Multi-face detection about facial-landmark-detection-hrnet HOT 6 OPEN

I have no experiences in this kind of project but, you might want to checkout this post:
https://medium.com/neuromation-blog/neuronuggets-understanding-human-poses-in-real-time-b73cb74b3818

from facial-landmark-detection-hrnet.

thank you. yes i have to use pose estimation methods for detecting multi faces.
I want to ask how to train images of 96x96 faces and heatmap labels on 256x256 input network size.
Currently I use 96x96 image and its heatmap labelsl with same size 96x96x1 network input and it can predict only 1 face of output size 96x96x15, where 15 maps are 15 keypoints.
In your case the input image is larger than the face size. How can i do it?

please help me

from facial-landmark-detection-hrnet.

I guess this training process is similar to body key points detection, and this repo do not support that kind of training. The training images in this repo contains only a single sample, and the input image is naturally down sampled by the conv layers; while a bottom up approach may consists multiple. They are so different.

from facial-landmark-detection-hrnet.

oh i see,
so you use the face bonding box information from your dataset and crop and feed if for training? all iamges are same size after crop? and what about the network input size and output size?

thank you

from facial-landmark-detection-hrnet.

you use some face detector to get the boudning box, crop and then feed to predcition network right? thats why you can use any resolution image while testing.

from facial-landmark-detection-hrnet.

Exactly! You can find some details in the preprocessing module:
https://github.com/yinguobing/facial-landmark-detection-hrnet/blob/master/preprocessing.py

from facial-landmark-detection-hrnet.