Hi,
I understand that one would get a shape mismatch if one just changes the num_output parameter, but I don't get how that net surgery tutorial is useful in my case.
Here is an example of what I would like to do:
- classify Gorilla ( label number 366 in the synset file)
- classify Chimpanzee (label number 367 in the synset file)
- classify background / jungle / grass ( not present, so I want to add this class, number 1000)
Would the following work?
1) Add 'background, jungle, grass' to the file synset_words.txt
2) Create training set like this:
chimpanzee_0.png 367
chimpanzee_1.png 367
gorilla_0.png 366
background_0.png 1000
3) Change num_outuput to 1001, (should I change the name of the layer as well?)
4) Resume training of the pretrained model