Face Mask Detector by live camera using tensorflow-keras, openCV and Python

Overview

Face Mask Detector ๐Ÿ˜ท

by Live Camera

  • Detecting masked or unmasked faces by live camera with percentange of mask occupation

About Project:

This an Artificial Intelligence based project in which we can detect person's faces by live camera and system can predict that person weared a mask or not. A programming language that I used in this project is Python. Where I build a predective model with the help of Neural Networks (Deep Learning). Dataset contains two classes that means two type of images such as With Mask and Without Mask

Overview:

  1. Importing machine learning libraries - Tensorflow, Keras and Sklearn
  2. Loading dataset and divding into two categories - With Mask and Without Mask
  3. Converting Categories into numbers by LabelBinarizer
  4. Splitting data into train, test and split
  5. Data Augmentation by ImageDataGenerator
  6. Creating neural network with MobileNetV2, and connected entire layers
  7. Compiling the model Adam optimizer and binray_cross entropy loss
  8. Using callbacks while model training to avoid overfitting
  9. Evaluating the model by classification report and confusion matrix
  10. Visualized model accuracy and val_loss
  11. Serializing the model and implementing into python code for live camera
  12. Using OpenCv and imutils for live implementation

Live Demo:

https://twitter.com/KuchBhiKaran/status/1482999558536036352?t=RgL5Rt0QA9uZgXHCNAHKuQ&s=19

Owner
Karan Shingde
Data Science | Machine Learning | Computer Science student ๐Ÿš€๐Ÿ“Š
Karan Shingde
Code for the paper "Offline Reinforcement Learning as One Big Sequence Modeling Problem"

Trajectory Transformer Code release for Offline Reinforcement Learning as One Big Sequence Modeling Problem. Installation All python dependencies are

Michael Janner 266 Dec 27, 2022
Data reduction pipeline for KOALA on the AAT.

KOALA KOALA, the Kilofibre Optical AAT Lenslet Array, is a wide-field, high efficiency, integral field unit used by the AAOmega spectrograph on the 3.

4 Sep 26, 2022
Code for Domain Adaptive Video Segmentation via Temporal Consistency Regularization in ICCV 2021

Domain Adaptive Video Segmentation via Temporal Consistency Regularization Updates 08/2021: check out our domain adaptation for sematic segmentation p

36 Dec 12, 2022
Setup and customize deep learning environment in seconds.

Deepo is a series of Docker images that allows you to quickly set up your deep learning research environment supports almost all commonly used deep le

Ming 6.3k Jan 06, 2023
Official implementation for paper Render In-between: Motion Guided Video Synthesis for Action Interpolation

Render In-between: Motion Guided Video Synthesis for Action Interpolation [Paper] [Supp] [arXiv] [4min Video] This is the official Pytorch implementat

8 Oct 27, 2022
Ratatoskr: Worcester Tech's conference scheduling system

Ratatoskr: Worcester Tech's conference scheduling system In Norse mythology, Ratatoskr is a squirrel who runs up and down the world tree Yggdrasil to

4 Dec 22, 2022
Semi-supervised Transfer Learning for Image Rain Removal. In CVPR 2019.

Semi-supervised Transfer Learning for Image Rain Removal This package contains the Python implementation of "Semi-supervised Transfer Learning for Ima

Wei Wei 59 Dec 26, 2022
๐Ÿƒโ€โ™€๏ธ A curated list about human motion capture, analysis and synthesis.

Awesome Human Motion ๐Ÿƒโ€โ™€๏ธ A curated list about human motion capture, analysis and synthesis. Contents Introduction Human Models Datasets Data Process

Dennis Wittchen 274 Dec 14, 2022
Real time sign language recognition

The proposed work aims at converting american sign language gestures into English that can be understood by everyone in real time.

Mohit Kaushik 6 Jun 13, 2022
GT4SD, an open-source library to accelerate hypothesis generation in the scientific discovery process.

The GT4SD (Generative Toolkit for Scientific Discovery) is an open-source platform to accelerate hypothesis generation in the scientific discovery process. It provides a library for making state-of-t

Generative Toolkit 4 Scientific Discovery 142 Dec 24, 2022
A simple implementation of Kalman filter in single object tracking

kalman-filter-in-single-object-tracking A simple implementation of Kalman filter in single object tracking https://www.bilibili.com/video/BV1Qf4y1J7D4

130 Dec 26, 2022
(Python, R, C/C++) Isolation Forest and variations such as SCiForest and EIF, with some additions (outlier detection + similarity + NA imputation)

IsoTree Fast and multi-threaded implementation of Extended Isolation Forest, Fair-Cut Forest, SCiForest (a.k.a. Split-Criterion iForest), and regular

141 Dec 29, 2022
Deploy pytorch classification model using Flask and Streamlit

Deploy pytorch classification model using Flask and Streamlit

Ben Seo 1 Nov 17, 2021
Tutorials, assignments, and competitions for MIT Deep Learning related courses.

MIT Deep Learning This repository is a collection of tutorials for MIT Deep Learning courses. More added as courses progress. Tutorial: Deep Learning

Lex Fridman 9.5k Jan 07, 2023
Classification models 1D Zoo - Keras and TF.Keras

Classification models 1D Zoo - Keras and TF.Keras This repository contains 1D variants of popular CNN models for classification like ResNets, DenseNet

Roman Solovyev 12 Jan 06, 2023
MonoRCNN is a monocular 3D object detection method for automonous driving

MonoRCNN MonoRCNN is a monocular 3D object detection method for automonous driving, published at ICCV 2021. This project is an implementation of MonoR

87 Dec 27, 2022
Official PyTorch Implementation for InfoSwap: Information Bottleneck Disentanglement for Identity Swapping

InfoSwap: Information Bottleneck Disentanglement for Identity Swapping Code usage Please check out the user manual page. Paper Gege Gao, Huaibo Huang,

Grace Heลกeri 56 Dec 20, 2022
Ranking Models in Unlabeled New Environments ๏ผˆiccv21๏ผ‰

Ranking Models in Unlabeled New Environments Prerequisites This code uses the following libraries Python 3.7 NumPy PyTorch 1.7.0 + torchivision 0.8.1

14 Dec 17, 2021
Out of Distribution Detection on Natural Adversarial Examples

OOD-on-NAE Research project on out of distribution detection for the Computer Vision course by Prof. Rob Fergus (CSCI-GA 2271) Paper out on arXiv - ht

Anugya 1 Jun 08, 2022
An implementation of the Contrast Predictive Coding (CPC) method to train audio features in an unsupervised fashion.

CPC_audio This code implements the Contrast Predictive Coding algorithm on audio data, as described in the paper Unsupervised Pretraining Transfers we

Meta Research 283 Dec 30, 2022