license: other
license_link: >-
https://github.st.com/AIS/stm32ai-modelzoo/raw/master/object_detection/LICENSE.md
pipeline_tag: object-detection
BlazeFace Front 128x128 Quantized
Use case : Object detection
Model description
BlazeFace Front 128x128 is a lightweight and efficient face detection model optimized for real-time applications on embedded devices. It is a variant of the BlazeFace architecture, designed specifically for detecting frontal faces at a resolution of 128x128 pixels. The model is quantized to int8 format using TensorFlow Lite converter to reduce memory footprint and improve inference speed on resource-constrained hardware.
BlazeFace 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 | TensorFlow Lite |
| Quantization | int8 |
| Input resolution | 128x128 |
| Provenance | https://github.com/PINTO0309/PINTO_model_zoo/tree/main/030_BlazeFace |
Network inputs / outputs
| Input Shape | Description |
|---|---|
| (1, 128, 128, 3) | Single 128x128 RGB image with FLOAT32 values between -1 and 1 |
| Output Shape | Description |
|---|---|
| (1, 512, 16) | FLOAT32 tensor containing bounding box coordinates and keypointss for detected faces |
| (1, 512, 1) | FLOAT32 tensor containing confidence scores for detected faces |
| (1, 384, 16) | FLOAT32 tensor containing bounding box coordinates and keypointss for detected faces |
| (1, 384, 1) | FLOAT32 tensor containing confidence scores for detected faces |
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) | STM32Cube.AI version | STEdgeAI Core version |
|---|---|---|---|---|---|---|---|---|---|
| BlazeFace Front 128x128 per channel | WIDER FACE (frontal) | Int8 | 128x128x3 | STM32N6 | 528 | 0 | 150.97 | 10.2.0 | 2.2.0 |
Reference NPU inference time (example)
| Model | Dataset | Format | Resolution | Board | Execution Engine | Inference time (ms) | Inf / sec | STM32Cube.AI version | STEdgeAI Core version |
|---|---|---|---|---|---|---|---|---|---|
| BlazeFace Front 128x128 per channel | WIDER FACE (frontal) | Int8 | 128x128x3 | STM32N6570-DK | NPU/MCU | 5.09 | 196.3 | 10.2.0 | 2.2.0 |
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
References
- BlazeFace paper: https://arxiv.org/abs/1907.05047
- MediaPipe BlazeFace model repository: https://github.com/PINTO0309/PINTO_model_zoo/tree/main/030_BlazeFace
- WIDER FACE dataset: http://shuoyang1213.me/WIDERFACE/