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CNN2D-ST-HandPosture-model

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@@ -61,8 +61,8 @@ Measures are done with default STM32Cube.AI configuration with enabled input / o
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  | Model | Format | Input Shape | Series | Activation RAM (KiB) | Runtime RAM (KiB) | Weights Flash (KiB) | Code Flash (KiB) | Total RAM (KiB) | Total Flash (KiB) | STM32Cube.AI version |
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  |:-----------------:|:------:|:-----------:|:-------:|:--------------:|:-----------:|:-------------:|:----------:|:-----------:|:-----------:|:---------------------:|
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- | [CNN2D_ST_HandPosture](https://github.com/STMicroelectronics/stm32ai-modelzoo/ST_pretrainedmodel_custom_dataset/ST_VL53L8CX_handposture_dataset/CNN2D_ST_HandPosture_8classes/CNN2D_ST_HandPosture_8classes.h5) | FLOAT32 | 8 x 8 x 2 | STM32F4 | 1.07 | 2.08 | 10.75 | 14.37 | 3.15 | 25.12 | 10.0.0 |
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- | [CNN2D_ST_HandPosture](https://github.com/STMicroelectronics/stm32ai-modelzoo/ST_pretrainedmodel_custom_dataset/ST_VL53L5CX_handposture_dataset/CNN2D_ST_HandPosture_8classes/CNN2D_ST_HandPosture_8classes.h5) | FLOAT32 | 8 x 8 x 2 | STM32F4 | 1.07 | 2.08 | 10.75 | 14.37 | 3.15 | 25.12 | 10.0.0 |
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  ### Reference inference time based on ST_VL53LxCX_handposture_dataset (see Accuracy for details on dataset)
@@ -70,8 +70,8 @@ Measures are done with default STM32Cube.AI configuration with enabled input / o
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  | Model | Format | Resolution | Board | Frequency | Inference time (ms) | STM32Cube.AI version |
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  |:-----------------:|:------:|:----------:|:----------------:|:-------------:|:-------------------:|:---------------------:|
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- | [CNN2D_ST_HandPosture](https://github.com/STMicroelectronics/stm32ai-modelzoo/ST_pretrainedmodel_custom_dataset/ST_VL53L8CX_handposture_dataset/CNN2D_ST_HandPosture_8classes/CNN2D_ST_HandPosture_8classes.h5) | FLOAT32 | 8 x 8 x 2 | STM32F401 | 84 MHz | 1.54 ms | 10.0.0 |
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- | [CNN2D_ST_HandPosture](https://github.com/STMicroelectronics/stm32ai-modelzoo/ST_pretrainedmodel_custom_dataset/ST_VL53L5CX_handposture_dataset/CNN2D_ST_HandPosture_8classes/CNN2D_ST_HandPosture_8classes.h5) | FLOAT32 | 8 x 8 x 2 | STM32F401 | 84 MHz | 1.53 ms | 10.0.0 |
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  ### Accuracy with ST_VL53LxCX_handposture_dataset
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@@ -80,8 +80,8 @@ Number of classes: 8 [None, FlatHand, Like, Dislike, Fist, Love, BreakTime, Cros
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  | Model | Format | Resolution | Accuracy |
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  |:-----------------:|:------:|:----------:|:----------------:|
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- | [CNN2D_ST_HandPosture](https://github.com/STMicroelectronics/stm32ai-modelzoo/ST_pretrainedmodel_custom_dataset/ST_VL53L8CX_handposture_dataset/CNN2D_ST_HandPosture_8classes/CNN2D_ST_HandPosture_8classes.h5) | FLOAT32 | 8 x 8 x 2 | 99.43 % |
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- | [CNN2D_ST_HandPosture](https://github.com/STMicroelectronics/stm32ai-modelzoo/ST_pretrainedmodel_custom_dataset/ST_VL53L5CX_handposture_dataset/CNN2D_ST_HandPosture_8classes/CNN2D_ST_HandPosture_8classes.h5) | FLOAT32 | 8 x 8 x 2 | 97.17 % |
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  ## Retraining and Integration in a simple example:
 
