Update Readme.md

Author: JensBlack

Readme.md

@@ -16,21 +16,25 @@ DeepLabStreams core feature is the real-time analysis using any type of camera-b
 
 ![DLS_Stim](docs/DLSSTim_example.gif)
 
-### Quick Reference:
+## Quick Reference:
+
+ ### Check out or wiki: [DLStream Wiki](https://github.com/SchwarzNeuroconLab/DeepLabStream/wiki)
 
  ### Read the preprint: [Schweihoff et al, 2019](https://doi.org/10.1101/2019.12.20.884478).
 
  ### 1. [Installation & Testing](https://github.com/SchwarzNeuroconLab/DeepLabStream/wiki/Installation-&-Testing)
 
- ### 2. [Introduction to experiments](https://github.com/SchwarzNeuroconLab/DeepLabStream/wiki/Introduction)
+ ### 2. [How to use DLStream GUI](https://github.com/SchwarzNeuroconLab/DeepLabStream/wiki/How-to-use-DLStream)
+ 
+ ### 3. [Introduction to experiments](https://github.com/SchwarzNeuroconLab/DeepLabStream/wiki/Introduction)
 
- ### 3. [Design your first experiment](https://github.com/SchwarzNeuroconLab/DeepLabStream/wiki/My-first-experiment)
+ ### 4. [Design your first experiment](https://github.com/SchwarzNeuroconLab/DeepLabStream/wiki/My-first-experiment)
 
- ### 4. [Adapting an existing experiment to your own needs](https://github.com/SchwarzNeuroconLab/DeepLabStream/wiki/Adapting-an-existing-experiment-to-your-own-needs)
+ ### 5. [Adapting an existing experiment to your own needs](https://github.com/SchwarzNeuroconLab/DeepLabStream/wiki/Adapting-an-existing-experiment-to-your-own-needs)
 
  #### Check out our [Out-of-the-Box](https://github.com/SchwarzNeuroconLab/DeepLabStream/wiki/Out-Of-The-Box:-What-Triggers-are-available%3F) section to get a good idea, what DLStream has in stock for your own experiments!
 
-### How does this work
+## How does this work
 
 DeepLabStream uses the camera's video stream to simultaneously record a raw (read as unmodified) video of the ongoing experiment,
 send frames one-by-one to the neuronal network for analysis, and use returned analysed data to plot and show a video stream for the experimenter to observe and control the experiment.
@@ -39,53 +43,6 @@ and to end, prolong or modify parts of experimental protocol.
 
 ![Flowchart](docs/flowchart2.png)
 
-## Usage
-
-### How to use DeepLabStream
-
-Just run 
-```
-cd DeepLabStream
-python app.py
-``` 
-
-You will see the main control panel of a GUI app.
-
-![Main](docs/screen_gui.png)
-
-To start working with DeepLabStream, press the `Start Stream` button. It will activate the camera manager and show you the current view from the connected cameras.
-
-![Stream](docs/screen_stream.png)
-
-After that you can `Start Analysis` to start DeepLabCut and receive a pose estimations for each frame, or, additionally, you can `Start Recording` to record a
-video of the current feed (visible in the stream window). You will see your current video timestamp (counted in frames) and FPS after you pressed the `Start Analysis` button.
-
-![Analisys](docs/screen_analysis.png)
-
-As you can see, we track three points that represent three body parts of the mouse - nose, neck and tail root.
-Every single frame where the animal was tracked is outputted to the dataframe, which would create a .csv file after the analysis is finished.
-
-After you finish with tracking and/or recording the video, you can stop either function by specifically pressing on corresponding "stop" button
-(so, `Stop Analysis` or `Stop Recording`) or you can stop the app and refresh all the timing at once, by pressing `Stop Streaming` button.
-
-#### Experiments
-
-DeepLabStream was build specifically for closed-loop experiments, so with a properly implemented experiment protocol, running experiments on this system is as easy as 
-pressing the `Start Experiment` button. Depending on your protocol and experimental goals, experiments could run and finish without any further engagement from the user.
-
-![Start](docs/screen_exp_start.png)
-
-In the provided `ExampleExperiment` two regions of interest (ROIs) are created inside an arena. The experiment is designed to count the number of times the mouse enters a ROI and trigger a corresponding visual stimulus on a screen.
-The high contrast stimuli (image files) are located within the `experiments/src` folder and specified within the `experiments.py` `ExampleExperiments` Class.
-
-![Experiment](docs/screen_exp.png)
-
-As a visual representation of this event, the border of the ROI will turn green.
-
-All experimental output will be stored to a .csv file for easy postprocessing.
-
-Look at the [Introduction to experiments](https://github.com/SchwarzNeuroconLab/DeepLabStream/wiki/Introduction) to get an idea how to design your own experiment in DeepLabStream or learn how to adapt one of the already published experiments at [Adapting an existing experiment](https://github.com/SchwarzNeuroconLab/DeepLabStream/wiki/Adapting-an-existing-experiment-to-your-own-needs).
-
 ### Known issues
 
 If you encounter any issues or errors, you can check out the wiki article ([Help there is an error!](https://github.com/SchwarzNeuroconLab/DeepLabStream/wiki/Help-there-is-an-error!)). If your issue is not listed yet, please refer to the issues and either submit a new issue or find a reported issue (which might be already solved) there. Thank you!
@@ -96,7 +53,9 @@ If you use this code or data please cite [Schweihoff et al, 2019](https://doi.or
 
 ## License
 This project is licensed under the GNU General Public License v3.0. Note that the software is provided "as is", without warranty of any kind, expressed or implied. 
+
 ## Authors
+
 Lead Researcher: Jens Schweihoff, [email protected]
 
 Lead Developer: Matvey Loshakov, [email protected]