Dyslexia Detection

Running the webapp

The app is developed in Python with frontend Developed in streamlit. To run the app in a vertual environment install the packages in requirements.txt using the command

pip install -r requirements.txt

Then run the app using

streamlit run app.py

Folder structure:

data:

contains the datasets used for Machine learning. The handwriting samples of the dyslexic childern are in dyslexic directory and the non-dyslexic samples are in non_dyslexic directory.

The data.csv has the extracted features of all the images in the above directories. the features are as follows:

• Spelling accuracy
• Gramatical accuracy
• Percentage of corrections
• Phonetic accuraccy (%)
• Presence of dyslexia

the school_symptoms.txt has the symptoms of the disorder documented.

images:

This folder contains the output images from visualization of the extracted features from the images which explains the accuracy of the classifier on the data.

model_training:

This folder contains the training and evaluation of various machine learning models on the extracted data.

app.py:

this file is the main file of the web application. This file has the logic for extracting all the required features from the uploaded image and making a predicton using the pretrained decision tree model.