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OCI Vision is an AI service for performing deep-learning–based image analysis at scale. With prebuilt models available out of the box, developers can easily build image recognition and text recognition into their applications without machine learning (ML) expertise. For industry-specific use cases, developers can automatically train custom vision models with their own data. These models can be used to detect visual anomalies in manufacturing, organize digital media assets, and tag items in images to count products or shipments.
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# Table of Contents
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1. [Team Publications](#team-publications)
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2. [Useful Links](#useful-uinks)
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3. [LiveLabs and Workshops](#livelabs-and-workshops)
- [Live Labs - Premier League Video Analysis](https://apexapps.oracle.com/pls/apex/r/dbpm/livelabs/view-workshop?wid=3489&clear=RR,180&session=101189893786132)
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- Lab 1: Provision OCI Data Science
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- Lab 2: Provision Autonomous Data Warehouse
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- Lab 3: Recognize Players and Shirt Numbers (OCI Console)
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- Lab 4: Recognize Players and Shirt Numbers (Programmatically)
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- Lab 5: Translate Camera Coordinates to Football Pitch Coordinates
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- Lab 6: Connecting to Autonomous Data Warehouse
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- Lab 7: Processing the entire video
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## Reusable Assets Overview
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[OCI image classification using data labeling and vision service](https://github.com/carlgira/oci-image-classification)
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[OCI object detection using data labeling and vision service](https://github.com/carlgira/oci-object-detection)
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## Useful Links
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- [Oracle AI Vision on oracle.com](https://www.oracle.com/uk/artificial-intelligence/vision/)
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- [Oracle AI Vision documentation](https://docs.oracle.com/en-us/iaas/vision/vision/using/home.htm)
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# License
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Copyright (c) 2023 Oracle and/or its affiliates.
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Licensed under the Universal Permissive License (UPL), Version 1.0.
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See [LICENSE](https://github.com/oracle-devrel/technology-engineering/blob/folder-structure/LICENSE) for more details.
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