--- license: other license_name: sla0044 license_link: >- https://github.com/STMicroelectronics/stm32aimodelzoo/pose_estimation/LICENSE.md pipeline_tag: keypoint-detection --- # MoveNet quantized ## **Use case** : `Pose estimation` # Model description MoveNet 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://www.kaggle.com/models/google/movenet | Paper | https://storage.googleapis.com/movenet/MoveNet.SinglePose%20Model%20Card.pdf | ## Networks inputs / outputs With an image resolution of NxM with K keypoints to detect : - For heatmaps models | Input Shape | Description | | ----- | ----------- | | (1, N, M, 3) | Single NxM RGB image with UINT8 values between 0 and 255 | | 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| - For the other models | 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 | |----------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_public_dataset/custom_dataset_person_13kpts/st_movenet_lightning_heatmaps_192/st_movenet_lightning_heatmaps_192_int8_pc.tflite) | COCO-Person | Int8 | 192x192x3 | STM32N6 | 1674 | 0.0 | 3036.17 | 10.0.0 | 2.0.0 | | [MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_192/movenet_lightning_heatmaps_192_int8_pc.tflite) | COCO-Person | Int8 | 192x192x3 | STM32N6 | 1674 | 0.0 | 3036.41 | 10.0.0 | 2.0.0 | | [MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_224/movenet_lightning_heatmaps_224_int8_pc.tflite) | COCO-Person | Int8 | 224x224x3 | STM32N6 | 2058 | 0.0 | 3088.56 | 10.0.0 | 2.0.0 | | [MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_256/movenet_lightning_heatmaps_256_int8_pc.tflite) | COCO-Person | Int8 | 256x256x3 | STM32N6 | 2360 | 0.0 | 3141.36 | 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 | |--------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------| | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_public_dataset/custom_dataset_person_13kpts/st_movenet_lightning_heatmaps_192/st_movenet_lightning_heatmaps_192_int8_pc.tflite) | COCO-Person | Int8 | 192x192x3 | STM32N6570-DK | NPU/MCU | 18.44 | 54.23 | 10.0.0 | 2.0.0 | | [MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_192/movenet_lightning_heatmaps_192_int8_pc.tflite) | COCO-Person | Int8 | 192x192x3 | STM32N6570-DK | NPU/MCU | 18.49 | 54.08 | 10.0.0 | 2.0.0 | | [MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_224/movenet_lightning_heatmaps_224_int8_pc.tflite) | COCO-Person | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 22.33 | 44.78 | 10.0.0 | 2.0.0 | | [MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_256/movenet_lightning_heatmaps_256_int8_pc.tflite) | COCO-Person | Int8 | 256x256x3 | STM32N6570-DK | NPU/MCU | 27.01 | 37.03 | 10.0.0 | 2.0.0 | ### Reference **MPU** inference time based on COCO Person dataset (see Accuracy for details on dataset) | Model | 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_public_dataset/custom_dataset_person_13kpts/st_movenet_lightning_heatmaps_192/st_movenet_lightning_heatmaps_192_int8_pc.tflite) | Int8 | 192x192x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 58.02 ms | 3.75 | 96.25 |0 | v5.0.0 | OpenVX | | [ST MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_public_dataset/custom_dataset_person_13kpts/st_movenet_lightning_heatmaps_192/st_movenet_lightning_heatmaps_192_int8_pt.tflite) | Int8 | 192x192x3 | per-tensor | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 7.93 ms | 84.89 | 15.11 |0 | v5.0.0 | OpenVX | | [MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_192/movenet_lightning_heatmaps_192_int8_pc.tflite) | Int8 | 192x192x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 58.17 ms | 3.80 | 96.20 |0 | v5.0.0 | OpenVX | | [MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_192/movenet_lightning_heatmaps_192_int8_pt.tflite) | Int8 | 192x192x3 | per-tensor | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 8.00 ms | 86.48 | 13.52 |0 | v5.0.0 | OpenVX | | [MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_224/movenet_lightning_heatmaps_224_int8_pc.tflite) | Int8 | 224x224x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 81.65 ms | 2.77 | 97.23 |0 | v5.0.0 | OpenVX | | [MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_224/movenet_lightning_heatmaps_224_int8_pt.tflite) | Int8 | 224x224x3 | per-tensor | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 11.55 ms | 87.04 | 12.96 |0 | v5.0.0 | OpenVX | | [MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_256/movenet_lightning_heatmaps_256_int8_pc.tflite) | Int8 | 256x256x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 70.57 ms | 3.74 | 96.26 |0 | v5.0.0 | OpenVX | | [MoveNet Lightning heatmaps](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_256/movenet_lightning_heatmaps_256_int8_pc.tflite) | Int8 | 256x256x3 | per-tensor | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 12.90 ms | 86.33 | 13.67 |0 | v5.0.0 | OpenVX | | [MoveNet Lightning](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_192/movenet_singlepose_lightning_192_int8.tflite) | Int8 | 192x192x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 66.97 ms | 6.72 | 93.28 |0 | v5.0.0 | OpenVX | [MoveNet Thunder](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_thunder_256/movenet_singlepose_thunder_256_int8.tflite) | Int8 | 256x256x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 187.1 ms | 3.96 | 96.04 |0 | v5.0.0 | OpenVX | ** **To get the most out of MP25 NPU hardware acceleration, please use per-tensor quantization** ### OKS on COCO Person dataset 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 | Model | Format | Resolution | OKS | |-------|--------|------------|----------------| | [ST MoveNet Lightning heatmaps per-channel](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_public_dataset/custom_dataset_person_13kpts/st_movenet_lightning_heatmaps_192/st_movenet_lightning_heatmaps_192_int8_pc.tflite) | Int8 | 192x192x3 | *52.1 % | | [ST MoveNet Lightning heatmaps per-tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/ST_pretrainedmodel_public_dataset/custom_dataset_person_13kpts/st_movenet_lightning_heatmaps_192/st_movenet_lightning_heatmaps_192_int8_pt.tflite) | Int8 | 192x192x3 | *39.31 % | | [MoveNet Lightning heatmaps per-channel](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_192/movenet_lightning_heatmaps_192_int8_pc.tflite) | Int8 | 192x192x3 | 54.01 % | | [MoveNet Lightning heatmaps per-tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_192/movenet_lightning_heatmaps_192_int8_pt.tflite) | Int8 | 192x192x3 | 48.49 % | | [MoveNet Lightning heatmaps per-channel](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_224/movenet_lightning_heatmaps_224_int8_pc.tflite) | Int8 | 224x224x3 | 57.07 % | | [MoveNet Lightning heatmaps per-tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_224/movenet_lightning_heatmaps_224_int8_pt.tflite) | Int8 | 224x224x3 | 50.93 % | | [MoveNet Lightning heatmaps per-channel](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_256/movenet_lightning_heatmaps_256_int8_pc.tflite) | Int8 | 256x256x3 | 58.58 % | | [MoveNet Lightning heatmaps per-tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_heatmaps_256/movenet_lightning_heatmaps_256_int8_pt.tflite) | Int8 | 256x256x3 | 52.86 % | | [MoveNet Lightning](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_lightning_192/movenet_singlepose_lightning_192_int8.tflite) | Int8 | 192x192x3 | 54.12% | | [MoveNet Thunder](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/movenet/Public_pretrainedmodel_custom_dataset/custom_dataset_person_17kpts/movenet_thunder_256/movenet_singlepose_thunder_256_int8.tflite) | Int8 | 256x256x3 | 64.43% | \* keypoints = 13 ## 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 [1] “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} }