amendments to action rec (#559)

* action rec additions

* fix

Author: jiata

README.md

@@ -56,10 +56,10 @@ The following is a summary of commonly used Computer Vision scenarios that are c
 | [Detection](scenarios/detection) | Base | Object Detection is a technique that allows you to detect the bounding box of an object within an image. |
 | [Keypoints](scenarios/keypoints) | Base | Keypoint detection can be used to detect specific points on an object. A pre-trained model is provided to detect body joints for human pose estimation. |
 | [Segmentation](scenarios/segmentation) | Base | Image Segmentation assigns a category to each pixel in an image. |
-| [Action recognition](contrib/action_recognition) | Contrib | Action recognition to identify in video/webcam footage what actions are performed (e.g. "running", "opening a bottle") and at what respective start/end times.|
+| [Action recognition](scenarios/action_recognition) | Base | Action recognition to identify in video/webcam footage what actions are performed (e.g. "running", "opening a bottle") and at what respective start/end times.|
 | [Crowd counting](contrib/crowd_counting) | Contrib | Counting the number of people in low-crowd-density (e.g. less than 10 people) and high-crowd-density (e.g. thousands of people) scenarios.|
 
-We separate the supported CV scenarios into two locations: (i) **base**: code and notebooks within the "utils_cs" and "scenarios" folders which follow strict coding guidelines, are well tested and maintained; (ii) **contrib**: code and other assets within the "contrib" folder, mainly covering less common CV scenarios using bleeding edge state-of-the-art approaches. Code in "contrib" is not regularly tested or maintained.
+We separate the supported CV scenarios into two locations: (i) **base**: code and notebooks within the "utils_cv" and "scenarios" folders which follow strict coding guidelines, are well tested and maintained; (ii) **contrib**: code and other assets within the "contrib" folder, mainly covering less common CV scenarios using bleeding edge state-of-the-art approaches. Code in "contrib" is not regularly tested or maintained.
 
 ## Computer Vision on Azure
 

contrib/README.md

@@ -8,7 +8,6 @@ Each project should live in its own subdirectory ```/contrib/<project>``` and co
 ## Scenarios
 | Directory | Project description | Build status (optional) |
 |---|---|---|
-| [Action recognition](action_recognition) | Action recognition to identify in video/webcam footage what actions are performed (e.g. "running", "opening a bottle") and at what respective start/end times.| |
 | [Crowd counting](crowd_counting) | Counting the number of people in low-crowd-density (e.g. less than 10 people) and high-crowd-density (e.g. thousands of people) scenarios. | [![Build Status](https://dev.azure.com/team-sharat/crowd-counting/_apis/build/status/lixzhang.cnt?branchName=lixzhang%2Fsubmodule-rev3)](https://dev.azure.com/team-sharat/crowd-counting/_build/latest?definitionId=49&branchName=lixzhang%2Fsubmodule-rev3)|
 
 ## Tools