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.
| 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 |
| Platform | Supported | Recommended |
|---|
| STM32L0 | [] | [] |
| STM32L4 | [] | [] |
| STM32U5 | [] | [] |
| STM32H7 | [] | [] |
| STM32MP1 | [] | [] |
| STM32MP2 | [] | [] |
| STM32N6 | [x] | [x] |
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 |
|---|
| BlazeFace Front 128x128 per channel | WIDER FACE (frontal) | Int8 | 128x128x3 | STM32N6 | 528 | 0 | 150.97 | 4.0.0 |
| Model | Dataset | Format | Resolution | Board | Execution Engine | Inference time (ms) | Inf / sec | STEdgeAI Core version |
|---|
| BlazeFace Front 128x128 per channel | WIDER FACE (frontal) | Int8 | 128x128x3 | STM32N6570-DK | NPU/MCU | 5.09 | 196.3 | 4.0.0 |
For integration examples and additional services, please refer to the STM32 AI model zoo services repository:
https://github.com/STMicroelectronics/stm32ai-modelzoo-services