microsoft/aiskillsforwindows

Contains samples for implementing Windows Skills by extending the preview base API and using exsting skill packages

This code repo is now deprecated and the project is unsupported

AI Skills for Windows

Summary

Implementing and integrating efficient AI and Computer Vision (CV) solutions is a hard task for developers. The industry is moving at a fast pace and the amount of custom-tailored solutions coming out makes it almost impossible for app developers to keep up easily. We preview a base framework to expose AI solutions called AI Skills for Windows as well as pre-built common solutions (i.e. detection, classification, segmentation, etc.) developed by Microsoft and partners.

The AI Skills for Windows framework is meant to standardize the way AI and CV is put to use within a Windows application (i.e.: UWP, Desktop Win32, .Net Core 3.0+) running on the edge. It aims to abstract away the complexity of AI techniques by simply defining the concept of skills which are modular pieces of code that process input(s) and produce output(s). The implementation that contains the complex details (i.e. pre and post processing of data, model inference, algorithm, transcoding, applying the right heuristics, etc.) is encapsulated by WinRT APIs that inherits the base class present in the Microsoft.AI.Skills.SkillInterface namespace, which leverages built-in Windows primitives which in-turn eases interop with built-in hardware acceleration leveraged by frameworks such as Windows ML. All AI Skills for Windows derivatives follow the same programatic paradigm and flow from a developer consumer standpoint: if you understand how to use one AI Skill for Windows, you understand how to use them all. (See key AI Skills API concepts)

While this release focuses on vision-oriented scenarios and primitives, this API is meant to accommodate any kind of input and output variable and a wide range of scenarios (Vision, Audio, Text, etc.). Any developer can extend this API set and expose their own AI skills. See skills released by Intel

If you are looking for the earlier preview release samples and documentation, we archived them in a branch here: Preview branch

Code samples for using AI skills for Windows published by Microsoft on nuget.org

Object Detector

	Detecting and classifying objects in images

Object Tracker

	Tracking objects in videos

Skeletal Detector

	Estimating poses of people in images

Concept Tagger

	Obtaining classification scores of concepts in images

Image Scanning

	A set of AI skills to achieve content scanning scenarios such as the ones featured in OfficeLens
CurvedEdgesDetector	Seeks within an image the pixels that constitute the curved edges composing the contour of a given quad and returns their coordinates.
ImageCleaner	Cleans and enhances an image given a specified preset.
ImageRectifier	Rectifies and crops an image to a rectangle plane given four UV coordinates.
LiveQuadDetector and QuadDetector	Searches an image for quadrilateral shapes and returns the coordinates of their corners if found. The LiveQuadDetector is a stateful version of the QuadDetector that attempts to detect only 1 quadrangle and keeps track of the previous quad detected to be used as guide which optimizes tracking performance as new frames are bound over time. This is well suited for most scenarios operating over a stream of frames over time. QuadDetector can be set to detect more than 1 quadrangle and will search the whole frame everytime unless a previous quadrangle is provided.
QuadEdgesDetector	Searches an image for the horizontal and vertical lines defining a quadrilateral shape's contour and returns their coordinates.

For samples using AI skills published by Intel on nuget.org see the Intel-AI GitHub and this link for further details

AI Skill Name	Description
Background Blur	Segments out individuals while blurring the background image to highlight the individuals in the foreground.
Background Replacement	Segments out individuals while replacing the background with a user-selected image.
Face Detection	Detects face(s) and returns face bounding box(es) and other attributes, such as eyes, mouths, or nose tips.
Intruder Detection	Detects intruder by checking to see if an additional face or person is present in the video frame.
Person Detection	Detects person(s) and returns person bounding box(es).
Super Resolution	Converts a low-resolution image or video frame (320 x 240) to a high-resolution image (1280 x 960).
Super Resolution (WinML)	Converts a low-resolution image or video frame (640 x 360) to a high-resolution image (1280 x 720).

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