Update 1.7 readme (#239)

Author: Pwhsky

README.md

@@ -6,16 +6,16 @@
 <p align="center">
   <a href="/LICENSE" alt="licence"><img src="https://img.shields.io/github/license/softmatterlab/DeepTrack-2.0"></a>
   <a href="https://badge.fury.io/py/deeptrack"><img src="https://badge.fury.io/py/deeptrack.svg" alt="PyPI version"></a>
-  <a href="https://softmatterlab.github.io/DeepTrack2/deeptrack.html"><img src="https://img.shields.io/badge/docs-passing-green" alt="PyPI version"></a>
+  <a href="https://deeptrackai.github.io/DeepTrack2"><img src="https://img.shields.io/badge/docs-passing-green" alt="PyPI version"></a>
   <a href="https://badge.fury.io/py/deeptrack"><img src="https://img.shields.io/badge/python-3.6%20%7C%203.7%20%7C%203.8%20%7C%203.9%20%7C%203.10-blue" alt="Python version"></a>
   <a href="https://doi.org/10.1063/5.0034891" alt="DOI">
     <img src="https://img.shields.io/badge/DOI-10.1063%2F5.0034891-blue">
   </a>
 </p>
 <p align="center">
   <a href="#installation">Installation</a> •
-  <a href="#using-deeptrack">Examples</a> •
-  <a href="#learning-deeptrack-21">Basics</a> •
+  <a href="#examples-of-applications-using-deeptrack">Examples</a> •
+  <a href="#getting-started-guides">Basics</a> •
   <a href="#cite-us">Cite us</a> •
   <a href="/LICENSE">License</a> 
 </p>
@@ -95,7 +95,7 @@ We have two separate series of notebooks which aims to teach you all you need to
 
 1. <a href="https://colab.research.google.com/github/softmatterlab/DeepTrack-2.0/blob/master/examples/get-started/01.%20deeptrack_introduction_tutorial.ipynb"> <img src="https://colab.research.google.com/assets/colab-badge.svg"> deeptrack_introduction_tutorial </a>  gives an overview of how to use DeepTrack 2.1.
 2. <a href="https://colab.research.google.com/github/softmatterlab/DeepTrack-2.0/blob/master/examples/tutorials/tracking_particle_cnn_tutorial.ipynb"> <img src="https://colab.research.google.com/assets/colab-badge.svg"> tracking_particle_cnn_tutorial </a> demonstrates how to track a point particle with a convolutional neural network (CNN).
-3. <a href="https://colab.research.google.com/github/softmatterlab/DeepTrack-2.0/blob/master/examples/tutorial/tracking_multiple_particles_unet_tutorial.ipynb"> <img src="https://colab.research.google.com/assets/colab-badge.svg"> tracking_particle_cnn_tutorial </a> demonstrates how to track multiple particles using a U-net.
+3. <a href="https://colab.research.google.com/github/softmatterlab/DeepTrack-2.0/blob/master/examples/tutorials/tracking_multiple_particles_unet_tutorial.ipynb"> <img src="https://colab.research.google.com/assets/colab-badge.svg"> tracking_particle_unet_tutorial </a> demonstrates how to track multiple particles using a U-net.
 4. <a href="https://colab.research.google.com/github/softmatterlab/DeepTrack-2.0/blob/master/examples/tutorials/characterizing_aberrations_tutorial.ipynb"> <img src="https://colab.research.google.com/assets/colab-badge.svg"> characterizing_aberrations_tutorial </a> demonstrates how to add and characterize aberrations of an optical device. 
 5. <a href="https://colab.research.google.com/github/softmatterlab/DeepTrack-2.0/blob/master/examples/tutorials/distinguishing_particles_in_brightfield_tutorial.ipynb"> <img src="https://colab.research.google.com/assets/colab-badge.svg"> distinguishing_particles_in_brightfield_tutorial </a> demonstrates how to use a U-net to track and distinguish particles of different sizes in brightfield microscopy. 
 6. <a href="https://colab.research.google.com/github/softmatterlab/DeepTrack-2.0/blob/master/examples/tutorials/analyzing_video_tutorial.ipynb"> <img src="https://colab.research.google.com/assets/colab-badge.svg"> analyzing_video_tutorial </a> demonstrates how to create videos and how to train a neural network to analyze them.
@@ -123,10 +123,10 @@ Additionally, we have seven more case studies which are less documented, but giv
 
 We also have examples that are specific for certain models. This includes 
 - [*LodeSTAR*](examples/LodeSTAR) for label-free particle tracking.
-- [*MAGIK*](deeptrack/models/gnns/) for graph-based particle linking and trace characterization.
+- [*MAGIK*](examples/MAGIK) for graph-based particle linking and trace characterization.
 
 ## Documentation
-The detailed documentation of DeepTrack 2.1 is available at the following link: https://softmatterlab.github.io/DeepTrack2/deeptrack.html
+The detailed documentation of DeepTrack 2.1 is available at the following link: https://deeptrackai.github.io/DeepTrack2
 
 ## Video Tutorials