Release AI-ModelZoo-4.0.0

README.md

@@ -1,3 +1,81 @@
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-license: apache-2.0
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+---
+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/)