Merge pull request #4 from MMathisLab/master

WIP course outline ...

Author: AlexEMG

README.md

@@ -6,8 +6,10 @@
 
 In **2020** we will host 2 workshops and 2 hackathons, one each at Harvard  and one each at EPFL. See [here for details](http://www.mousemotorlab.org/workshops). We will also be present at various other summer schools (TBA).
 
+**NEW: due to COVID-19, we are working on a virtual [self-paced spring/summer course](/summercourse_2020.md)**
 
-# DeepLabCut January 2020 Workshop Materials:
+
+# DeepLabCut 2020 Workshop Materials:
 
 Notice that details on installation, usage and examples can be found on the standard repository: https://github.com/AlexEMG/DeepLabCut
 
@@ -37,7 +39,7 @@ You can also use Google Colaboratory to run the demo data (without any installat
 Notice that more demos can be found in the examples folder of the [DeepLabCut github repo](https://github.com/AlexEMG/DeepLabCut/tree/master/examples).
 
 # Past and present workshop schedule
-- March 5-6, 2020: First DLC Hackathon: focus on hardware integration!
+- March 5-6, 2020: First DLC Hackathon: focus on hardware integration. Many exciting developments will appear -- Stay tuned!
 - Jan 16-17, 2020: Second Annual Workshop at the Rowland Institute at Harvard!
 - July 2019: [Neural Data Science Course at Cold Spring Harbor Laboratory](https://meetings.cshl.edu/courses.aspx?course=c-neudata&year=19)
 - June 2019: Marine Biological Laboratory, Woods Hole, MA as part of [The Neural Systems and Behavior Course in Woods Hole](https://www.mbl.edu/nsb/). The ribbon fin tracking below is from that course. See http://www.mousemotorlab.org/deeplabcutdetails for more details.

