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--- |
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license: other |
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license_name: sla0044 |
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license_link: >- |
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https://github.com/STMicroelectronics/stm32aimodelzoo/pose_estimation/LICENSE.md |
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pipeline_tag: keypoint-detection |
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--- |
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# MoveNet quantized |
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## **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 | |
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|-------------------------|-----------------| |
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| Framework | TensorFlow Lite | |
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| Quantization | int8 | |
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| Provenance | https://www.kaggle.com/models/google/movenet |
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| 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 | |
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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, 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 | |
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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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| [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 | |
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| [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 | |
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| [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 | |
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| [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 | |
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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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| [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 | |
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| [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 | |
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| [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 | |
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| [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 | |
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### Reference **MPU** inference time based on COCO Person dataset (see Accuracy for details on dataset) |
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| Model | Format | Resolution | Quantization | Board | Execution Engine | Frequency | Inference time (ms) | %NPU | %GPU | %CPU | X-LINUX-AI version | Framework | |
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|--------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------|------------|---------------|-------------------|------------------|-----------|---------------------|-------|-------|------|--------------------|-----------------------| |
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| [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 | |
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| [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 | |
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| [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 | |
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| [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 | |
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| [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 | |
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| [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 | |
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| [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 | |
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| [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 | |
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| [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 |
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| [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 | |
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** **To get the most out of MP25 NPU hardware acceleration, please use per-tensor quantization** |
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### OKS on COCO Person dataset |
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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 | OKS | |
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|-------|--------|------------|----------------| |
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| [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 % | |
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| [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 % | |
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| [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 % | |
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| [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 % | |
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| [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 % | |
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| [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 % | |
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| [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 % | |
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| [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 % | |
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| [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% | |
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| [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% | |
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\* keypoints = 13 |
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## Integration in a simple example and other services support: |
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Please refer to the stm32ai-modelzoo-services GitHub [here](https://github.com/STMicroelectronics/stm32ai-modelzoo-services) |
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# References |
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<a id="1">[1]</a> |
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“Microsoft COCO: Common Objects in Context”. [Online]. Available: https://cocodataset.org/#download. |
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@article{DBLP:journals/corr/LinMBHPRDZ14, |
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author = {Tsung{-}Yi Lin and |
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Michael Maire and |
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Serge J. Belongie and |
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Lubomir D. Bourdev and |
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Ross B. Girshick and |
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James Hays and |
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Pietro Perona and |
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Deva Ramanan and |
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Piotr Doll{'{a} }r and |
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C. Lawrence Zitnick}, |
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title = {Microsoft {COCO:} Common Objects in Context}, |
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journal = {CoRR}, |
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volume = {abs/1405.0312}, |
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year = {2014}, |
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url = {http://arxiv.org/abs/1405.0312}, |
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archivePrefix = {arXiv}, |
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eprint = {1405.0312}, |
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timestamp = {Mon, 13 Aug 2018 16:48:13 +0200}, |
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biburl = {https://dblp.org/rec/bib/journals/corr/LinMBHPRDZ14}, |
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bibsource = {dblp computer science bibliography, https://dblp.org} |
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} |
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