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Final Year Project serving the sign language translator with custom made capability

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Hi there

Project Title

Sign Language Recognition

Getting Started

All the source code is available on this repo. It requires python version 3.6 or later as to synchronize with tensorflow.

  • winGuiAuto.py available inside source code directory contains the hwnd handler which is used to tweak the default window behavior much similar to windows programming.
  • The Recognise.py will recognise the gesture as per the trained dataset, recogniseAppend.py file will make a formation of sentences. These are acting as the stubs for this project. This project has been developed module wise and then has been integrated into a whole full fledge application. Long press 'escape' key for exiting a window.
  • gestfinal2.min.mp4 is the introductory video demonstration of the complete application. icons and UI_Files directory contains all the necessary front end assets.
  • Capture.py file will help in creating your own dataset and cnn_model.py file will use cnn deep neural nets to train your model and store it in the form of hadoop distributed (h5) format.
  • Build the model with name "ASLModel.h5" using cnn_model.py or give any name just modify the line 38 inside "Dashboard.py"
  • Install the required libraries and packages.
  • Start using the application by simply double clicking "Dashboard.py"
  • If you want to move the placing of the window then simply refer to the coordinates available inside cv2.moveWindow() functions.

Prerequisites

  • python 3.6 or later
  • pyqt5, tkinter
  • keyboard
  • winGuiAuto
  • pypiwin32
  • pyttsx3
  • tensorflow
  • keras
  • scipy
  • opencv
  • qimage2ndarray
  • keras
  • pillow

Installing

Download the software setups and follow the on screen instructions

step 1

Installing python 3.7.1 can be downloaded from below link

Click here to visit download page

step 2

Installing pyqt5 with the following command
pip install pyqt5

Note: If getting error related to 'No module named PyQt5.sip' you are expected to do as follows:
pip uninstall PyQt5 PyQt5-sip PyQtWebEngine
pip install PyQt5

Reference link

step 3

Installing keyboard with the following command
pip install keyboard

step 4 (optional)

Downloading winGuiAuto.py from the below link, and pasting it to Python installation directory->Lib->Site-Packages
make sure path is registered on system variables.

Click here to visit download page

step 5

Installing win32api,win32con,win32gui with the following command
pip install pypiwin32

step 6

Installing pyttsx3 with the following command
pip install pyttsx3

step 7

Installing tensorflow framework with the following command
python -m pip install tensorflow --trusted-host files.pythonhosted.org --trusted-host pypi.org --trusted-host pypi.python.org
For upgradation use the following command
pip install tensorflow==2.0.0-alpha0

step 8

Installing keras with the following command
pip install keras

Note: (if keras doesnt work just replace keras.model to tensorflow.keras.model and keras.preprocessing to tensorflow.keras.preprocessing on line 37 and 156 respectively)

step 9

Installing PIL with the following command
pip install pillow

step 10

Installing qimage2ndarray with the following command
pip install qimage2ndarray

step 11

Installing scipy with the following command
pip install scipy

step 12

Installing opencv for python with the following commands
pip install opencv-python==3.4.2.16
pip install opencv-contrib-python==3.4.2.16

Edited on 4th June, 2021 After abundance of request and observation following changes has been made

  • The Dataset required for training the model is available inside Dataset Directory. Also, the trained model has been made available with the consent of all the sakeholders for totally Non-Commercial purpose only.
  • This project now works on python 3.7x interpreter platform as well fully tested as of the above mentioned date.
  • The complexity of step 4 has been reduced, the file is available inside the source code folder itself and if you are okay to not use winGuiAuto functions globally then you can skip this step.
  • The minimize window is now present with the window border so that the application can be moved and the mask window can be placed properly.

Concerning to the students, it is highly appreciable and encouraging if you are willing to build your own datasets as the key should be on learning and not just downloading/copy pasting to just get rid of the submissions.

Built With

  • Sublime - A sophisticated text editor for code, markup and prose.
  • QT Designer - Qt tool for designing and building graphical user interfaces.

Demonstrations

  • Take a look at the working project demonstration. Click on the image to view the complete video

Sign Language Recognition

Acknowledgments

  • The template of readme.md was taken from PurpleBooth
  • Mr. Muhammed Salman Shamsi Asst. Prof Kalsekar Technical campus - For his guidance.
  • Mr. Rupesh Poudel Repo- For his assistance and permission to use his existing application.

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Final Year Project serving the sign language translator with custom made capability

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