Comments (2)
lucaskyle
commented on July 23, 2024
the hrnet input size will be (256,256,3)
as far as i know :
center=torch.tensor([[128.0,128.0]])
scale= torch.tensor([1.28])
so feed the network with 256*256 face image
and u may get (a,98,2) results.
from hrnet-facial-landmark-detection.
starhiking
commented on July 23, 2024
from hrnet-facial-landmark-detection.
Related Issues (20)
- head
- head estimation
- How to acquire labels on own images? HOT 1
- 300W pretrained model weights' name inconsistent with updated model HOT 3
- Could you share with the model file of RACE dataset (106 points)
- So many bugs.....
- how to test this code in other Dataset? such as CelebA and FFHQ.
- Error in loading model trained on 300W dataset HOT 2
- volatile gpu-util=0% when training HOT 1
- Why don't you use Sigmoid fucntion as the last activation function?
- Why do you re-write such "crop" function ? HOT 1
- 300W Dataset Annotation File Detail HOT 1
- How to download the 300W full set? HOT 2
- I want to detect landmarks in real time HOT 1
- demo.py
- What is the aim of "Transform back"? Is it necesary when inference on my images?
- How to modify code for only one landmarks cordinates ,Like I have only one xy coordinates
- How long it takes to detect a image HOT 1
- Confidence Score of Detected Landmarks
- How to use this pre-trainmodel?
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from hrnet-facial-landmark-detection.