Python and Deep Learning with OpenCV 4 Training Course
OpenCV is a library of programming functions for deciphering images with computer algorithms. OpenCV 4 is the latest OpenCV release and it provides optimized modularity, updated algorithms, and more. With OpenCV 4 and Python, users will be able to view, load, and classify images and videos for advanced image recognition.
This instructor-led, live training (online or onsite) is aimed at software engineers who wish to program in Python with OpenCV 4 for deep learning.
By the end of this training, participants will be able to:
- View, load, and classify images and videos using OpenCV 4.
- Implement deep learning in OpenCV 4 with TensorFlow and Keras.
- Run deep learning models and generate impactful reports from images and videos.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Course Outline
Introduction
What is AI
- Computational Psychology
- Computational Philosophy
Deep Learning
- Artificial neural networks
- Deep learning vs. machine learning
Preparing the Development Environment
- Installing and configuring OpenCV
OpenCV 4 Quickstart
- Viewing images
- Using color channels
- Viewing videos
Deep Learning Computer Vision
- Using the DNN module
- Working with with deep learning models
- Using SSDs
Neural Networks
- Using different training methods
- Measuring performance
Convolutional Neural Networks
- Training and designing CNNs
- Building a CNN in Keras
- Importing data
- Saving, loading, and displaying a model
Classifiers
- Building and training a classifier
- Splitting data
- Boosting accuracy of results and values
Summary and Conclusion
Requirements
- Basic programming experience
Audience
- Software Engineers
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