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hand_landmarks

Keypoint Detection
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Release AI-ModelZoo-4.0.0

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  1. README.md +7 -6
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@@ -57,11 +57,12 @@ With an image resolution of NxM with K keypoints to detect :
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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 |
 
 
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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) | STEdgeAI Core version |
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+ |----------|------------------|--------|-------------|------------------|------------------|---------------------|-------|-------------------------|
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+ | [handlandmarks](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/handlandmarks/custom_dataset_hands_21kpts/handlandmarks_full_224_int8.tflite) | custom_dataset_hands_21kpts | Int8 | 224x224x3 | STM32N6 | 1739.5 | 0.0 | 3283.38 | 3.0.0 |
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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 | STEdgeAI Core version |
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+ |--------|------------------|--------|-------------|------------------|------------------|---------------------|-------|-------------------------|
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+ | [handlandmarks](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/handlandmarks/custom_dataset_hands_21kpts/handlandmarks_full_224_int8.tflite) | custom_dataset_hands_21kpts | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 20.75 | 48.19 | 3.0.0 |
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