Feedback ideas based on your feedback just now :)

[AlexEMG]

Thanks to all the feedback!

Already beforehand share:

• [x] What minimal specs do you need for a computer if you want to use DLC (efficiently)?
• [x] What limitations does COLAB have?
• [x] Do you want to use the GUI / COLAB?
• [x] already install DLC, read rel. papers
• [x] share what you're interested in multi-animal / DLC live / ... / clustering / action segmentation / kinematics / neural data ..

Day 2 feedback:

• [x] How to pick the most representative frames?
• [x] What parameters are relevant for what?
• [x] Can we train models for students over night (for students without GPU access)? --> mostly COLAB should be ideal?

Day 3 feedback:

• [x] how to measure speed / benchmark runtime ?
• [x] include further reading recommendations and refs in lecture page

Specific formatting feedback:

• [x] #23
• [x] one can link notebooks in a Jupyter book: https://jupyterbook.org/en/stable/content/executable/index.html --> (oner relevant notebook is: https://github.com/DeepLabCut/DeepLabCut/blob/master/examples/COLAB/COLAB_YOURDATA_TrainNetwork_VideoAnalysis.ipynb)
• [x] also link to relevant time intervals of video tutorials for GUI

General problem solving:

• [x] What have people struggled with? --> with solutions! (also link to the [DeepLabCut Forum(https://forum.image.sc/t/behavior-and-deeplabcut/23710) and Forum solutions). --> @KonradDanielewski
• [x] Start FAQ section --> @KonradDanielewski
• [x] Glossary of terms --> make section in resources @KonradDanielewski
• [x] Link for prerequisites --> make section in resources @KonradDanielewski

Please add more aspects that I forgot?

[sfmig]

Some bits that were also mentioned that may be relevant:

• adding at the end of each day take-home message and things you should have ready for the next day
• Python refresher --> add to resources? I like this one but it does assume some programming knowledge

[sfmig]

ok the first item is fixed by #22

Some bits that were also mentioned that may be relevant:

• adding at the end of each day take-home message and things you should have ready for the next day
• Python refresher --> add to resources? I like this one but it does assume some programming knowledge

[KonradDanielewski]

I think a video reencoding guide should be linked (https://deeplabcut.github.io/DeepLabCut/docs/recipes/io.html#tips-on-video-re-encoding-and-preprocessing) under general problem solving I guess, as part of common struggles. Since people will probably move video between places/change computers/download from cloud storage which sometimes results in video/single frame corruption. Just so they know it happens and is nothing serious and easy to fix

[KonradDanielewski]

@AlexEMG A question about the prerequisites. For DLC I guess we can point straight to the installation and installation tips as it covers everything that's needed for all platforms. What about other packages we will be using?

[AlexEMG]

I think the other packages have less or equal requirements, so we're fine :)

[KonradDanielewski]

also link to relevant time intervals of video tutorials for GUI

Link for prerequisites --> make section in resources @KonradDanielewski

Addressed by #35