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Unsupervised Object Detection Using the Azure Cognitive Services on Spark

2,086 views · Published 11 October 2018 · 30:41 · Indexed 29 October 2026

Channel: Databricks · 2018 · Science & Technology

Talk by: Anand Raman and Mark Hamilton (Microsoft)

We present HTTP on Spark, a novel integration between Spark with the widely used Hypertext Transfer Protocol (HTTP). This library can be used to integrate any framework into the Spark ecosystem that is capable of communicating through HTTP. Furthermore, HTTP on Spark enables distributed and fault tolerant micro service architectures that commute with Spark’s dynamic allocation and Streaming capabilities. We build upon this work and release a library of idiomatic spark bindings for a wide array of Microsoft Cognitive Services. These bindings allow users to easily add *any* cognitive service as a part of their existing Spark and SparkML machine learning pipelines. Finally, we demonstrate how to use these services to create a large class of custom image classification and object detection systems that can learn without requiring human labeled training examples. We demonstrate the power of these new releases with an automated Snow Leopard Detection system.

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Unsupervised Object Detection Using the Azure Cognitive Services on Spark

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