| | --- |
| | license: apache-2.0 |
| | --- |
| | # Yunet |
| |
|
| | ## **Use case** : `Face detection` |
| |
|
| | # Model description |
| |
|
| | Yunet is a lightweight and efficient face detection model optimized for real-time applications on embedded devices. Yunet designed specifically for detecting faces and 5 keypoints (2x eyes, 2x mouth, nose). The models are quantized to int8 format using ONNX QDQ to reduce memory footprint and improve inference speed on resource-constrained hardware. |
| |
|
| | Yunet is known for its fast inference and accuracy, making it suitable for applications such as face tracking, augmented reality, and user authentication. |
| |
|
| | ## Network information |
| |
|
| | | Network information | Value | |
| | |---------------------|----------------------------------------------------------------------------| |
| | | Framework | ONNX | |
| | | Quantization | int8 | |
| | | Provenance | https://github.com/opencv/opencv_zoo/tree/main/models/face_detection_yunet | |
| | |
| | ## Network inputs / outputs |
| | |
| | | Input Shape | Description | |
| | |--------------|----------------------------------------------------------| |
| | | (1, N, M, 3) | Single NxM RGB image with UINT8 values between 0 and 255 | |
| | |
| | |
| | |
| | YuNet produces multi-scale outputs for face detection and landmark localization. Yunet has 3 strides (32,16,8), for each stride S, outputs have the following shapes. |
| | |
| | | Output Shape | Description | |
| | |--------------|-------------------------------------------------------| |
| | | (1, F, 1) | **Classification scores:** Probability of face | |
| | | (1, F, 1) | **IoU scores:** Predicted IoU | |
| | | (1, F, 4) | **Bounding box regression:** [dx, dy, dw, dh] offsets | |
| | | (1, F, 10) | **Landmark regression:** 5 facial landmarks (x, y) | |
| | |
| | Where: |
| | |
| | - **F = (N/S)×(M/S)** (Total number of detections for a given stride S) |
| | ## Recommended Platforms |
| | |
| | | Platform | Supported | Recommended | |
| | |----------|-----------|-------------| |
| | | STM32L0 | [] | [] | |
| | | STM32L4 | [] | [] | |
| | | STM32U5 | [] | [] | |
| | | STM32H7 | [] | [] | |
| | | STM32MP1 | [] | [] | |
| | | STM32MP2 | [] | [] | |
| | | STM32N6 | [x] | [x] | |
| | |
| | ## Performances |
| | |
| | ### Metrics |
| | |
| | Performance metrics are measured using default STM32Cube.AI configurations with input/output allocated buffers. |
| | |
| | | Model | Dataset | Format | Resolution | Series | Internal RAM (KB) | External RAM (KB) | Weights Flash (KB) | STEdgeAI Core version | |
| | |------------------------------------------------------------------------------------------------------|------------|--------|------------|---------|-------------------|-------------------|--------------------|-----------------------| |
| | | [yunet 320x320](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/face_detection/yunet/Public_pretrainedmodel_public_dataset/widerface/yunetn_320/yunetn_320_qdq_int8.onnx) | WIDER FACE | Int8 | 3x320x320 | STM32N6 | 1130.49 | 0 | 92.31 | 3.0.0 | |
| | |
| | ### Reference **NPU** inference time (example) |
| | |
| | | Model | Dataset | Format | Resolution | Board | Execution Engine | Inference time (ms) | Inf / sec | STEdgeAI Core version | |
| | |------------------------------------------------------------------------------------------------------|------------|--------|------------|---------------|------------------|---------------------|-----------|-----------------------| |
| | | [yunet 320x320](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/face_detection/yunet/Public_pretrainedmodel_public_dataset/widerface/yunetn_320/yunetn_320_qdq_int8.onnx) | WIDER FACE | Int8 | 3x320x320 | STM32N6570-DK | NPU/MCU | 6.74 | 147.36 | 3.0.0 | |
| | |
| | |
| | ## Integration and support |
| | |
| | For integration examples and additional services, please refer to the STM32 AI model zoo services repository: |
| | [https://github.com/STMicroelectronics/stm32ai-modelzoo-services](https://github.com/STMicroelectronics/stm32ai-modelzoo-services) |
| | |
| | |
| | ## References |
| | |
| | - Yunet paper: [https://link.springer.com/article/10.1007/s11633-023-1423-y](https://link.springer.com/article/10.1007/s11633-023-1423-y) |
| | - MediaPipe Yunet model repository: [https://github.com/opencv/opencv_zoo/tree/main/models/face_detection_yunet]https://github.com/opencv/opencv_zoo/tree/main/models/face_detection_yunet) |
| | - WIDER FACE dataset: [http://shuoyang1213.me/WIDERFACE/](http://shuoyang1213.me/WIDERFACE/) |
