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mobilenetv1

Image Classification
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@@ -99,13 +99,13 @@ For an image resolution of NxM and P classes
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  | Model | Format | Resolution | Series | Activation RAM | Runtime RAM | Weights Flash | Code Flash | Total RAM | Total Flash | STM32Cube.AI version |
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  |--------------------------------------------------------------------------------------------------------------------------------------|--------|------------|---------|----------------|-------------|---------------|------------|-------------|-------------|-----------------------|
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- | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft_int8.tflite) | Int8 | 224x224x3 | STM32H7 | 272.96 KiB | 16.38 KiB | 214.69 KiB | 68.05 KiB | 289.34 KiB | 282.74 KiB | 10.0.0 |
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- | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft_int8.tflite) | Int8 | 224x224x3 | STM32H7 | 449.58 KiB | 16.38 KiB | 812.61 KiB | 81.46 KiB | 465.96 KiB | 894.02 KiB | 10.0.0 |
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- | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_fft/mobilenet_v1_0.25_96_fft_int8.tflite) | Int8 | 96x96x3 | STM32H7 | 66.96 KiB | 16.33 KiB | 214.69 KiB | 68 KiB | 83.29 KiB | 282.69 KiB | 10.0.0 |
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- | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_grayscale_tfs/mobilenet_v1_0.25_96_grayscale_tfs_int8.tflite) | Int8 | 96x96x1 | STM32H7 | 52.8 KiB | 16.33 KiB | 214.55 KiB | 70.27 KiB | 69.13 KiB | 284.82 KiB | 10.0.0 |
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- | [MobileNet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_0.25_224/mobilenet_v1_0.25_224_int8.tflite) | Int8 | 224x224x3 | STM32H7 | 272.96 KiB | 16.43 KiB | 467.33 KiB | 70.02 KiB | 283.63 KiB | 537.35 KiB | 10.0.0 |
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- | [MobileNet v1 0.5](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_0.5_224/mobilenet_v1_0.5_224_int8.tflite) | Int8 | 224x224x3 | STM32H7 | 431.07 KiB | 16.43 KiB | 1314 KiB | 83.38 KiB | 447.5 KiB | 1397.38 KiB | 10.0.0 |
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- | [MobileNet v1 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_1.0_224/mobilenet_v1_1.0_224_int8.tflite) | Int8 | 224x224x3 | STM32H7 | 1331.13 KiB | 16.48 KiB | 4157.09 KiB | 110.11 KiB | 1347.61 KiB | 4267.2 KiB | 10.0.0 |
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  ### Reference **MCU** inference time based on Flowers dataset and ImageNet dataset (see Accuracy for details on dataset)
@@ -113,30 +113,30 @@ For an image resolution of NxM and P classes
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  | Model | Format | Resolution | Board | Execution Engine | Frequency | Inference time (ms) | STM32Cube.AI version |
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  |-------------------|--------|------------|------------------|------------------|-----------|------------------|-----------------------|
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- | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft_int8.tflite) | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 163.78 ms | 10.0.0 |
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- | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft_int8.tflite) | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 485.79 ms | 10.0.0 |
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- | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_fft/mobilenet_v1_0.25_96_fft_int8.tflite) | Int8 | 96x96x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 29.94 ms | 10.0.0 |
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- | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_grayscale_tfs/mobilenet_v1_0.25_96_grayscale_tfs_int8.tflite) | Int8 | 96x96x1 | STM32H747I-DISCO | 1 CPU | 400 MHz | 28.34 ms | 10.0.0 |
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- | [MobileNet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_0.25_224/mobilenet_v1_0.25_224_int8.tflite) | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 166.75 ms | 10.0.0 |
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- | [MobileNet v1 0.5](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_0.5_224/mobilenet_v1_0.5_224_int8.tflite) | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 504.37 ms | 10.0.0 |
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- | [MobileNet v1 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_1.0_224/mobilenet_v1_1.0_224_int8.tflite) | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 1641.84 ms | 10.0.0 |
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  ### Reference **MPU** inference time based on Flowers 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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- | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft_int8.tflite) | Int8 | 224x224x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 14.29 ms | 6.04 | 93.96 | 0 | v5.1.0 | OpenVX |
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- | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft_int8.tflite) | Int8 | 224x224x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 32.74 ms | 3.41 | 96.59 | 0 | v5.1.0 | OpenVX |
