In this project we are able to detect signs notations in online video call meeting by applying deep learning model in the online video call meeting. The front end of this android application is created by using flutter and also the video calling module is made by flutter and than our deep
Signicate
In this project we are able to detect signs notations in online video call meeting by applying deep learning model in the online video call meeting. The front end of this android application is created by using flutter and also the video calling module is made by flutter and than our deep learning model which is trained by using python ( tensorflow, open Cv) is integrated in our flutter application
The main objectives of this project is provide the communication method to the aphasic people and also to remove the communication barrier between aphasic people and the normal people
The front end of our android application is done by flutter which includes sign up , sign in and the front look of the application,The database of storing the user is done by using the firebase after this we use the video calling appliction sdk in our flutter application which help us to create our online video calling meeting. Than we train our deep learning model in python which help us to detect the sign notations and intergrate this model in our flutter video calling Application.
This project helps many aphasic people to convey their messages to someone who don't have idea of sign language .Basically this project help to remove the communication barrier between aphasic people and normal people.
The tools which the using in this projects are vs code for flutter development and the jupyter notebook which is used for training deep learning model.
The final deliverable of this project is an adroid application which provides way of communication to the aphasic people.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| GPU | Equipment | 1 | 50000 | 50000 |
| RAM | Equipment | 1 | 5000 | 5000 |
| SSD | Equipment | 1 | 5000 | 5000 |
| Total in (Rs) | 60000 |
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