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IBM PowerAI developer portal

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IBM PowerAI Vision Version 1.1.1

Available now

About PowerAI Vision

PowerAI Vision an help provide robust end-to-end workflow support for deep learning models related to computer vision. This enterprise-grade software provides a complete ecosystem to label raw data sets for training, creating, and deploying deep learning-based models. PowerAI Vision is designed to empower subject matter experts with no skills in deep learning technologies to train models for AI applications. It can help train highly accurate models to classify images and detect objects in images and videos.

PowerAI Vision is built on open source frameworks for modeling and managing containers to deliver a highly available framework, providing application lifecycle support, centralized management and monitoring, and support from IBM.

What’s new is PowerAI Vision Version 1.1.1

PowerAI V1.1.1 builds upon previous releases and includes the following updates and features:

  • Data augmentation: After deploying a model, you can improve the model by using data augmentation to add modified images to the data set, then retraining the model. Data augmentation is the use of filters, such as blur and rotate, to create new versions of existing images. When you use data augmentation, a new data set is created that contains all of the existing images, plus the newly generated images.
  • Optimize training for speed: When training a data set, you can optimize the training for accuracy (default), or for speed. When training for speed, PowerAI Vision uses you only look once (YOLO) V2.
  • Inference only containers: With a PowerAI Vision Inference server, you can quickly and easily deploy multiple trained models to a single server. These models are portable and can be used by many users and on different systems. This allows you to make trained models available to others, such as customers or collaborators.
  • User account creation and management: Use the powerai_vision_users.sh or powerai-vision-usermgt commands to work with users.
  • User data isolation: Users can only see and act on objects (data sets, files, trained models, and deployed models) that he or she owns. Objects are owned by the user who created them.

Code patterns

Check out these real world examples and tutorials that highlight PowerAI Vision in action.

Tell us what you think

Your feedback is important to us. After you download PowerAI Vision and give it a try, please tell us about your experience by taking this short survey.

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