1

* tensorflow _ _ _ _ 1.14

* numpy _ _ _ _ _ _ 1.16

* os

* mtcnn

## Sample Images