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--- |
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license: apache-2.0 |
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license_link: >- |
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https://github.com/STMicroelectronics/stm32ai-modelzoo/raw/refs/heads/main/pose_estimation/LICENSE.md |
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pipeline_tag: keypoint-detection |
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--- |
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# Hand landmarks quantized |
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## **Use case** : `Pose estimation` |
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# Model description |
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Hand landmarks is a single pose estimation model targeted for real-time processing implemented in Tensorflow. |
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The model is quantized in int8 format using tensorflow lite converter. |
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## Network information |
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| Network information | Value | |
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|-------------------------|-----------------| |
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| Framework | TensorFlow Lite | |
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| Quantization | int8 | |
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| Provenance | https://github.com/PINTO0309/PINTO_model_zoo/tree/main/033_Hand_Detection_and_Tracking |
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| Paper | https://storage.googleapis.com/mediapipe-assets/Model%20Card%20Hand%20Tracking%20(Lite_Full)%20with%20Fairness%20Oct%202021.pdf | |
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## Networks inputs / outputs |
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With an image resolution of NxM with K keypoints to detect : |
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| Input Shape | Description | |
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| ----- | ----------- | |
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| (1, N, M, 3) | Single NxM RGB image with UINT8 values between 0 and 255 | |
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| Output Shape | Description | |
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| ----- | ----------- | |
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| (1, Kx3) | FLOAT values Where Kx3 are the (x,y,conf) values of each keypoints | |
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## Recommended Platforms |
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| Platform | Supported | Recommended | |
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|----------|-----------|-------------| |
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| STM32L0 | [] | [] | |
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| STM32L4 | [] | [] | |
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| STM32U5 | [] | [] | |
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| STM32H7 | [] | [] | |
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| STM32MP1 | [x] | [] | |
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| STM32MP2 | [x] | [x] | |
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| STM32N6 | [x] | [x] | |
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# Performances |
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## Metrics |
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Measures are done with default STM32Cube.AI configuration with enabled input / output allocated option. |
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### Reference **NPU** memory footprint based on COCO Person dataset (see Accuracy for details on dataset) |
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|Model | Dataset | Format | Resolution | Series | Internal RAM (KiB) | External RAM (KiB) | Weights Flash (KiB) | STM32Cube.AI version | STEdgeAI Core version | |
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|----------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------| |
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| [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 | 10.2.0 | 2.2.0 | |
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### Reference **NPU** inference time based on COCO Person dataset (see Accuracy for details on dataset) |
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| Model | Dataset | Format | Resolution | Board | Execution Engine | Inference time (ms) | Inf / sec | STM32Cube.AI version | STEdgeAI Core version | |
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|--------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------| |
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| [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 | 10.2.0 | 2.2.0 | |
