| --- |
| license: other |
| license_name: sla0044 |
| license_link: >- |
| https://github.com/STMicroelectronics/stm32ai-modelzoo/raw/refs/heads/main/pose_estimation/LICENSE.md |
| pipeline_tag: keypoint-detection |
| --- |
| # MoveNet quantized |
|
|
| ## **Use case** : `Pose estimation` |
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| # Model description |
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| MoveNet 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 | |
| |-------------------------|-----------------| |
| | Framework | TensorFlow Lite | |
| | Quantization | int8 | |
| | Provenance | https://www.kaggle.com/models/google/movenet |
| | Paper | https://storage.googleapis.com/movenet/MoveNet.SinglePose%20Model%20Card.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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| - For heatmaps models |
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| | Input Shape | Description | |
| | ----- | ----------- | |
| | (1, N, M, 3) | Single NxM RGB image with UINT8 values between 0 and 255 | |
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| | Output Shape | Description | |
| | ----- | ----------- | |
| | (1, W, H, K) | FLOAT values Where WXH is the resolution of the output heatmaps and K is the number of keypoints| |
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| - For the other models |
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| | Input Shape | Description | |
| | ----- | ----------- | |
| | (1, N, M, 3) | Single NxM RGB image with UINT8 values between 0 and 255 | |
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| | Output Shape | Description | |
| | ----- | ----------- | |
| | (1, Kx3) | FLOAT values Where Kx3 are the (x,y,conf) values of each keypoints | |
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|
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| ## Recommended Platforms |
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| | Platform | Supported | Recommended | |
| |----------|-----------|-------------| |
| | STM32L0 | [] | [] | |
| | STM32L4 | [] | [] | |
| | STM32U5 | [] | [] | |
| | STM32H7 | [] | [] | |
| | STM32MP1 | [x] | [] | |
| | STM32MP2 | [x] | [x] | |
| | 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) |
| |Model | Dataset | Format | Resolution | Series | Internal RAM (KiB)| External RAM (KiB) | Weights Flash (KiB) | STEdgeAI Core version | |
| |----------|------------------|--------|-------------|------------------|------------------|---------------------|-------|-------------------------| |
| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_192/st_movenet_lightning_a100_heatmaps_192_int8.tflite) | COCO-Person | Int8 | 192x192x3 | STM32N6 | 914.88 | 0.0 | 2304.0 | 3.0.0 | |
| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_224/st_movenet_lightning_a100_heatmaps_224_int8.tflite) | COCO-Person | Int8 | 224x224x3 | STM32N6 | 1239.04 | 0.0 | 2304.0 | 3.0.0 | |
| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_256/st_movenet_lightning_a100_heatmaps_256_int8.tflite) | COCO-Person | Int8 | 256x256x3 | STM32N6 | 1607.68 | 0.0 | 2304.0 | 3.0.0 | |
|
|
|
|
| ### 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 | STEdgeAI Core version | |
| |--------|------------------|--------|-------------|------------------|------------------|---------------------|-------|-------------------------| |
| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_192/st_movenet_lightning_a100_heatmaps_192_int8.tflite) | COCO-Person | Int8 | 192x192x3 | STM32N6570-DK | NPU/MCU | 22.05 | 45.35 | 3.0.0 | |
| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_224/st_movenet_lightning_a100_heatmaps_224_int8.tflite) | COCO-Person | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 27.64 | 36.18 | 3.0.0 | |
| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_256/st_movenet_lightning_a100_heatmaps_256_int8.tflite) | COCO-Person | Int8 | 256x256x3 | STM32N6570-DK | NPU/MCU | 35.50 | 28.17 | 3.0.0 | |
|
|
|
|
| ### Reference **MPU** inference time based on COCO Person dataset (see Accuracy for details on dataset) |
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|
| | Model | Dataset | Format | Resolution | Quantization | Board | Execution Engine | Frequency | Inference time (ms) | %NPU | %GPU | %CPU | X-LINUX-AI version | Framework | |
