bleakie / maskinsightface Goto Github PK
View Code? Open in Web Editor NEW基于人脸关键区域提取的人脸识别(LFW:99.82%+ CFP_FP:98.50%+ AgeDB30:98.25%+)
License: Apache License 2.0
基于人脸关键区域提取的人脸识别(LFW:99.82%+ CFP_FP:98.50%+ AgeDB30:98.25%+)
License: Apache License 2.0
如题,非常感谢大佬的开源项目,学习中想先测试一下,谢谢大佬啦
i want to know how did you use Trillionpairs Datasets to generate .lst file? In your code, you mentioned 'webface celeb facescrub megaface fgnet ytf clfw' . so is there anyone of Trillionpairs?
Hello, can you give a pre training model, that Baidu online link expired! @bleakie bleakie
百度网盘链接被取消了
Hello!
Have you estimated what is the effect of your input image normalization approach (face wrapping + background removing) on the final quality of recognition, compared to the conventional way of normalization (like insightface do, for instance) ?
Thank you!
Hi @bleakie,
Congratulations for the nice work.
I am trying to use SSR-Net pretrained model in ncnn for edge device inference. For that I need to convert this model to onnx. However with this keras2onnx converter i am facing following trouble.
(ghimire36) C:\Users\ghimire\Desktop\keras2onnx>python keras_onnx.py
Traceback (most recent call last):
File "keras_onnx.py", line 7, in <module>
model = load_model('ssrnet_3_3_3_112_0.75_1.0.h5')
File "C:\ProgramData\Anaconda3\envs\ghimire36\lib\site-packages\tensorflow_core\python\keras\saving\save.py", line 143, in load_model
return hdf5_format.load_model_from_hdf5(filepath, custom_objects, compile)
File "C:\ProgramData\Anaconda3\envs\ghimire36\lib\site-packages\tensorflow_core\python\keras\saving\hdf5_format.py", line 159, in load_model_from_hdf5
raise ValueError('No model found in config file.')
ValueError: No model found in config file.
keras_onnx.py
from tensorflow.python.keras.models import load_model
import onnx
import keras2onnx
onnx_model_name = 'ssrnet_3_3_3_112_0.75_1.0.onnx'
model = load_model('ssrnet_3_3_3_112_0.75_1.0.h5')
onnx_model = keras2onnx.convert_keras(model, model.name)
keras2onnx.save_model(onnx_model, onnx_model_name)
Any help will be highly appreciated!
Thanks.
作者能同时发布128模型吗?
hello,can you tell me the code mening?
if args.num_classes != arg_params['fc7_weight'].shape[0]:
print ("discarding fc7 weights...")
arg_params.pop('fc7_weight')
File "train.py", line 1031, in
main()
File "train.py", line 1028, in main
train_net(args)
File "train.py", line 744, in train_net
sym, arg_params, aux_params = get_symbol(args, arg_params, aux_params)
File "train.py", line 220, in get_symbol
print('init VarGFaceNet', args.num_layers)
AttributeError: 'Namespace' object has no attribute 'num_layers'
请问模型y2-res2-6-10-2-dim256与y2-res4-8-16-4-dim256是同样的数据集训练的吗,数据集是居于glint和私有数据训练,私有数据大概多少?我用单用glint数据训练,效果不太好,CFP_FP的识别率差
y2-res2-6-10-2-dim256 这个是已经训练好的没有用mask的模型吗,我看CFP_FP(%)能到97.18,精度有这么高吗。
@bleakie
以0.5为分界线,经常把女的识别成男的
楼主您好,在运行gen_datasets.py时,出现prn模型读取错误(已从readme提供的百度网盘链接下载模型,并放入Data/nrt-data里边),请问您知道是什么原因吗?非常感谢!
代码:
self.pos_predictor = PosPrediction(self.resolution_inp, self.resolution_op)
prn_path = os.path.join(prefix, 'Data/net-data/256_256_resfcn256_weight')
if not os.path.isfile(prn_path + '.data-00000-of-00001'):
print("please download PRN trained model first.")
exit()
self.pos_predictor.restore(prn_path)
错误:
DataLossError (see above for traceback): Unable to open table file /home/../MaskInsightface/PRNet_Mask/Data/net-data/256_256_resfcn256_weight: Failed precondition: /../MaskInsightface/PRNet_Mask/Data/net-data/256_256_resfcn256_weight: perhaps your file is in a different file format and you need to use a different restore operator?
人脸质量检测facequality效果好像不好啊
Hi, I could not download "FaceQnet pretrained model .h5 file". The page is broken. Thank you.
预训练模型的下载链接没有开放权限啊,下载不了
按照我的理解,人脸对齐步骤如下
1.统计facial landmark相对检测框的坐标,求取平均脸的landmark坐标。
2.将landmark相对坐标转化为112x112或其他大小检测框的绝对坐标。
3.利用相似性变换计算待对齐人脸与标准脸的变换矩阵。
不知我上述理解是否有问题。这里面对于第二点,landmark相对坐标该如何转化到绝对坐标呢?按照步骤1的统计,绝对坐标是根据检测框大小求来的,但是针对不同姿态的人脸,检测框的宽高比可能就有很大变化,这样就应该没法直接套用112x112或112x96大小的人脸。
请问关于这一点,您有什么建议么?
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.