Comments (4)
another question: When I use two gpus, how to change the learning rate? lr*2?
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please find the answer in #3
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@yangyangkiki Is there some tricks I forgot to add? I followed your Readme, but the training on 300W dataset was not the same with the log you provided. Finally, the nme for 300W validation is about 0.04, which has big difference between your paper's, and as for config file, I have changed the validation set to 300W_validation, in you paper , the nme is 0.0322. Please help me ! Really thanks!
from hrnet-facial-landmark-detection.
Our code has been updated.
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Related Issues (20)
- Want to run inference on CPU, any solution? HOT 2
- 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
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