| |--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------|--------|------------|----------------|-------------------|------------------|-----------|---------------------|-------|-------|------|--------------------|-----------------------| |
| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_192/st_movenet_lightning_a100_heatmaps_192_int8.tflite) | custom_coco_person_17kpts | Int8 | 192x192x3 | per-channel** | STM32MP257F-EV1 | NPU/GPU | 800 MHz | 55.81 | 2.87 | 97.13 | 0 | v6.1.0 | OpenVX | |
| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_224/st_movenet_lightning_a100_heatmaps_224_int8.tflite) | custom_coco_person_17kpts | Int8 | 224x224x3 | per-channel** | STM32MP257F-EV1 | NPU/GPU | 800 MHz | 79.41 | 2.41 | 97.59 | 0 | v6.1.0 | OpenVX | |
| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_256/st_movenet_lightning_a100_heatmaps_256_int8.tflite) | custom_coco_person_17kpts | Int8 | 256x256x3 | per-channel** | STM32MP257F-EV1 | NPU/GPU | 800 MHz | 68.42 | 3.32 | 96.68 | 0 | v6.1.0 | OpenVX | |
| | [ST MoveNet Lightning heatmaps per-tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_192/st_movenet_lightning_a100_heatmaps_192_int8_per_tensor.tflite) | custom_coco_person_17kpts | Int8 | 192x192x3 | per-tensor | STM32MP257F-EV1 | NPU/GPU | 800 MHz | 8.20 | 82.06 | 17.94 | 0 | v6.1.0 | OpenVX | |
| | [ST MoveNet Lightning heatmaps per-tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_224/st_movenet_lightning_a100_heatmaps_224_int8_per_tensor.tflite) | custom_coco_person_17kpts | Int8 | 224x224x3 | per-tensor | STM32MP257F-EV1 | NPU/GPU | 800 MHz | 11.63 | 83.75 | 16.25 | 0 | v6.1.0 | OpenVX | |
| | [ST MoveNet Lightning heatmaps per-tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_256/st_movenet_lightning_a100_heatmaps_256_int8_per_tensor.tflite) | custom_coco_person_17kpts | Int8 | 256x256x3 | per-tensor | STM32MP257F-EV1 | NPU/GPU | 800 MHz | 13.10 | 81.39 | 18.61 | 0 | v6.1.0 | OpenVX | |
| | [MoveNet Lightning](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_a100_192/movenet_singlepose_lightning_a100_192_int8.tflite) | custom_dataset_person_17kpts| Int8 | 192x192x3 | per-channel** | STM32MP257F-EV1 | NPU/GPU | 800 MHz | 63.80 | 6.58 | 93.42 | 0 | v6.1.0 | OpenVX | |
| | [MoveNet Thunder](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_thunder_a100_256/movenet_singlepose_thunder_a100_256_int8.tflite) | custom_dataset_person_17kpts| Int8 | 256x256x3 | per-channel** | STM32MP257F-EV1 | NPU/GPU | 800 MHz | 183.49 | 3.47 | 96.53 | 0 | v6.1.0 | OpenVX | |
| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_192/st_movenet_lightning_a100_heatmaps_192_int8.tflite) | custom_coco_person_17kpts | Int8 | 192x192x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 315.44 | NA | NA | 100 | v6.1.0 | TensorFlowLite 2.18.0 | |
| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_224/st_movenet_lightning_a100_heatmaps_224_int8.tflite) | custom_coco_person_17kpts | Int8 | 224x224x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 416.98 | NA | NA | 100 | v6.1.0 | TensorFlowLite 2.18.0 | |
| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_256/st_movenet_lightning_a100_heatmaps_256_int8.tflite) | custom_coco_person_17kpts | Int8 | 256x256x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 533.61 | NA | NA | 100 | v6.1.0 | TensorFlowLite 2.18.0 | |
| | [ST MoveNet Lightning heatmaps per-tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_192/st_movenet_lightning_a100_heatmaps_192_int8_per_tensor.tflite) | custom_coco_person_17kpts | Int8 | 192x192x3 | per-tensor | STM32MP157F-DK2 | 2 CPU | 800 MHz | 424.77 | NA | NA | 100 | v6.1.0 | TensorFlowLite 2.18.0 | |
| | [ST MoveNet Lightning heatmaps per-tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_224/st_movenet_lightning_a100_heatmaps_224_int8_per_tensor.tflite) | custom_coco_person_17kpts | Int8 | 224x224x3 | per-tensor | STM32MP157F-DK2 | 2 CPU | 800 MHz | 558.26 | NA | NA | 100 | v6.1.0 | TensorFlowLite 2.18.0 | |
| | [ST MoveNet Lightning heatmaps per-tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_256/st_movenet_lightning_a100_heatmaps_256_int8_per_tensor.tflite) | custom_coco_person_17kpts | Int8 | 256x256x3 | per-tensor | STM32MP157F-DK2 | 2 CPU | 800 MHz | 727.03 | NA | NA | 100 | v6.1.0 | TensorFlowLite 2.18.0 | |
