Comments (1)
The step "make test" and "make runtest" are not necessary for using caffe. It can only check whether the gradient is realized correctly or not.
In my caffe project, I have written some layers but don't write their test layers. If "make" is successfully, the project could be used for training and testing.
And you can use caffe release candidate version which is released on 19 Sep 2014 to train my model.
from face_verification_experiment.
Related Issues (20)
- There may be some errors in the 'labels' HOT 3
- Where do you get the 5 facial points for MSCELEB dataset. Do you use some other model to find the facial points ? HOT 1
- Xavier vs Gaussian HOT 1
- I feel the size of the trainning data doubt HOT 1
- no an issue but a doubt HOT 2
- about lfw labels in model C-LightenedCNN_C_lfw.mat HOT 3
- Error occurred when computing accuracy
- Query
- no such file in your clean list
- Eltwise层名字拼写错误有影响吗?
- MegaFace Evaluation: it generated 'OpenCV Error' when running experiment.py with own features HOT 1
- hello,your model A and B is small,why your model C is bigger than B by using the same cnn architecture HOT 1
- can't get the same result HOT 3
- How to use fine tuned model to do classification for an image in light CNN?
- Any architecture patent information HOT 1
- the issue about architecture
- LightenedCNN_A_deploy.prototxt
- The evaluation of CASIA-NIR2.0
- Request Pretrained lightenedCNN model in .mat format HOT 1
- Computation of rank 1
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from face_verification_experiment.