MLECO-3100: Added summary document of use-cases
Update for use-case API and CMSIS pack.
Change-Id: Ic730a80fa43ba2a6e3eaa05333b61d3e1677b04e
Signed-off-by: Kshitij Sisodia <kshitij.sisodia@arm.com>
diff --git a/Readme.md b/Readme.md
index 69864c2..5f731b3 100644
--- a/Readme.md
+++ b/Readme.md
@@ -21,7 +21,7 @@
[Arm Virtual Hardware](https://www.arm.com/products/development-tools/simulation/virtual-hardware) (AVH) and [run the Fixed Virtual Platform
in the cloud](./docs/sections/arm_virtual_hardware.md).
> **NOTE**: While Arm® Corstone™-300 is available as an [Ecosystem FVP](https://developer.arm.com/tools-and-software/open-source-software/arm-platforms-software/arm-ecosystem-fvps)
- > and AVH, Arm® Corstone™-310 is available (for both Arm® Ethos™-U55 and Ethos™-U55 NPUs) only as AVH implementations.
+ > and AVH, Arm® Corstone™-310 is available (for both Arm® Ethos™-U55 and Ethos™-U65 NPUs) only as AVH implementations.
## Overview of the evaluation kit
diff --git a/scripts/cmake/cmsis-pack-gen/use-case-api.yml b/scripts/cmake/cmsis-pack-gen/use-case-api.yml
index 230e29a..3d81433 100644
--- a/scripts/cmake/cmsis-pack-gen/use-case-api.yml
+++ b/scripts/cmake/cmsis-pack-gen/use-case-api.yml
@@ -42,7 +42,7 @@
description: "ML sample use case APIs derived from ml-embedded-eval-kit"
vendor: "ARM"
license: "LICENSE_APACHE_2.0.txt"
- url: "https://git.mlplatform.org/ml/ethos-u/ml-embedded-evaluation-kit.git/plain/resources/cmsis-packs/"
+ url: "https://git.mlplatform.org/ml/ethos-u/ml-embedded-evaluation-kit.git/plain/source/application/api/use_case/readme.md"
requirements:
packages:
diff --git a/source/application/api/use_case/readme.md b/source/application/api/use_case/readme.md
index f7eb0d1..419dee0 100644
--- a/source/application/api/use_case/readme.md
+++ b/source/application/api/use_case/readme.md
@@ -1,11 +1,70 @@
-## Use case APIs
+- [Use case APIs](#use-case-apis)
+ - [Anomaly detection](#anomaly-detection)
+ - [Automatic speech recognition](#automatic-speech-recognition)
+ - [Image classification](#image-classification)
+ - [Inference runner](#inference-runner)
+ - [Keyword spotting](#keyword-spotting)
+ - [Noise reduction](#noise-reduction)
+ - [Object detection](#object-detection)
+ - [Visual wake word](#visual-wake-word)
+ - [Useful links](#useful-links)
-The directories in here are individual CMake projects to generate use case API static libraries. These libraries are
-intended to be used by external projects that only want access to the ready-to-use ML use case pipelines implemented in this repository.
-This can be as CMake projects, but also in the form of CMSIS-packs. These libraries do not depend on the HAL layer and
-are platform-agnostic to allow for easy portability.
+# Use case APIs
+
+The directories in here are individual CMake projects to generate use case API static libraries.
+These libraries are intended to be used by external projects that only want access to the
+ready-to-use ML use case pipelines implemented in this repository. This can be as CMake projects,
+but also in the form of CMSIS-packs.
+
+## Anomaly detection
+
+This use case takes an audio clip of a machine at work as input and indicates whether there is an
+anomaly to suggest that the machine is not performing normally and might need attention.
+
+## Automatic speech recognition
+
+This use case takes in an audio clip as an input and returns a transcript of what was being said
+in text format.
+
+## Image classification
+
+This use case takes an image as input and classifies it into one of the categories the neural
+network model supports. For example, the default Mobilenet V2 based model will be able to
+classify the images into 1000 different classes.
+
+## Inference runner
+
+The inference runner is a generic use case which can run any model. It has a bigger memory
+footprint because it includes support for all possible ML operators. This use case is useful for
+checking if a given neural network model can be run with TensorFlow Lite Micro. The application
+can also be used to get performance metrics for executing the ML workload for a given model.
+
+## Keyword spotting
+
+This use case takes an audio clip as an input, divides it into smaller sub-clips, and indicates which
+keyword has been spotted for each sub-clip.
+
+## Noise reduction
+
+This use case removes noise from an audio clip. Instead of replicating a "noisy audio in" and
+"clean audio out" problem, a simpler version is defined. Given an audio clip, the use case produces
+gains to be applied to the input audio to reduce the noise.
+
+## Object detection
+
+This use case takes image data as input and performs object detection on them. The default model is
+set up to detect faces of size 20x20 and above. The output represents the coordinates of the
+bounding boxes that encapsulate the faces.
+
+## Visual wake word
+
+This use case takes images as input and determines, with a certain probability, whether the image
+contains a person.
+
## Useful links
-* [Repository Structure](../../../../docs/documentation.md#repository-structure)
-* [Reusable Software](../../../../Readme.md#reusable-software).
+* [Project ReadMe](../../../../Readme.md)
+* [Reusable Software](../../../../Readme.md#reusable-software)
+
+