Predicting Student Attentiveness using OpenCV

Overview

Predicting-Student-Attentiveness-using-OpenCV

The model will predict if a student is attentive or not through facial parameter received through the student's webcam using Face Detection, Drowsiness Detection, and Head Pose Estimation

Libraries Used (To be installed to execute program)

  1. cv2
  2. dlib
  3. numpy
  4. mediapipe
  5. imutils
  6. scipy
  7. glob

Information :

  1. data : The data folder contains test images for cam_calibration.py and a '.dat' file used for placing landmarks on the face using dlib library.

  2. face detectors : This folder contains two face detector models that were used to implement Drowsiness Detection and Head Pose Estimation.

  3. helpermod : This folder contains two helper modules used for implementing Head Pose Estimation.

  4. Drowsiness_Detection.py : The main program for implementing Drowsiness Detection to predict Student Attentiveness.

  5. cam_calibration.py : This program is to be run before running headposedlib.py to implement Head Pose Estimation correctly.

  6. headposedlib.py : This contains the main program for implementing Head Pose Estimation to predict Student Attentiveness.

Steps to run the Program :

  1. Install all the required library packages in your python environment.
  2. Drowsiness_Detection.py can then be run. A new window will popup with the webcamera turning on and the video will displayed on this window. The program will detect face and check if the eyes are opened or closed to predict if the student is attentive or not attentive. To exit the program , press the ESC key.
  3. Run cam_calibration.py, this will give the approximate focal length as output. This focal length has to be modified in the headposedlib.py for correct implementation.
  4. In headposedlib.py, modify the focal length 'f' to the nearest intger value received as output of the cam_calibration.py program.

image

  1. After updating the focal length 'f', run headposedlib.py. A new window will popup with the webcamera turning on and the video will displayed on this window.The program will estimate the position of the head to predict if the student is attentive or not attentive. To exit the program, press the ESC key.
Note : The face detector models used to run Drowsiness_Detection.py and headposedlib.py are given for reference.

Both these programs can be run after the required libraries are installed. Both these programs will open a new window with your video capture through the webcam and will detect the face on the video. To exit these programs, press the ESC key.

Project Done By

Johann Kyle Pinto
Reg No. : 20BKT0009

Owner
Johann Pinto
Johann Pinto
An Artificial Intelligence trying to drive a car by itself on a user created map

An Artificial Intelligence trying to drive a car by itself on a user created map

Akhil Sahukaru 17 Jan 13, 2022
A python bot to move your mouse every few seconds to appear active on Skype, Teams or Zoom as you go AFK. 🐭 🤖

PyMouseBot If you're from GT and annoyed with SGVPN idle timeouts while working on development laptop, You might find this useful. A python cli bot to

Oaker Min 6 Oct 24, 2022
[ACL 20] Probing Linguistic Features of Sentence-level Representations in Neural Relation Extraction

REval Table of Contents Introduction Overview Requirements Installation Probing Usage Citation License 🎓 Introduction REval is a simple framework for

13 Jan 06, 2023
[CVPR 2022] "The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy" by Tianlong Chen, Zhenyu Zhang, Yu Cheng, Ahmed Awadallah, Zhangyang Wang

The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy Codes for this paper: [CVPR 2022] The Pr

VITA 16 Nov 26, 2022
Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

Parallel Tacotron2 Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

Keon Lee 170 Dec 27, 2022
PyTorch implementation of convolutional neural networks-based text-to-speech synthesis models

Deepvoice3_pytorch PyTorch implementation of convolutional networks-based text-to-speech synthesis models: arXiv:1710.07654: Deep Voice 3: Scaling Tex

Ryuichi Yamamoto 1.8k Jan 08, 2023
exponential adaptive pooling for PyTorch

AdaPool: Exponential Adaptive Pooling for Information-Retaining Downsampling Abstract Pooling layers are essential building blocks of Convolutional Ne

Alexandros Stergiou 55 Jan 04, 2023
BookMyShowPC - Movie Ticket Reservation App made with Tkinter

Book My Show PC What is this? Movie Ticket Reservation App made with Tkinter. Tk

The Nithin Balaji 3 Dec 09, 2022
Byzantine-robust decentralized learning via self-centered clipping

Byzantine-robust decentralized learning via self-centered clipping In this paper, we study the challenging task of Byzantine-robust decentralized trai

EPFL Machine Learning and Optimization Laboratory 4 Aug 27, 2022
Fast, differentiable sorting and ranking in PyTorch

Torchsort Fast, differentiable sorting and ranking in PyTorch. Pure PyTorch implementation of Fast Differentiable Sorting and Ranking (Blondel et al.)

Teddy Koker 655 Jan 04, 2023
Unpaired Caricature Generation with Multiple Exaggerations

CariMe-pytorch The official pytorch implementation of the paper "CariMe: Unpaired Caricature Generation with Multiple Exaggerations" CariMe: Unpaired

Gu Zheng 37 Dec 30, 2022
mmfewshot is an open source few shot learning toolbox based on PyTorch

OpenMMLab FewShot Learning Toolbox and Benchmark

OpenMMLab 514 Dec 28, 2022
Official PyTorch implementation of Learning Intra-Batch Connections for Deep Metric Learning (ICML 2021) published at International Conference on Machine Learning

About This repository the official PyTorch implementation of Learning Intra-Batch Connections for Deep Metric Learning. The config files contain the s

Dynamic Vision and Learning Group 41 Dec 10, 2022
Dataset used in "PlantDoc: A Dataset for Visual Plant Disease Detection" accepted in CODS-COMAD 2020

PlantDoc: A Dataset for Visual Plant Disease Detection This repository contains the Cropped-PlantDoc dataset used for benchmarking classification mode

Pratik Kayal 109 Dec 29, 2022
KSAI Lite is a deep learning inference framework of kingsoft, based on tensorflow lite

KSAI Lite is a deep learning inference framework of kingsoft, based on tensorflow lite

80 Dec 27, 2022
darija <-> english dictionary

darija-dictionary Having advanced IT solutions that are well adapted to the Moroccan context passes inevitably through understanding Moroccan dialect.

DODa 102 Jan 01, 2023
Fast mesh denoising with data driven normal filtering using deep variational autoencoders

Fast mesh denoising with data driven normal filtering using deep variational autoencoders This is an implementation for the paper entitled "Fast mesh

9 Dec 02, 2022
Streamlit tool to explore coco datasets

What is this This tool given a COCO annotations file and COCO predictions file will let you explore your dataset, visualize results and calculate impo

Jakub Cieslik 75 Dec 16, 2022
U^2-Net - Portrait matting This repository explores possibilities of using the original u^2-net model for portrait matting.

U^2-Net - Portrait matting This repository explores possibilities of using the original u^2-net model for portrait matting.

Dennis Bappert 104 Nov 25, 2022
Finetune the base 64 px GLIDE-text2im model from OpenAI on your own image-text dataset

Finetune the base 64 px GLIDE-text2im model from OpenAI on your own image-text dataset

Clay Mullis 82 Oct 13, 2022