Sign Language is detected in realtime using video sequences. Our approach involves MediaPipe Holistic for keypoints extraction and LSTM Model for prediction.

Overview

PR's Welcome made-with-python

RealTime Sign Language Detection using Action Recognition

Approach

Real-Time Sign Language is commonly predicted using models whose architecture consists of multiple CNN layers followed by multiple LSTM layers. However , the accuracy of these state of the art models is pretty low. On the other hand, this approach , Mediapipe Holistic with LSTM Model gives a much better accuracy. This approach produced better results with very less amount of data . Since this model trained on fewer parameters, it trained much faster thus resulting in lesser computation time.

Project

This project is divided into two parts:

  1. Keypoints extraction using MediaPipe Holistic
  2. LSTM Model trained on these keypoints to predict realtime sign language using video sequences.

Dataset

Data is collected using MediaPipe Holistic for 3 actions :

  • Hello
  • Thanks
  • I Love You

30 frames have been collected for each action and 30 sequences for each frame have been collected from real time actions using Computer Vision and MediaPipe Holistic. For each sequence , 1662 keypoints have been extracted.

  • Face Landmarks - 468*3
  • Pose Landmarks - 33*4
  • Left Hand Landmarks - 21*3
  • Right Hand Landmarks - 21*3

                   

The dataset can be accessed from the Feature_Extraction Folder.

Model

LSTM Model is trained using the extracted keypoints from the Feature_Extraction folder and later used for real time predictions.

         

The Weights of the model are saved in the lstm_model.h5 file.

How to Use

  • Clone the repository using :

      $ git clone https://github.com/rishusiva/Pose-Network
    
  • Install the requirements using:

      $ cd Pose-Network/
      $ pip install -r requirements.txt
    
  • To Predict Sign Languages in Real Time , run :

      $ cd Pose-Network/Code
      $ python3 realtime_testing.py
    

Results

  • Our LSTM Model, after training for only 100 epochs, has an accuracy of 70%
  • It produced an accuracy score of 1.0 on a test set of 5 images.
  • Our Trained LSTM Model is then used for real time testing.

Prediction Results:

         

Author

  • Rishikesh Sivakumar

ForTheBadge built-with-love by Rishikesh Sivakumar

Owner
Rishikesh S
Currently pursuing Computer Science Engineering. Working towards the upliftment of the machine learning community. Aspiring ML and DL engineer.
Rishikesh S
なりすまし検出(anti-spoof-mn3)のWebカメラ向けデモ

FaceDetection-Anti-Spoof-Demo なりすまし検出(anti-spoof-mn3)のWebカメラ向けデモです。 モデルはPINTO_model_zoo/191_anti-spoof-mn3からONNX形式のモデルを使用しています。 Requirement mediapipe

KazuhitoTakahashi 8 Nov 18, 2022
Unofficial keras(tensorflow) implementation of MAE model from Masked Autoencoders Are Scalable Vision Learners

MAE-keras Unofficial keras(tensorflow) implementation of MAE model described in 'Masked Autoencoders Are Scalable Vision Learners'. This work has been

Yewon 11 Jun 12, 2022
A TensorFlow implementation of SOFA, the Simulator for OFfline LeArning and evaluation.

SOFA This repository is the implementation of SOFA, the Simulator for OFfline leArning and evaluation. Keeping Dataset Biases out of the Simulation: A

22 Nov 23, 2022
Find the Heart simple Python Game

This is a simple Python game for finding a heart emoji. There is a 3 x 3 matrix in which a heart emoji resides. The location of the heart is randomized and is not revealed. The player must guess the

p.katekomol 1 Jan 24, 2022
基于Pytorch实现优秀的自然图像分割框架!(包括FCN、U-Net和Deeplab)

语义分割学习实验-基于VOC数据集 usage: 下载VOC数据集,将JPEGImages SegmentationClass两个文件夹放入到data文件夹下。 终端切换到目标目录,运行python train.py -h查看训练 (torch) Li Xiang 28 Dec 21, 2022

The fastest way to visualize GradCAM with your Keras models.

VizGradCAM VizGradCam is the fastest way to visualize GradCAM in Keras models. GradCAM helps with providing visual explainability of trained models an

58 Nov 19, 2022
Distributional Sliced-Wasserstein distance code

Distributional Sliced Wasserstein distance This is a pytorch implementation of the paper "Distributional Sliced-Wasserstein and Applications to Genera

VinAI Research 39 Jan 01, 2023
face property detection pytorch

This is the face property train code of project face-detection-project

i am x 2 Oct 18, 2021
Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.

HAWQ: Hessian AWare Quantization HAWQ is an advanced quantization library written for PyTorch. HAWQ enables low-precision and mixed-precision uniform

Zhen Dong 293 Dec 30, 2022
i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery

i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery This is a public code repository for the publication: i-SpaSP: Structured Neural Pruning

Cameron Ronald Wolfe 5 Nov 04, 2022
Binary classification for arrythmia detection with ECG datasets.

HEART DISEASE AI DATATHON 2021 [Eng] / [Kor] #English This is an AI diagnosis modeling contest that uses the heart disease echocardiography and electr

HY_Kim 3 Jul 14, 2022
The end-to-end platform for building voice products at scale

Picovoice Made in Vancouver, Canada by Picovoice Picovoice is the end-to-end platform for building voice products on your terms. Unlike Alexa and Goog

Picovoice 318 Jan 07, 2023
The implementation for "Comprehensive Knowledge Distillation with Causal Intervention".

Comprehensive Knowledge Distillation with Causal Intervention This repository is a PyTorch implementation of "Comprehensive Knowledge Distillation wit

Xiang Deng 10 Nov 03, 2022
Scene-Text-Detection-and-Recognition (Pytorch)

Scene-Text-Detection-and-Recognition (Pytorch) Competition URL: https://tbrain.t

Gi-Luen Huang 9 Jan 02, 2023
Efficient Multi Collection Style Transfer Using GAN

Proposed a new model that can make style transfer from single style image, and allow to transfer into multiple different styles in a single model.

Zhaozheng Shen 2 Jan 15, 2022
Multi-Person Extreme Motion Prediction

Multi-Person Extreme Motion Prediction Implementation for paper Wen Guo, Xiaoyu Bie, Xavier Alameda-Pineda, Francesc Moreno-Noguer, Multi-Person Extre

GUO-W 38 Nov 15, 2022
Learning to Prompt for Continual Learning

Learning to Prompt for Continual Learning (L2P) Official Jax Implementation L2P is a novel continual learning technique which learns to dynamically pr

Google Research 207 Jan 06, 2023
A simple API wrapper for Discord interactions.

Your ultimate Discord interactions library for discord.py. About | Installation | Examples | Discord | PyPI About What is discord-py-interactions? dis

james 641 Jan 03, 2023
A Pytorch Implementation of Source Data-free Domain Adaptation for a Faster R-CNN

A Pytorch Implementation of Source Data-free Domain Adaptation for a Faster R-CNN Please follow Faster R-CNN and DAF to complete the environment confi

2 Jan 12, 2022