summer_course2020.md

@@ -0,0 +1,78 @@
+## Got Behavior? Get Poses ...  <img src="https://images.squarespace-cdn.com/content/v1/57f6d51c9f74566f55ecf271/1572296495650-Y4ZTJ2XP2Z9XF1AD74VW/ke17ZwdGBToddI8pDm48kMulEJPOrz9Y8HeI7oJuXxR7gQa3H78H3Y0txjaiv_0fDoOvxcdMmMKkDsyUqMSsMWxHk725yiiHCCLfrh8O1z5QPOohDIaIeljMHgDF5CVlOqpeNLcJ80NK65_fV7S1UZiU3J6AN9rgO1lHw9nGbkYQrCLTag1XBHRgOrY8YAdXW07ycm2Trb21kYhaLJjddA/DLC_logo_blk-01.png?format=1000w" width="350" title="DLC-live" alt="DLC LIVE!" align="right" vspace = "50">
+
+This document is a **WIP** outline of resources for an informal "spring/summer course" for those wanting to learn to use DeepLabCut while responsibilty isolating due to COVID-19.
+
+www.deeplabcut.org 
+
+We suggest student self organize into groups to work through this together. Perhaps find each other on Gitter or Twitter:
+[![Gitter](https://badges.gitter.im/DeepLabCut/community.svg)](https://gitter.im/DeepLabCut/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
+[![Twitter Follow](https://img.shields.io/twitter/follow/DeepLabCut.svg?label=DeepLabCut&style=social)](https://twitter.com/DeepLabCut)
+
+## Quick Start:
+
+You need: Anaconda for python3 and DeepLabCut installed (CPU version)
+- you should have a [CPU version of DeepLabCut installed on your laptop](https://github.com/AlexEMG/DeepLabCut/blob/master/conda-environments/README.md). We will assume you don't all have GPUs at home, so we will 
+utilize cloud-computing resources for those steps. 
+
+## Outline:
+
+### **The basics:**
+
+- Using the terminal / cmd [Video Tutorial!](https://www.youtube.com/watch?v=5XgBd6rjuDQ)
+
+- Can I DEMO DEEPLABCUT (DLC) quickly? 
+    - Yes: [you can click through this DEMO notebook](https://colab.research.google.com/github/AlexEMG/DeepLabCut/blob/master/examples/COLAB_DEMO_mouse_openfield.ipynb)
+    - AND follow along with me: [Video Tutorial!](https://www.youtube.com/watch?v=DRT-Cq2vdWs)
+- How do you know DLC is installed properly? (how to use test scripts!) ##TODO
+
+- There are a lot os docs... where to begin: [Video Tutorial!](https://www.youtube.com/watch?v=A9qZidI7tL8) 
+
+### **Module 1: getting started on your own data**
+
+What you need: any videos where you can see the animals/objects, etc. 
+You can use our demo videos, grab some from the internet, or use whatever older data you have. Any camera, color/monchrome, etc will work.
+Find diverse videos, and label what you want to track well :) 
+    
+   - **Slides:** [Overview of starting new projects](https://github.com/DeepLabCut/DeepLabCut-Workshop-Materials/blob/master/part1-labeling.pdf)
+   - **READ ME PLEASE:** [DeepLabCut, the science](rdcu.be/4Rep)
+   - **READ ME PLEASE:** [DeepLabCut, the user guide](https://rdcu.be/bHpHN)
+   - **WATCH:** Video tutorial 1: [using the Project Manager GUI](https://www.youtube.com/watch?v=KcXogR-p5Ak)
+     - Please go from project creation (use >1 video!) to labeling your data, and then check the labels!
+   - **WATCH:** Video tutorial 2: [using ipython/pythonw (more functions!)](https://www.youtube.com/watch?v=7xwOhUcIGio)
+      - coming soon, multi-animal DLC: [labeling preview](https://www.youtube.com/watch?v=_qbEqNKApsI)
+      - Please go from project creation (use >1 video!) to labeling your data, and then check the labels!
+      
+
+### **Module 2: Neural Networks**
+ 
+   - **Slides:** [Overview of creating training and test data, and training networks](https://github.com/DeepLabCut/DeepLabCut-Workshop-Materials/blob/master/part2-network.pdf)
+   - **READ ME PLEASE:** [What are convolutional neural networks?](https://towardsdatascience.com/a-comprehensive-guide-to-convolutional-neural-networks-the-eli5-way-3bd2b1164a53) 
+   
+  Before you create a training/test set, please read/watch:
+   - **More information:** [Which types neural networks are available, and what should I use?](https://github.com/AlexEMG/DeepLabCut/wiki/What-neural-network-should-I-use%3F)
+   - **WATCH:** Video tutorial 1: [How to test different networks in a controlled way](https://www.youtube.com/watch?v=WXCVr6xAcCA)
+     - Now, decide what model(s) you want to test. 
+        - IF you want to train on your CPU, then run the step `create_training_dataset`, in the GUI etc. on your own computer. 
+        - IF you want to use GPUs on google colab, [**(1)** watch this FIRST/follow along here!](https://www.youtube.com/watch?v=qJGs8nxx80A) **(2)** move your whole project folder to Google Drive, and then [**use this notebook**](https://github.com/AlexEMG/DeepLabCut/blob/master/examples/COLAB_YOURDATA_TrainNetwork_VideoAnalysis.ipynb)
+   
+
+### **Module 3: Evalution of network performance**
+ 
+   - **Slides** [Evalute your network](https://github.com/DeepLabCut/DeepLabCut-Workshop-Materials/blob/master/part3-analysis.pdf)
+   - **WATCH:** [Evaluate the network in ipython](https://www.youtube.com/watch?v=bgfnz1wtlpo)
+      - why evaluation matters; how to benchmark; analyzing an video and using scoremaps, conf. readouts, etc 
+   
+### **Module 4: Scaling your analysis to many new videos**
+ 
+   - [Analyzing videos in batches, over many folders, setting up automated data processing](https://github.com/DeepLabCut/DLCutils/tree/master/SCALE_YOUR_ANALYSIS) 
+   
+### **Module 5: Got Poses? Now what ...**
+ 
+   - [Helper code and packages for use on DLC outputs](https://github.com/DeepLabCut/DLCutils)
+
+
+**Other ideas:**
+
+- Docker, 3D DLC, ...
+
+*compiled and edited by Mackenzie Mathis*