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- | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_fft/mobilenet_v1_0.25_96_fft_int8.tflite) | Int8 | 96x96x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 3.740 ms | 14.20 | 85.80 | 0 | v5.1.0 | OpenVX |
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- | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_grayscale_tfs/mobilenet_v1_0.25_96_grayscale_tfs_int8.tflite) | Int8 | 96x96x1 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 3.68 ms | 11.47 | 88.53 | 0 | v5.1.0 | OpenVX |
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- | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft_int8.tflite) | Int8 | 224x224x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 33.97 ms | NA | NA | 100 | v5.1.0 | TensorFlowLite 2.11.0 |
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- | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft_int8.tflite) | Int8 | 224x224x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 91.42 ms | NA | NA | 100 | v5.1.0 | TensorFlowLite 2.11.0 |
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- | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_fft/mobilenet_v1_0.25_96_fft_int8.tflite) | Int8 | 96x96x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 6.40 ms | NA | NA | 100 | v5.1.0 | TensorFlowLite 2.11.0 |
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- | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_grayscale_tfs/mobilenet_v1_0.25_96_grayscale_tfs_int8.tflite) | Int8 | 96x96x1 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 5.83 ms | NA | NA | 100 | v5.1.0 | TensorFlowLite 2.11.0 |
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- |[MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft_int8.tflite) | Int8 | 224x224x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 52.51 ms | NA | NA | 100 | v5.1.0 | TensorFlowLite 2.11.0 |
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- |[MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft_int8.tflite) | Int8 | 224x224x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 145.4 ms | NA | NA | 100 | v5.1.0 | TensorFlowLite 2.11.0 |
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- |[MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_fft/mobilenet_v1_0.25_96_fft_int8.tflite) | Int8 | 96x96x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 9.75 ms | NA | NA | 100 | v5.1.0 | TensorFlowLite 2.11.0 |
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- |[MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_grayscale_tfs/mobilenet_v1_0.25_96_grayscale_tfs_int8.tflite) | Int8 | 96x96x1 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 9.01 ms | NA | NA | 100 | v5.1.0 | TensorFlowLite 2.11.0 |
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  ** **To get the most out of MP25 NPU hardware acceleration, please use per-tensor quantization**
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@@ -147,22 +147,22 @@ Dataset details: [link](http://download.tensorflow.org/example_images/flower_pho
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  | Model | Format | Resolution | Top 1 Accuracy |
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  |-------|--------|------------|----------------|
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- | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_tfs/mobilenet_v1_0.25_224_tfs.h5) | Float | 224x224x3 | 88.83 % |
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- | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_tfs/mobilenet_v1_0.25_224_tfs_int8.tflite) | Int8 | 224x224x3 | 89.37 % |
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- | [MobileNet v1 0.25 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_tl/mobilenet_v1_0.25_224_tl.h5) | Float | 224x224x3 | 85.83 % |
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- | [MobileNet v1 0.25 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_tl/mobilenet_v1_0.25_224_tl_int8.tflite) | Int8 | 224x224x3 | 83.24 % |
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- | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft.h5) | Float | 224x224x3 | 93.05 % |
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- | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft_int8.tflite) | Int8 | 224x224x3 | 92.1 % |
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- | [MobileNet v1 0.5 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_tfs/mobilenet_v1_0.5_224_tfs.h5) | Float | 224x224x3 | 92.1 % |
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- | [MobileNet v1 0.5 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_tfs/mobilenet_v1_0.5_224_tfs_int8.tflite) | Int8 | 224x224x3 | 91.55 % |
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- | [MobileNet v1 0.5 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_tl/mobilenet_v1_0.5_224_tl.h5) | Float | 224x224x3 | 88.56 % |
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- | [MobileNet v1 0.5 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_tl/mobilenet_v1_0.5_224_tl_int8.tflite) | Int8 | 224x224x3 | 87.74 % |
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- | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft.h5) | Float | 224x224x3 | 95.1 % |
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- | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft_int8.tflite) | Int8 | 224x224x3 | 94.41 % |
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- | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_fft/mobilenet_v1_0.25_96_fft.h5) | Float | 96x96x3 | 87.47 % |
