Žiga Vaupot's Blog

  Oracle LiveLabs is a one-stop shop for Oracle's tools and technology labs and workshops. I am very proud to announce that my first  Oracle LiveLabs  workshop  Classify X-Ray Images for Pneumonia using Analytics Cloud and Vision AI Services  has been approved and published. This workshop explains in all details how to prepare an image library for images that are used for training a machine learning model for image classification, for example x-ray images of normal and pneumonia infected lungs. Once images are organised in an image library, all images are labeled and based on this a vision machine learning is created. Finally, vision model is registered in Oracle Analytics where classification of a new x-ray image dataset is performed. For anyone interested, here is direct link to  Classify X-Ray Images for Pneumonia using Analytics Cloud and Vision AI Services  workshop.

I have been writing about OCI Vision services and integration between OCI Vision to Oracle Analytics in previous blog posts and how these services can integrate and be used with Oracle Analytics Cloud (OAC) .  In the meantime Oracle has released the Oracle Analytics January 2023 release, which comes with an option to integrate OAC with another OCI AI service , OCI language service (Language) . In this blog post I am focusing on the integration between OAC and Language . This means, I am not focusing on the training of a custom model (possible topic for one of the future blog posts), but I am using pre-trained model available within  Language . Assuming that model already exists, connecting OAC instance to  Language  has to follow the following steps: Language  requires storage to store temporary results. This is why, a staging bucket is created in Object Storage. In order to access  Language  and to access staging bucket  OAC  users require few policies that needs to be set

On November 3rd, I delivered my presentation OCI Vision and Oracle Analytics: Just like a Box of Chocolates at Analytics and Data Oracle User Community (AnDOUC)  TechCast : OCI Vision is a self-service AI Service, which applies computer vision to analyze image-based content. It allows developers easily integrate pre-trained models into their applications with APIs or custom training models to meet their specific use cases. In our example, I will explore how to use OCI Vision service to create a custom-built model to detect pneumonia infected lungs on a fresh dataset of X-ray images. In this example, I am using rather large dataset of X-ray images found on Kaggle.com. Oracle Analytics is then used as a front-end tool to use the model to classify new images for pneumonia. What to expect to see in this presentation? In the first place, we will demonstrate and explore the whole process from “plain” X-ray image to identifying pneumonia infected lungs using OCI services: Gathering and stori

After 5 years, I was attending HROUG’22   (Croatian Oracle User Group) as a presenter delivering my latest Just Like a Box of Chocolate presentation: OCI Vision is a self-service AI Service, available in Oracle Cloud Infrastructure (OCI), which Oracle defines as a service that “applies computer vision to analyse image-based content. Developers can easily integrate pretrained models into their applications with APIs or custom train models to meet their specific use cases. These models can be used to detect visual anomalies in manufacturing, extract text from documents to automate business workflows, and tag items in images to count products or shipments”. Basically, what Vision AI Service does is Image Classification, Object Detection and Document AI. In the first part, presentation focuses on how to prepare data for the training, by using Data Labelling, another OCI service, and how to run the model training itself using OCI Vision. In the second part of the presentation, we will focu