louis-she / center-loss.pytorch Goto Github PK
View Code? Open in Web Editor NEWcenter loss for face recognition
center loss for face recognition
Hi, thanks for your work, i want to ask you a question, how to do the test? I tested the resnet50 and epoch_100.pth.tar on lfw, with crop face, but the accuracy is 0.66. How can I reproduce this result? thank you.
Could you please let me know if you are generating landmarks for lfw? I am currently using a dataset with low resolution images for which I am unable to generate landmarks (using MTCNN), so I'm looking for an implementation that isn't using landmarks..
Hello, I am a beginner. So maybe my question is simple. Please forgive me.
In the main.py. The code:
model = model_class(num_classes).to(device)
trainables_wo_bn = [param for name, param in model.named_parameters() if
param.requires_grad and 'bn' not in name]
trainables_only_bn = [param for name, param in model.named_parameters() if
param.requires_grad and 'bn' in name]
optimizer = torch.optim.SGD([
{'params': trainables_wo_bn, 'weight_decay': 0.0001},
{'params': trainables_only_bn}
], lr=args.lr, momentum=0.9)
I want to know why you separate the parameters to two parts: trainables_wo_bn and trainables_only_bn,
In the optimizer, I always write:
optimizer = torch.optim.SGD(model.parameters(), lr = args.lr, momentum=0.9)
Did I do something wrong? Please help me, thank you so much!
Is it necessary to normalize features?
can not tar -xvf the pretrained model.
Hi, thanks for your pytorch implementation of the center face .
I played with your code for a while, and I may found some problem.
by this way, too much background are envoled.
for klass, name in enumerate(names):
def add_class(image):
image_path = os.path.join(images_root, name, image)
return (image_path, klass, name)
images_of_person = os.listdir(os.path.join(images_root, name))
total = len(images_of_person)
training_set += map(
add_class,
images_of_person[:ceil(total * train_val_split)])
validation_set += map(
add_class,
images_of_person[floor(total * train_val_split):])
I think you should use samples listed in the pairsDevTrain.txt to train and pairsDevTest.txt to test by the lfw paper
thanks for your codes!
i have a question that what is the protocol do you use in your training,
there are
PAIRS_TRAIN = "http://vis-www.cs.umass.edu/lfw/pairsDevTrain.txt"
PAIRS_VAL = "http://vis-www.cs.umass.edu/lfw/pairsDevTest.txt"
in the codes,but doesnot use.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.