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---
license: apache-2.0
license_name: sla0044
pipeline_tag: keypoint-detection
---
# Hand landmarks quantized
## **Use case** : `Pose estimation`
# Model description
Hand landmarks is a single pose estimation model targeted for real-time processing implemented in Tensorflow.
The model is quantized in int8 format using tensorflow lite converter.
## Network information
| Network information | Value |
|-------------------------|-----------------|
| Framework | TensorFlow Lite |
| Quantization | int8 |
| Provenance | https://github.com/PINTO0309/PINTO_model_zoo/tree/main/033_Hand_Detection_and_Tracking
| Paper | https://storage.googleapis.com/mediapipe-assets/Model%20Card%20Hand%20Tracking%20(Lite_Full)%20with%20Fairness%20Oct%202021.pdf |
## Networks inputs / outputs
With an image resolution of NxM with K keypoints to detect :
| Input Shape | Description |
| ----- | ----------- |
| (1, N, M, 3) | Single NxM RGB image with UINT8 values between 0 and 255 |
| Output Shape | Description |
| ----- | ----------- |
| (1, Kx3) | FLOAT values Where Kx3 are the (x,y,conf) values of each keypoints |
## Recommended Platforms
| Platform | Supported | Recommended |
|----------|-----------|-------------|
| STM32L0 | [] | [] |
| STM32L4 | [] | [] |
| STM32U5 | [] | [] |
| STM32H7 | [] | [] |
| STM32MP1 | [x] | [] |
| STM32MP2 | [x] | [x] |
| STM32N6 | [x] | [x] |
# Performances
## Metrics
Measures are done with default STM32Cube.AI configuration with enabled input / output allocated option.
### Reference **NPU** memory footprint based on COCO Person dataset (see Accuracy for details on dataset)
|Model | Dataset | Format | Resolution | Series | Internal RAM (KiB) | External RAM (KiB) | Weights Flash (KiB) | STM32Cube.AI version | STEdgeAI Core version |
|----------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
| [hand_landmarks](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/hand_landmarks/Public_pretrainedmodel_custom_dataset/custom_dataset_hands_21kpts/hand_landmarks_full_224_int8_pc.tflite) | COCO-Person | Int8 | 224x224x3 | STM32N6 | 1739.5 | 0.0 | 3283.38 | 10.0.0 | 2.0.0 |
### Reference **NPU** inference time based on COCO Person dataset (see Accuracy for details on dataset)
| Model | Dataset | Format | Resolution | Board | Execution Engine | Inference time (ms) | Inf / sec | STM32Cube.AI version | STEdgeAI Core version |
|--------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
| [hand_landmarks](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/hand_landmarks/Public_pretrainedmodel_custom_dataset/custom_dataset_hands_21kpts/hand_landmarks_full_224_int8_pc.tflite) | custom_dataset_hands_21kpts | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 20.75 | 48.19 | 10.0.0 | 2.0.0 | |