Hand Gesture Recognition Using Keras
- Artificial Intelligence
- Computer Vision
- Project length: 4h 09m
Ever thought of creating your own hand gesture recognition system? This project will teach you how to do so. Not only this, but we will also be learning about different data augmentation techniques.
This tutorial will cover all the details (resources, tools, languages etc) that are necessary to create a Hand Gesture Recognition system. You will be guided through all the steps and concepts, starting from the basic ones like data augmentation to the more advanced topics related to the development.
What are the requirements?
- Python basics
- TensorFlow-Keras basics (not mandatory as it will be covered in lesson too)
- Basic neural network concepts
- And the most important is: a desire to learn
What is the target audience?
- Learners who want to enhance their knowledge
- This project will help the students who are doing their final projects.
Session 1: Data Augmentation
- Session 1.1: Resize and grayscale images in different folders
- Session 1.2: Rotation and Translation
- Session 1.3: Affine and perspective transformation
- Session 1.4: Adding noise and alter lights
- Session 1.6: Generate Shadows
- Session 1.5: Generate multiple images
- Session 1.7: Add snow and rain
Session 2: Hand Gesture Recognition
- Session 2.1: Create Data (trick)
- Session 2.2: Hand Gesture Recognition: Build an outline of our hand gesture recognition.
- Session 2.3: Hand or not model
- Session 2.4: Making Hand Gesture Recognition model from scratch
- Session 2.5: Making Hand Gesture Recognition model using Pretrained model
- Session 2.6: Hand Gesture Recognition: Implement our models into our previously built hand gesture recognition outline. (Built in session 2.2)