aplux/MediaPipe-Selfie-Segmentation

MediaPipe-Selfie-Segmentation: Semantic Segmentation

MediaPipe-Selfie-Segmentation is a real-time human segmentation model within Google's MediaPipe framework, optimized for efficient background separation. Leveraging deep learning, lightweight architecture, and hardware acceleration, it supports multi-resolution input on mobile and edge devices. Core features include precise subject extraction, background replacement/blurring, and applications in video conferencing (e.g., virtual backgrounds), AR filters (e.g., dynamic effects), and photo editing. With general and landscape versions, it balances low computational resource consumption with high-quality output, establishing itself as an industry benchmark for lightweight portrait segmentation.

Source model

• Input shape: 1x3x256x256
• Number of parameters: 0.11M
• Model size: 0.65M
• Output shape: 1x1x256x256

The source model can be found here.

Performance Reference

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Inference & Model Conversion

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License

• Source Model: APACHE-2.0

• Deployable Model: APLUX-MODEL-FARM-LICENSE