updated Readme.md

Author: JensBlack

Readme.md

@@ -9,9 +9,10 @@
 [![License: GPL v3](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)
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-DeepLabStream is a python based multi-purpose tool that enables the realtime tracking of animals and manipulation of experiments.
-Our toolbox is adapted from the previously published [DeepLabCut](https://github.com/AlexEMG/DeepLabCut) ([Mathis et al., 2018](https://www.nature.com/articles/s41593-018-0209-y)) and expands on its core capabilities.
-DeepLabStreams core feature is the real-time analysis using any type of camera-based video stream (incl. multiple streams).  Building onto that, we designed a full experimental closed-loop toolkit. It enables running experimental protocols that are dependent on a constant stream of bodypart positions and feedback activation of several input/output devices. It's capabilities range from simple region of interest (ROI) based triggers to headdirection or behavior dependent stimulation.
+DeepLabStream is a python based multi-purpose tool that enables the realtime tracking and manipulation of animals during ongoing experiments.
+Our toolbox was orginally adapted from the previously published [DeepLabCut](https://github.com/AlexEMG/DeepLabCut) ([Mathis et al., 2018](https://www.nature.com/articles/s41593-018-0209-y)) and expanded on its core capabilities, but is now able to utilize a variety of different network architectures for online pose estimation
+ ([DLC + maDLC](https://github.com/AlexEMG/DeepLabCut), [DLC-Live](https://github.com/DeepLabCut/DeepLabCut-live), [DeepPosekit's](https://github.com/jgraving/DeepPoseKit) StackedDenseNet, StackedHourGlass and [LEAP](https://github.com/murthylab/sleap)).
+DeepLabStreams core feature is the utilization of real-time tracking to orchestrate closed-loop experiments. This can be achieved using any type of camera-based video stream (incl. multiple streams).  It enables running experimental protocols that are dependent on a constant stream of bodypart positions and feedback activation of several input/output devices. It's capabilities range from simple region of interest (ROI) based triggers to headdirection or behavior dependent stimulation.
 
 ![DLS_Stim](docs/DLSSTim_example.gif)
 
@@ -27,7 +28,7 @@ If you have feature requests or questions regarding the design of experiments jo
 
 We are constantly working to update and increase the capabilities of DLStream. 
 We welcome all feedback and input from your side.
-ALso, do not hesitate to contact us for collaborations.
+Also, do not hesitate to contact us for collaborations.
 
  ### 1. [Installation & Testing](https://github.com/SchwarzNeuroconLab/DeepLabStream/wiki/Installation-&-Testing)