Was created with the help of Ahmed Hafez Omar Ayman Moamon Ahmed

The main goal of our project is to help paralyzed people, who can’t make any gesture or express their feelings, deal with other people and communicate with them using a virtual keyboard that is displayed on the monitor and use their eyes as a mouse to choose letters from that keyboard in order to display the chosen letters as a meaningful word that express the patient needs.

Helps limit the spread of the Coronavirus by using the apps without having to touch the mouse and keyboard.

• User will be able to write on the virtual keyboard using his eyes
• User will be able to control the mouse using his eyes.
• User will be able to convert text to speech.
• System provide word suggestion feature

In EyeTrackerV2.py

• Using open CV, dlib and numpy module to detect the image.
• Eye blanking detection.
• Gaz Detection.
• Every 10 frames we locate the landmark points of the right and left eye.
• Send the eyes landmarks to Eye blanking detection and gaz detection to get eye state for each frame.
• Find most frequent state for each 10 frames as Eye State.
• Send this state to controller

In WordPrediction.py

• We use machine learning algorithm here.
• We Import big.txt (huge chunk of text).
• Clean the text using regular expression.
• Divide the text into inputs and outputs.
• We use one hot encoding to make the training easier.
• Now we move to building the model using embedding layer, LSTM layer and dense layers and train it for 500 epoch.
• take text input from the controller and we return the top 5 prediction from our model.

In Threads.py

we distributed every main function into different threads so that they can work in parallel

In Controller.py

• here we Design VK
• connect VK buttons to keyboard keys
• connect curser tracker
• connect with eye tracker
• control VK
• connect to text to speech
• connect to word prediction
• connect to mouse
• control Mouse Tracker