I’ve just finished the first class and I’d like to know if there is a way to use vgg16 to extract multiple categories from an image. Is it called
How should be my training directory? Should I copy the images to multiple folders (one folder per tag)?
I think you’re referring to multi-label classification? The output would use Sigmoid and select all categories with a probability score above some fixed threshold.
In that case, the one-directory-per-class approach will break down. You will need to have all image files in the same directory and use some alternative lookup scheme, perhaps with a CSV file:
Here is an example with categories delimited by spaces:
1, forest water road
3, habitation road
This design was used in the recent planet competition and you should be able to find sample Keras code for loading this files:
If you’re open to using Pytorch, here is an example we wrote while working on the competition
It uses something called a FileDataset which simply takes a list of file paths and a target (one-hot encoded) numpy array.
Thank you! Learning a lot from you!