Series

Learning path: Getting started with PowerAI Vision

From computer vision basics to creating your own apps

By Mark Sturdevant
Updated July 12, 2019 | Published July 12, 2019

Level	Topic	Type
100	Introduction to computer vision	Article
101	Introduction to PowerAI Vision	Article
201	Build and deploy a PowerAI Vision model and use it in an iOS app	Tutorial
202	Locate and count items with object detection	Code pattern
203	Object tracking in video with OpenCV and Deep Learning	Code pattern
301	Validate computer vision deep learning models	Code pattern
302	Develop analytical dashboards for AI projects with PowerAI Vision	Code pattern

This learning path is designed for developers interested in quickly getting up to speed on what PowerAI Vision offers and how to use it. The learning path consists of step-by-step tutorials, deep-dive videos, and complete examples of working code. As you proceed through the learning path, you will learn about more advanced features as well as different use cases for PowerAI Vision.

To get started, click on a card below, or see the table above for a complete list of topics covered.

Intro to computer vision

Article

Introduction to computer vision

July 12, 2019

Learn about:

Image classification
Object detection
Object tracking in videos
Creating custom models
Using your model
Example use cases

Introduction to PowerAI Vision

Article

Introduction to PowerAI Vision

July 1, 2019

Learn about:

Creating a data set
Assigning categories for image classification
Labeling objects for object detection
Training a model
Testing the model
Using it in an app

Build and deploy a PowerAI Vision model and use it in an iOS app

Tutorial

Build and deploy a PowerAI Vision model

May 3, 2018

Learn about:

Creating a data set
Training a model for image classification
Deploying it to a web API
Integrating the API into an iOS app

Locate and count items with object detection

Code Pattern

Locate and count items with object detection

Feb 17, 2018

Learn about:

Creating a data set
Training a model for object detection
Deploying it to a web API
Testing the model with REST calls
Integrating object detection into a Node.js web app

Object tracking in video with OpenCV and deep learning

Code Pattern

Object tracking in video with OpenCV and Deep Learning

May 31, 2019

Learn about:

Using automatic labeling to create an object detection classifier from a video
Processing frames of a video using a Jupyter Notebook, OpenCV, and PowerAI Vision
Detecting objects in video frames with PowerAI Vision
Tracking objects from frame to frame with OpenCV
Counting objects in motion as they enter a region of interest
Annotating a video with bounding boxes, labels, and statistics

Validate computer vision deep learning models

Code Pattern

Validate computer vision deep learning models

June 14, 2019

Learn about:

Classifing images using an existing model and a Jupyter Notebook
Collecting statistics to evaluate a model
Visualizing model accuracy with a confusion matrix
Producing a variety of accuracy measure for model validation

Develop analytical dashboards for AI projects with PowerAI Vision

Code Pattern

Develop analytical dashboards for AI projects with PowerAI Vision

January 9, 2020

Learn about:

Uploading training images to PowerAI Vision
Training and deploying a model in PowerAI Vision
Uploading images to be processed through the dashboard
Viewing the processed images and graphs in the dashboard

Next: Introduction to computer vision

Image recognition with TensorFlow and Keras

Feb 19, 2019

Article

Refine your deep learning model

Feb 19, 2019

Series