**Sign Language ASL Alphanumeric Recognizer**
=============================================

**A real-time hand gesture recognition system for American Sign Language (ASL) alphanumeric characters using deep learning and computer vision.**

markdownCopy code# Sign Language ASL Recognizer

This project is an ASL (American Sign Language) Recognizer that utilizes computer vision techniques to recognize and classify hand gestures corresponding to different ASL signs.

\## Table of Contents

\- \[Installation\](#installation)

\- \[Usage\](#usage)

\- \[How It Works\](#how-it-works)

\- \[Requirements\](#requirements)

\- \[Known Issues\](#known-issues)

\- \[Contributing\](#contributing)

\- \[License\](#license)

\## Installation

1\. \*\*Clone the repository:\*\*

\`\`\`bash

git clone https://github.com/YourUsername/SignLangASL\_Recognizer.git

cd SignLangASL\_Recognizer

1.  Ensure you have Python installed. Install required dependencies by running:bashCopy codepip install -r requirements.txtIf you do not have a requirements.txt, here's an example of what it might contain:bashCopy codeopencv-pythonmediapipetensorflownumpy
    
2.  bashCopy codepip install mediapipe
    
3.  After installing the dependencies, you can run the recognition script:bashCopy codepython recognize.py
    

Usage
-----

Once you run the script, it will open your webcam to detect hand gestures in real-time. The system will analyze the hand's landmarks and attempt to classify the gesture into a known ASL sign.

### Key Features

*   Real-time hand gesture detection using MediaPipe.
    
*   Gesture recognition with TensorFlow/Keras.
    
*   Option to classify gestures with maximum accuracy and minimal latency.
    

How It Works
------------

The system leverages the following components:

*   **MediaPipe Hand Detector**: Detects hands and extracts landmark coordinates.
    
*   **Custom Gesture Classifier**: Built using a deep learning model (TensorFlow/Keras) to classify hand gestures into different ASL signs.
    

### Hand Detection

MediaPipe’s HandDetector is used to detect and track the hand landmarks. These landmarks are passed to the classifier for gesture recognition.

Requirements
------------

*   Python 3.7 or higher
    
*   OpenCV
    
*   MediaPipe
    
*   TensorFlow
    
*   NumPy
    

Known Issues
------------

### Error: TypeError: HandDetector.\_\_init\_\_() got an unexpected keyword argument 'maxTrackCon'

This error occurs if an incorrect version of MediaPipe or a modified version of the HandDetector class is used. Ensure that you're using the correct version of MediaPipe and refer to their official documentation for the correct arguments.

To resolve this issue:

*   bashCopy codepip show mediapipe
    
*   If the error persists, modify the recognize.py script and remove or correct the maxTrackCon argument in the HandDetector initialization.
    

For example:

Plain textANTLR4BashCC#CSSCoffeeScriptCMakeDartDjangoDockerEJSErlangGitGoGraphQLGroovyHTMLJavaJavaScriptJSONJSXKotlinLaTeXLessLuaMakefileMarkdownMATLABMarkupObjective-CPerlPHPPowerShell.propertiesProtocol BuffersPythonRRubySass (Sass)Sass (Scss)SchemeSQLShellSwiftSVGTSXTypeScriptWebAssemblyYAMLXML`   pythonCopy codeself.detector = HandDetector(maxHands=1)  # Remove 'maxTrackCon' if it's not supported   `

Contributing
------------

Feel free to fork the repository and submit pull requests if you wish to contribute to this project.

License
-------

This project is licensed under the MIT License.

Plain textANTLR4BashCC#CSSCoffeeScriptCMakeDartDjangoDockerEJSErlangGitGoGraphQLGroovyHTMLJavaJavaScriptJSONJSXKotlinLaTeXLessLuaMakefileMarkdownMATLABMarkupObjective-CPerlPHPPowerShell.propertiesProtocol BuffersPythonRRubySass (Sass)Sass (Scss)SchemeSQLShellSwiftSVGTSXTypeScriptWebAssemblyYAMLXML``   markdownCopy code  ### Notes:  - Replace `YourUsername` with your actual GitHub username.  - Ensure the `requirements.txt` reflects the actual dependencies your project uses.  - Make sure to test the project after removing the `maxTrackCon` argument, as outlined in the "Known Issues" section.   ``