| | [MoveNet Lightning](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_a100_192/movenet_singlepose_lightning_a100_192_int8.tflite) | custom_dataset_person_17kpts| Int8 | 192x192x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 196.81 | NA | NA | 100 | v6.1.0 | TensorFlowLite 2.18.0 | |
| | [MoveNet Thunder](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_thunder_a100_256/movenet_singlepose_thunder_a100_256_int8.tflite) | custom_dataset_person_17kpts| Int8 | 256x256x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 766.38 | NA | NA | 100 | v6.1.0 | TensorFlowLite 2.18.0 | |
| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_192/st_movenet_lightning_a100_heatmaps_192_int8.tflite) | custom_coco_person_17kpts | Int8 | 192x192x3 | per-channel | STM32MP135F-DK | 1 CPU | 1000 MHz | 484.64 | NA | NA | 100 | v6.1.0 | TensorFlowLite 2.18.0 | |
| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_224/st_movenet_lightning_a100_heatmaps_224_int8.tflite) | custom_coco_person_17kpts | Int8 | 224x224x3 | per-channel | STM32MP135F-DK | 1 CPU | 1000 MHz | 651.62 | NA | NA | 100 | v6.1.0 | TensorFlowLite 2.18.0 | |
| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_256/st_movenet_lightning_a100_heatmaps_256_int8.tflite) | custom_coco_person_17kpts | Int8 | 256x256x3 | per-channel | STM32MP135F-DK | 1 CPU | 1000 MHz | 844.89 | NA | NA | 100 | v6.1.0 | TensorFlowLite 2.18.0 | |
| | [ST MoveNet Lightning heatmaps per-tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_192/st_movenet_lightning_a100_heatmaps_192_int8_per_tensor.tflite) | custom_coco_person_17kpts | Int8 | 192x192x3 | per-tensor | STM32MP135F-DK | 1 CPU | 1000 MHz | 578.72 | NA | NA | 100 | v6.1.0 | TensorFlowLite 2.18.0 | |
| | [ST MoveNet Lightning heatmaps per-tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_224/st_movenet_lightning_a100_heatmaps_224_int8_per_tensor.tflite) | custom_coco_person_17kpts | Int8 | 224x224x3 | per-tensor | STM32MP135F-DK | 1 CPU | 1000 MHz | 772.76 | NA | NA | 100 | v6.1.0 | TensorFlowLite 2.18.0 | |
| | [ST MoveNet Lightning heatmaps per-tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_256/st_movenet_lightning_a100_heatmaps_256_int8_per_tensor.tflite) | custom_coco_person_17kpts | Int8 | 256x256x3 | per-tensor | STM32MP135F-DK | 1 CPU | 1000 MHz | 1007.57 | NA | NA | 100 | v6.1.0 | TensorFlowLite 2.18.0 | |
| | [MoveNet Lightning](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_a100_192/movenet_singlepose_lightning_a100_192_int8.tflite) | custom_dataset_person_17kpts| Int8 | 192x192x3 | per-channel | STM32MP135F-DK | 1 CPU | 1000 MHz | 306.34 | NA | NA | 100 | v6.1.0 | TensorFlowLite 2.18.0 | |
| | [MoveNet Thunder](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_thunder_a100_256/movenet_singlepose_thunder_a100_256_int8.tflite) | custom_dataset_person_17kpts| Int8 | 256x256x3 | per-channel | STM32MP135F-DK | 1 CPU | 1000 MHz | 1131.30 | NA | NA | 100 | v6.1.0 | TensorFlowLite 2.18.0 | |
|
|
| ** **To get the most out of MP25 NPU hardware acceleration, please use per-tensor quantization** |
|
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| ** **Note:** On STM32MP2 devices, per-channel quantized models are internally converted to per-tensor quantization by the compiler using an entropy-based method. This may introduce a slight loss in accuracy compared to the original per-channel models. |
|
|
| ### OKS on COCO Person dataset |
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|
|
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| Dataset details: [link](https://cocodataset.org/#download) , License [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/legalcode) , Quotation[[1]](#1) , Number of classes: 80, Number of images: 118,287 |
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|
| | Model | Format | Resolution | Training Dataset | OKS | |
| |-------|--------|------------|------------------|----------------| |
| | [ST MoveNet Lightning heatmaps per-channel](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_192/st_movenet_lightning_a100_heatmaps_192_int8.tflite) | Int8 | 192x192x3 | custom ST | 57.64 % | |
