First of all, thank you for the release. I am sure that it will help alot of people doing behaviour classification in open fields.
I have adapted the code to work on 8 features derived from 7 DLC markers on a top-down video.
Our original goal was to train a supervised classifier (grooming yes/no) on dimensionality reduced data. Now shifting strategy to adapt your code, a very crucial step will be to subjectively judge the action in each of the classes that the gmm and svm works with.
My questions are regarding the action_gif function to output small videos.
Is it possible to run the function on multiple subjects automatically, or do I need to parse the action_gif videos and group_labels for each subject separately?
Another thing. While testing the function on a single video, I got a warning from line 51 of action_gif.
grp_1 = grp_fill(1:fps/20:end);
My fps is 30, so here the grp_1 is downsampled in a ambigous way... Any thoughts on this?
Again, thanks alot for the upload.
Sincerely, Peter
First of all, thank you for the release. I am sure that it will help alot of people doing behaviour classification in open fields.
I have adapted the code to work on 8 features derived from 7 DLC markers on a top-down video.
Our original goal was to train a supervised classifier (grooming yes/no) on dimensionality reduced data. Now shifting strategy to adapt your code, a very crucial step will be to subjectively judge the action in each of the classes that the gmm and svm works with.
My questions are regarding the action_gif function to output small videos.
Is it possible to run the function on multiple subjects automatically, or do I need to parse the action_gif videos and group_labels for each subject separately?
Another thing. While testing the function on a single video, I got a warning from line 51 of action_gif.
grp_1 = grp_fill(1:fps/20:end);My fps is 30, so here the grp_1 is downsampled in a ambigous way... Any thoughts on this?
Again, thanks alot for the upload.
Sincerely, Peter