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- | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_fft/mobilenet_v1_0.25_96_fft_int8.tflite) | Int8 | 96x96x3 | 87.06 % |
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- | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_grayscale_tfs/mobilenet_v1_0.25_96_grayscale_tfs.h5) | Float | 96x96x1 | 74.93 % |
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- | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_grayscale_tfs/mobilenet_v1_0.25_96_grayscale_tfs_int8.tflite) | Int8 | 96x96x1 | 74.93 % |
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@@ -173,18 +173,18 @@ Dataset details: [link](https://data.mendeley.com/datasets/tywbtsjrjv/1), Licens
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  | Model | Format | Resolution | Top 1 Accuracy |
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  |-------|--------|------------|----------------|
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- | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.25_224_tfs/mobilenet_v1_0.25_224_tfs.h5) | Float | 224x224x3 | 99.92 % |
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- | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.25_224_tfs/mobilenet_v1_0.25_224_tfs_int8.tflite) | Int8 | 224x224x3 | 99.92 % |
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- | [MobileNet v1 0.25 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.25_224_tl/mobilenet_v1_0.25_224_tl.h5) | Float | 224x224x3 | 85.38 % |
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- | [MobileNet v1 0.25 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.25_224_tl/mobilenet_v1_0.25_224_tl_int8.tflite) | Int8 | 224x224x3 | 83.7 % |
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- | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft.h5) | Float | 224x224x3 | 99.95 % |
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- | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft_int8.tflite) | Int8 | 224x224x3 | 99.82 % |
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- | [MobileNet v1 0.5 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.5_224_tfs/mobilenet_v1_0.5_224_tfs.h5) | Float | 224x224x3 | 99.9 % |
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- | [MobileNet v1 0.5 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.5_224_tfs/mobilenet_v1_0.5_224_tfs_int8.tflite) | Int8 | 224x224x3 | 99.83 % |
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- | [MobileNet v1 0.5 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.5_224_tl/mobilenet_v1_0.5_224_tl.h5) | Float | 224x224x3 | 93.05 % |
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- | [MobileNet v1 0.5 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.5_224_tl/mobilenet_v1_0.5_224_tl_int8.tflite) | Int8 | 224x224x3 | 92.7 % |
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- | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft.h5) | Float | 224x224x3 | 99.94 % |
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- | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft_int8.tflite) | Int8 | 224x224x3 | 99.85 % |
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@@ -194,20 +194,20 @@ Dataset details: [link](https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-1
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  | Model | Format | Resolution | Top 1 Accuracy |
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  |-------|--------|------------|----------------|
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- | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.25_224_tfs/mobilenet_v1_0.25_224_tfs.h5) | Float | 224x224x3 | 72.16 % |
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- | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.25_224_tfs/mobilenet_v1_0.25_224_tfs_int8.tflite) | Int8 | 224x224x3 | 71.13 % |
199
- | [MobileNet v1 0.25 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.25_224_tl/mobilenet_v1_0.25_224_tl.h5) | Float | 224x224x3 | 43.21 % |
200
- | [MobileNet v1 0.25 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.25_224_tl/mobilenet_v1_0.25_224_tl_int8.tflite) | Int8 | 224x224x3 | 39.89 % |
201
- | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft.h5) | Float | 224x224x3 | 72.36 % |
202
- | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft_int8.tflite) | Int8 | 224x224x3 | 69.52 % |
203
- | [MobileNet v1 0.5 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.5_224_tfs/mobilenet_v1_0.5_224_tfs.h5) | Float | 224x224x3 | 76.97 % |
204
- | [MobileNet v1 0.5 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.5_224_tfs/mobilenet_v1_0.5_224_tfs_int8.tflite) | Int8 | 224x224x3 | 76.37 % |
205
- | [MobileNet v1 0.5 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.5_224_tl/mobilenet_v1_0.5_224_tl.h5) | Float | 224x224x3 | 48.78 % |
206
- | [MobileNet v1 0.5 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.5_224_tl/mobilenet_v1_0.5_224_tl_int8.tflite) | Int8 | 224x224x3 | 45.89 % |
207
- | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft.h5) | Float | 224x224x3 | 76.72 % |
208
- | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft_int8.tflite) | Int8 | 224x224x3 | 74.82 % |
209
- | [MobileNet v1 1.0 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_1.0_224_fft/mobilenet_v1_1.0_224_fft.h5) | Float | 224x224x3 | 80.38 % |
210
- | [MobileNet v1 1.0 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_1.0_224_fft/mobilenet_v1_1.0_224_fft_int8.tflite) | Int8 | 224x224x3 | 79.43 % |
211
 
