From 060d664896bd3dae3c7244c39973571a5c91b2de Mon Sep 17 00:00:00 2001
From: Alex <95913221+Pwhsky@users.noreply.github.com>
Date: Fri, 13 Dec 2024 12:12:15 +0100
Subject: [PATCH] Update 1.7 readme
---
README.md | 12 ++++++------
1 file changed, 6 insertions(+), 6 deletions(-)
diff --git a/README.md b/README.md
index 4ad78ed10..8908cb7dd 100644
--- a/README.md
+++ b/README.md
@@ -6,7 +6,7 @@
-
+
@@ -14,8 +14,8 @@
Installation •
- Examples •
- Basics •
+ Examples •
+ Basics •
Cite us •
License
@@ -95,7 +95,7 @@ We have two separate series of notebooks which aims to teach you all you need to
1.
deeptrack_introduction_tutorial gives an overview of how to use DeepTrack 2.1.
2.
tracking_particle_cnn_tutorial demonstrates how to track a point particle with a convolutional neural network (CNN).
-3.
tracking_particle_cnn_tutorial demonstrates how to track multiple particles using a U-net.
+3.
tracking_particle_unet_tutorial demonstrates how to track multiple particles using a U-net.
4.
characterizing_aberrations_tutorial demonstrates how to add and characterize aberrations of an optical device.
5.
distinguishing_particles_in_brightfield_tutorial demonstrates how to use a U-net to track and distinguish particles of different sizes in brightfield microscopy.
6.
analyzing_video_tutorial 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