InsightFace: Open‑Source 2D/3D Deep Face Analysis Toolbox with PaddlePaddle Support
InsightFace is an open‑source 2D/3D deep face analysis toolbox that implements a variety of detection, alignment and recognition algorithms, now supports PaddlePaddle with out‑of‑the‑box models, high‑throughput distributed training up to 60 million classes, and provides a one‑line demo script for quick testing.
InsightFace is an open‑source 2D/3D deep face analysis toolbox that implements a wide range of face detection, alignment and recognition algorithms, optimized for training and deployment, and has been cited over 2100 times since the ArcFace paper.
The project shows strong activity on GitHub, supporting multiple frameworks such as MXNet, PyTorch and PaddlePaddle. Recent updates add PaddlePaddle implementations of Blazeface, ArcFace and MobileFace that run out‑of‑the‑box with speed advantages and can scale to distributed training of up to 60 million classes.
Key highlights include:
ArcFace model ready‑to‑use with speed advantage.
ResNet large‑model distributed training with high throughput, supporting up to 60 million classifications.
A one‑line demo command for simple face recognition.
python3.7 tools/test_recognition.py --det --rec --index=index.bin --input=friends2.jpg --output="./output"
The demo saves visual results in the output directory, as shown in the following image:
To help users become familiar with InsightFace, the project initiators and PaddlePaddle developers host live B‑station sessions and a registration course, inviting participants to join the InsightFace technical community.
Project repository: https://github.com/deepinsight/insightface
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