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Sign Language Classification

🏆 Accuracy: %93.54

Overview

This project focuses on classifying sign language images representing the numbers 0 and 1. The model achieves an impressive accuracy rate of 93.54%. This project has applications in sign language recognition and communication.

Dataset

The dataset used for this project contains images of hand signs for the numbers 0 and 1 in sign language. It includes two categories, one for each number. Data Link: Kaggle Link**

Project Structure

The project is organized into the following sections:

  1. Library and Input Files: In this section, we import the necessary Python libraries and load the dataset.

  2. Data Loading and Visualization: We load the sign language dataset and provide visualizations of the data.

  3. Data Preprocessing: The dataset is preprocessed and organized for model training.

  4. Train-Test Split: We split the data into training and testing sets for model evaluation.

  5. Flatten Operation: Images are flattened to prepare them for training.

  6. Transpose Operation: Data is transposed to match the required dimensions.

  7. Initialize Weights and Bias: We initialize the weights and bias for logistic regression.

  8. Sigmoid Function: The sigmoid function is defined, which is a crucial part of logistic regression.

  9. Forward-Backward Propagation: Forward and backward propagation steps are explained for logistic regression.

  10. Updating Parameters: The model parameters, including weights and bias, are updated using the gradient descent algorithm.

  11. Prediction: We make predictions using the trained model.

  12. Logistic Regression Algorithm: The logistic regression algorithm is executed, and results are displayed.

Requirements

To run the project, make sure you have the following Python libraries installed:

  • NumPy
  • matplotlib
  • pandas
  • scikit-learn

You can install these libraries using pip:

pip install numpy
pip install matplotlib
pip install pandas
pip install scikit-learn

Getting Started

Installation

  1. Clone the project repository:
git clone [https://github.com/Prometheussx/Sign-Language-Classification-Tutorial]
cd Sign-Language-Classification
  1. Ensure you have Python and the required libraries installed.

Data Preparation

  1. Download the sign language dataset containing images of the numbers 0 and 1 in sign language.

  2. Follow the code in the "Data Loading and Visualization" section to load and visualize the dataset.

  3. Data Link: Kaggle Link

Usage

Training the Model

logistic_regression(x_train, y_train, x_test, y_test,learning_rate=0.01 ,num_iterations = 150)

Evaluation

The model's performance is evaluated with metrics such as accuracy, and a sample image with the predicted number is displayed.

image

image

Results

The project achieves an accuracy of 93.54% in classifying sign language images of numbers 0 and 1. You can monitor the training progress and results by running the provided code.

image

Author

Feel free to reach out if you have any questions or need further information about the project.