Key points extration model about depthnets HOT 6 OPEN

ME TOO !!! PLEASE .....

from depthnets.

Hi there, you can follow the steps mentioned here to use the Recombinator Networks to get the keypoint predictions: https://github.com/SinaHonari/RCN/tree/master/trained_model/RCN_300W

There is a pre-trained keypoint prediction model you can use. This model was used to extract the keypoints for the DepthNet experiments. Note that the Recombinator Network repo is in Theano.

from depthnets.

thanks @SinaHonari . The question is that RCN extracts 68 points instead of 66 points used in DepthNet; is there a way to convert from 68 to 66 pts?

from depthnets.

@y-x-c there is this method in the utils.py file:

That converts from 66 to 68, but you could just use that to infer going from 68 to 66 (removing zero-indexed indices 60 and 64)

from depthnets.

thanks! I will try.

from depthnets.

@royaljava @seungtaekoh @y-x-c sorry for a rather late addressal of the issue. I have labeled it 'enhancement request'. While we used @SinaHonari's RCN network to extract face keypoints, unfortunately it is in Theano and perhaps not a lot of people use it anymore (or will bother to remember how to set it up). If you are able to use an off-the-shelf keypoint detector that extracts either 68 or 66 keypoints, that would be faster. Or, worst case scenario, you may have to train one yourself, but this shouldn't take too long if you're working with a modest resolution. An example of one of these repos can be found here: https://github.com/soheil-mpg/Facial-Keypoint-Detection (it includes data in the repo)

Thanks.

from depthnets.