One 、InsightFace brief introduction
InsightFace It's a 2D/3D Face analysis project .InsightFace The code is in MIT Issued under license . about acadmic And there are no restrictions on commercial use .
Training data with comments （ And the model trained with these data ） Only for non-commercial research purposes .
In this repository , We provide training data for depth recognition , Network setup and loss design . Training data includes standardized MS1M,VGG2 and CASIA-Webface Data sets , These datasets have been written in MXNet Binary format packaging . The network backbone includes ResNet,MobilefaceNet,MobileNet,InceptionResNet_v2,DenseNet,DPN. The loss function includes Softmax,SphereFace,CosineFace,ArcFace and Triplet（Euclidean / Angular）Loss.
Our approach ArcFace Initially in arXiv Described in the technical report . By using this repository , You can simply implement through a single model LFW 99.80％+ and Megaface 98％+. This repository can help researchers / Engineers quickly develop depth recognition algorithms in two steps ： Download the binary data set and run the training script .
Two 、 be based on InsightFace Of Java Version face comparison 、 Face search service
The project uses components ：spring boot + milvus + onnx, Ensure stable operation in multi-threaded mode , Resource ratio deployment Python At least reduce the service 50%. Secondly, the natural support of the project Java client , And to provide restful Of API, See file -1.2.0.
Project open source address ：https://gitee.com/open-visual/face-search
The test case of the project uses the photos of several business leaders as the search library , The picture shows the result preview ：
Project open source address ：https://gitee.com/open-visual/face-search
be based on InsightFace High precision face recognition , More related articles of hongruan can be directly benchmarked
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