212
 
213
  ### Accuracy with ImageNet dataset
@@ -219,12 +219,12 @@ For the sake of simplicity, the accuracy reported here was estimated on the 5000
219
 
220
  |model | Format | Resolution | Top 1 Accuracy |
221
  |---------|--------|------------|----------------|
222
- | [MobileNet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_0.25_224/mobilenet_v1_0.25_224.h5) | Float | 224x224x3 | 48.96 % |
223
- | [MobileNet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_0.25_224/mobilenet_v1_0.25_224_int8.tflite) | Int8 | 224x224x3 | 46.34 % |
224
- | [MobileNet v1 0.5](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_0.5_224/mobilenet_v1_0.5_224.h5) | Float | 224x224x3 | 62.11 % |
225
- | [MobileNet v1 0.5](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_0.5_224/mobilenet_v1_0.5_224_int8.tflite) | Int8 | 224x224x3 | 59.92 % |
226
- | [MobileNet v1 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_1.0_224/mobilenet_v1_1.0_224.h5) | Float | 224x224x3 | 69.52 % |
227
- | [MobileNet v1 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_1.0_224/mobilenet_v1_1.0_224_int8.tflite) | Int8 | 224x224x3 | 68.64 % |
228
 
229
 
230
 
 
99
 
100
  | Model | Format | Resolution | Series | Activation RAM | Runtime RAM | Weights Flash | Code Flash | Total RAM | Total Flash | STM32Cube.AI version |
101
  |--------------------------------------------------------------------------------------------------------------------------------------|--------|------------|---------|----------------|-------------|---------------|------------|-------------|-------------|-----------------------|
102
+ | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft_int8.tflite) | Int8 | 224x224x3 | STM32H7 | 272.96 KiB | 16.38 KiB | 214.69 KiB | 68.05 KiB | 289.34 KiB | 282.74 KiB | 10.0.0 |
103
+ | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft_int8.tflite) | Int8 | 224x224x3 | STM32H7 | 449.58 KiB | 16.38 KiB | 812.61 KiB | 81.46 KiB | 465.96 KiB | 894.02 KiB | 10.0.0 |
104
+ | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_fft/mobilenet_v1_0.25_96_fft_int8.tflite) | Int8 | 96x96x3 | STM32H7 | 66.96 KiB | 16.33 KiB | 214.69 KiB | 68 KiB | 83.29 KiB | 282.69 KiB | 10.0.0 |
105
+ | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_grayscale_tfs/mobilenet_v1_0.25_96_grayscale_tfs_int8.tflite) | Int8 | 96x96x1 | STM32H7 | 52.8 KiB | 16.33 KiB | 214.55 KiB | 70.27 KiB | 69.13 KiB | 284.82 KiB | 10.0.0 |
106
+ | [MobileNet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_0.25_224/mobilenet_v1_0.25_224_int8.tflite) | Int8 | 224x224x3 | STM32H7 | 272.96 KiB | 16.43 KiB | 467.33 KiB | 70.02 KiB | 283.63 KiB | 537.35 KiB | 10.0.0 |
107
+ | [MobileNet v1 0.5](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_0.5_224/mobilenet_v1_0.5_224_int8.tflite) | Int8 | 224x224x3 | STM32H7 | 431.07 KiB | 16.43 KiB | 1314 KiB | 83.38 KiB | 447.5 KiB | 1397.38 KiB | 10.0.0 |
108
+ | [MobileNet v1 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_1.0_224/mobilenet_v1_1.0_224_int8.tflite) | Int8 | 224x224x3 | STM32H7 | 1331.13 KiB | 16.48 KiB | 4157.09 KiB | 110.11 KiB | 1347.61 KiB | 4267.2 KiB | 10.0.0 |
109
 
