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face-recognition-resnet100-arcface-onnx

Use Case and High-Level Description

The face-recognition-resnet100-arcface-onnx model is a deep face recognition model with ResNet100 backbone and ArcFace loss. ArcFace is a novel supervisor signal called additive angular margin which used as an additive term in the softmax loss to enhance the discriminative power of softmax loss. This model is pre-trained in MXNet* framework and converted to ONNX* format. More details provided in the paper and repository.

Specification

Metric Value
Type Face recognition
GFLOPs 24.2115
MParams 65.1320
Source framework MXNet*

Accuracy

Metric Value
LFW accuracy 99.68%

Input

Original Model

Image, name: data, shape: 1, 3, 112, 112, format: B, C, H, W, where:

  • B - batch size
  • C - channel
  • H - height
  • W - width

Channel order is RGB.

Converted Model

Image, name: data, shape: 1, 3, 112, 112, format: B, C, H, W, where:

  • B - batch size
  • C - channel
  • H - height
  • W - width

Channel order is BGR.

Output

Original Model

Face embeddings, name: fc1, shape: 1, 512, output data format: B, C, where:

  • B - batch size
  • C - row-vector of 512 floating points values, face embeddings

The net outputs on different images are comparable in cosine distance.

Converted Model

Face embeddings, name: fc1, shape: 1, 512, output data format: B, C, where:

  • B - batch size
  • C - row-vector of 512 floating points values, face embeddings

The net outputs on different images are comparable in cosine distance.

Download a Model and Convert it into OpenVINO™ IR Format

You can download models and if necessary convert them into OpenVINO™ IR format using the Model Downloader and other automation tools as shown in the examples below.

An example of using the Model Downloader:

omz_downloader --name <model_name>

An example of using the Model Converter:

omz_converter --name <model_name>

Demo usage

The model can be used in the following demos provided by the Open Model Zoo to show its capabilities:

Legal Information

The original model is distributed under the Apache License, Version 2.0. A copy of the license is provided in <omz_dir>/models/public/licenses/APACHE-2.0.txt.