| | [ST MoveNet Lightning heatmaps per-channel](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_224/st_movenet_lightning_a100_heatmaps_224_int8.tflite) | Int8 | 224x224x3 | custom ST | 62.29 % | |
| | [ST MoveNet Lightning heatmaps per-channel](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_256/st_movenet_lightning_a100_heatmaps_256_int8.tflite) | Int8 | 256x256x3 | custom ST | 62.36 % | |
| | [ST MoveNet Lightning heatmaps per-tensor ](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_192/st_movenet_lightning_a100_heatmaps_192_int8_per_tensor.tflite) | Int8 | 192x192x3 | custom ST | 55.84 % | |
| | [ST MoveNet Lightning heatmaps per-tensor ](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_224/st_movenet_lightning_a100_heatmaps_224_int8_per_tensor.tflite) | Int8 | 224x224x3 | custom ST | 58.95 % | |
| | [ST MoveNet Lightning heatmaps per-tensor ](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_custom_dataset/custom_coco_person_17kpts/st_movenet_lightning_a100_heatmaps_256/st_movenet_lightning_a100_heatmaps_256_int8_per_tensor.tflite) | Int8 | 256x256x3 | custom ST | 60.73 % | |
| | [ST MoveNet Lightning heatmaps per-channel](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_public_dataset/coco_person_17kpts/st_movenet_lightning_a100_heatmaps_192/st_movenet_lightning_a100_heatmaps_192_int8.tflite) | Int8 | 192x192x3 | COCO | 55.34 % | |
| | [ST MoveNet Lightning heatmaps per-channel](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_public_dataset/coco_person_17kpts/st_movenet_lightning_a100_heatmaps_224/st_movenet_lightning_a100_heatmaps_224_int8.tflite) | Int8 | 224x224x3 | COCO | 59.02 % | |
| | [ST MoveNet Lightning heatmaps per-channel](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_public_dataset/coco_person_17kpts/st_movenet_lightning_a100_heatmaps_256/st_movenet_lightning_a100_heatmaps_256_int8.tflite) | Int8 | 256x256x3 | COCO | 61.99 % | |
| | [ST MoveNet Lightning heatmaps per-tensor ](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_public_dataset/coco_person_17kpts/st_movenet_lightning_a100_heatmaps_192/st_movenet_lightning_a100_heatmaps_192_int8_per_tensor.tflite) | Int8 | 192x192x3 | COCO | 55.34 % | |
| | [ST MoveNet Lightning heatmaps per-tensor ](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_public_dataset/coco_person_17kpts/st_movenet_lightning_a100_heatmaps_224/st_movenet_lightning_a100_heatmaps_224_int8_per_tensor.tflite) | Int8 | 224x224x3 | COCO | 58.50 % | |
| | [ST MoveNet Lightning heatmaps per-tensor ](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_public_dataset/coco_person_17kpts/st_movenet_lightning_a100_heatmaps_256/st_movenet_lightning_a100_heatmaps_256_int8_per_tensor.tflite) | Int8 | 256x256x3 | COCO | 61.63 % | |
| | [MoveNet Lightning per-channel](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_a100_192/movenet_singlepose_lightning_a100_192_int8.tflite) | Int8 | 192x192x3 | custom Google | 54.12 % | |
| | [MoveNet Thunder per-channel](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_thunder_a100_256/movenet_singlepose_thunder_a100_256_int8.tflite) | Int8 | 256x256x3 | custom Google | 64.43 % | |
|
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|
|
| ## Integration in a simple example and other services support: |
|
|
| Please refer to the stm32ai-modelzoo-services GitHub [here](https://github.com/STMicroelectronics/stm32ai-modelzoo-services) |
|
|
|
|
| # References |
|
|
| <a id="1">[1]</a> |
| “Microsoft COCO: Common Objects in Context”. [Online]. Available: https://cocodataset.org/#download. |
| @article{DBLP:journals/corr/LinMBHPRDZ14, |
| author = {Tsung{-}Yi Lin and |
| Michael Maire and |
| Serge J. Belongie and |
| Lubomir D. Bourdev and |
| Ross B. Girshick and |
| James Hays and |
| Pietro Perona and |
| Deva Ramanan and |
| Piotr Doll{'{a} }r and |
| C. Lawrence Zitnick}, |
| title = {Microsoft {COCO:} Common Objects in Context}, |
| journal = {CoRR}, |
| volume = {abs/1405.0312}, |
| year = {2014}, |
| url = {http://arxiv.org/abs/1405.0312}, |
| archivePrefix = {arXiv}, |
| eprint = {1405.0312}, |
| timestamp = {Mon, 13 Aug 2018 16:48:13 +0200}, |
| biburl = {https://dblp.org/rec/bib/journals/corr/LinMBHPRDZ14}, |
| bibsource = {dblp computer science bibliography, https://dblp.org} |
| } |