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  | Model | Format | Input Shape | Series | Activation RAM (KiB) | Runtime RAM (KiB) | Weights Flash (KiB) | Code Flash (KiB) | Total RAM (KiB) | Total Flash (KiB) | STM32Cube.AI version |
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  |:-----------------:|:------:|:-----------:|:-------:|:--------------:|:-----------:|:-------------:|:----------:|:-----------:|:-----------:|:---------------------:|
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+ | [CNN2D_ST_HandPosture](https://github.com/STMicroelectronics/stm32ai-modelzoo/hand_posture/CNN2D_ST_HandPosture/ST_pretrainedmodel_custom_dataset/ST_VL53L8CX_handposture_dataset/CNN2D_ST_HandPosture_8classes/CNN2D_ST_HandPosture_8classes.h5) | FLOAT32 | 8 x 8 x 2 | STM32F4 | 1.07 | 2.08 | 10.75 | 14.37 | 3.15 | 25.12 | 10.0.0 |
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+ | [CNN2D_ST_HandPosture](https://github.com/STMicroelectronics/stm32ai-modelzoo/hand_posture/CNN2D_ST_HandPosture/ST_pretrainedmodel_custom_dataset/ST_VL53L5CX_handposture_dataset/CNN2D_ST_HandPosture_8classes/CNN2D_ST_HandPosture_8classes.h5) | FLOAT32 | 8 x 8 x 2 | STM32F4 | 1.07 | 2.08 | 10.75 | 14.37 | 3.15 | 25.12 | 10.0.0 |
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  ### Reference inference time based on ST_VL53LxCX_handposture_dataset (see Accuracy for details on dataset)
 
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  | Model | Format | Resolution | Board | Frequency | Inference time (ms) | STM32Cube.AI version |
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  |:-----------------:|:------:|:----------:|:----------------:|:-------------:|:-------------------:|:---------------------:|
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+ | [CNN2D_ST_HandPosture](https://github.com/STMicroelectronics/stm32ai-modelzoo/hand_posture/CNN2D_ST_HandPosture/ST_pretrainedmodel_custom_dataset/ST_VL53L8CX_handposture_dataset/CNN2D_ST_HandPosture_8classes/CNN2D_ST_HandPosture_8classes.h5) | FLOAT32 | 8 x 8 x 2 | STM32F401 | 84 MHz | 1.54 ms | 10.0.0 |
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+ | [CNN2D_ST_HandPosture](https://github.com/STMicroelectronics/stm32ai-modelzoo/hand_posture/CNN2D_ST_HandPosture/ST_pretrainedmodel_custom_dataset/ST_VL53L5CX_handposture_dataset/CNN2D_ST_HandPosture_8classes/CNN2D_ST_HandPosture_8classes.h5) | FLOAT32 | 8 x 8 x 2 | STM32F401 | 84 MHz | 1.53 ms | 10.0.0 |
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  ### Accuracy with ST_VL53LxCX_handposture_dataset
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  | Model | Format | Resolution | Accuracy |
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  |:-----------------:|:------:|:----------:|:----------------:|
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+ | [CNN2D_ST_HandPosture](https://github.com/STMicroelectronics/stm32ai-modelzoo/hand_posture/CNN2D_ST_HandPosture/ST_pretrainedmodel_custom_dataset/ST_VL53L8CX_handposture_dataset/CNN2D_ST_HandPosture_8classes/CNN2D_ST_HandPosture_8classes.h5) | FLOAT32 | 8 x 8 x 2 | 99.43 % |
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+ | [CNN2D_ST_HandPosture](https://github.com/STMicroelectronics/stm32ai-modelzoo/hand_posture/CNN2D_ST_HandPosture/ST_pretrainedmodel_custom_dataset/ST_VL53L5CX_handposture_dataset/CNN2D_ST_HandPosture_8classes/CNN2D_ST_HandPosture_8classes.h5) | FLOAT32 | 8 x 8 x 2 | 97.17 % |
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  ## Retraining and Integration in a simple example: