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diff --git a/docs/use_cases/object_detection.md b/docs/use_cases/object_detection.md index 8062325..1b74cf1 100644 --- a/docs/use_cases/object_detection.md +++ b/docs/use_cases/object_detection.md @@ -14,11 +14,13 @@ - [Running Object Detection](./object_detection.md#running-object-detection) ## Introduction - This document describes the process of setting up and running the Arm® *Ethos™-U* NPU Object Detection example. - -This use-case example solves the classical computer vision problem of Object Detection. The ML sample was developed -using the *YOLO Fastest* model that was trained on the *Wider* dataset. +Object Detection is a classical computer vision use case in which specific objects need to be identified and located +within a full frame. In this specific example the model was trained for face detection. The ML sample was developed +using the *YOLO Fastest* model. To adopt the model for low power / low memory systems the input images to the model +are monochrome images. The model was trained on the *Wider* dataset (after conversion from RGB to monochrome) +and on *Emza Visual-Sense* dataset [www.emza-vs.com](www.emza-vs.com). +The model makes detection faces in size of 20x20 pixels and above. Use-case code could be found in the following directory:[source/use_case/object_detection](../../source/use_case/object_detection). |