Hi JB!



 gass_jb:

I have to find a suitable model for recognizing different events within video clips.





 gass_jb:

Classes (A,B,C,D,E) and each class have subclasses


Could you clarify your use case?
First, let’s temporarily ignore the “subclasses” issue, and just look at
“classes.”
Second, I will purposely speak in the language of two-dimensional
still images rather than “three-dimensional” videos.  There is a clean
analogy between the two, so, to focus the discussion, please describe
your use case in the still-image setting.
Let a single sample (which would typically be part of a batch consisting
of one or more independent samples) be a single still image.
Do you wish to perform (single-label), multi-class classification, e.g.,
this is an image of a cat or a pigeon or a shark (but not more than
one at a time)?
Do you wish to perform multi-label, multi-class classification, e.g.,
this image contains a cat, does not contain a pigeon, and does
contain a shark?
Do you wish to perform object detection, that is, this image contains
one cat in bounding-box A, three pigeons, one each in bounding-boxes
B, C, and D, and no sharks?
(Other possibilities would include semantic segmentation and instance
segmentation.)
Now, about your “subclasses:”  What is the substantive meaning of
a class vs. a subclass?  Why don’t we just say that you have 17
different classes (that happen to be labelled “A0”, “A1”, “B2”, “B3”,
“B4”, …, “E13”, “E14”, “E15”, and “E16”)?
Best.
K. Frank