110
 
111
  ### Reference **MCU** inference time based on Flowers dataset and ImageNet dataset (see Accuracy for details on dataset)
 
113
 
114
  | Model | Format | Resolution | Board | Execution Engine | Frequency | Inference time (ms) | STM32Cube.AI version |
115
  |-------------------|--------|------------|------------------|------------------|-----------|------------------|-----------------------|
116
+ | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft_int8.tflite) | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 163.78 ms | 10.0.0 |
117
+ | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft_int8.tflite) | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 485.79 ms | 10.0.0 |
118
+ | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_fft/mobilenet_v1_0.25_96_fft_int8.tflite) | Int8 | 96x96x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 29.94 ms | 10.0.0 |
119
+ | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_grayscale_tfs/mobilenet_v1_0.25_96_grayscale_tfs_int8.tflite) | Int8 | 96x96x1 | STM32H747I-DISCO | 1 CPU | 400 MHz | 28.34 ms | 10.0.0 |
120
+ | [MobileNet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_0.25_224/mobilenet_v1_0.25_224_int8.tflite) | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 166.75 ms | 10.0.0 |
121
+ | [MobileNet v1 0.5](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_0.5_224/mobilenet_v1_0.5_224_int8.tflite) | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 504.37 ms | 10.0.0 |
122
+ | [MobileNet v1 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_1.0_224/mobilenet_v1_1.0_224_int8.tflite) | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 1641.84 ms | 10.0.0 |
123
 
124
 
125
  ### Reference **MPU** inference time based on Flowers dataset (see Accuracy for details on dataset)
126
  | Model | Format | Resolution | Quantization | Board | Execution Engine | Frequency | Inference time (ms) | %NPU | %GPU | %CPU | X-LINUX-AI version | Framework |
127
  |-----------------------|--------|------------|---------------|-------------------|------------------|-----------|---------------------|-------|-------|------|--------------------|-----------------------|
128
+ | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft_int8.tflite) | Int8 | 224x224x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 14.29 ms | 6.04 | 93.96 | 0 | v5.1.0 | OpenVX |
129
+ | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft_int8.tflite) | Int8 | 224x224x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 32.74 ms | 3.41 | 96.59 | 0 | v5.1.0 | OpenVX |
130
+ | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_fft/mobilenet_v1_0.25_96_fft_int8.tflite) | Int8 | 96x96x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 3.740 ms | 14.20 | 85.80 | 0 | v5.1.0 | OpenVX |
131
+ | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_grayscale_tfs/mobilenet_v1_0.25_96_grayscale_tfs_int8.tflite) | Int8 | 96x96x1 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 3.68 ms | 11.47 | 88.53 | 0 | v5.1.0 | OpenVX |
132
+ | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft_int8.tflite) | Int8 | 224x224x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 33.97 ms | NA | NA | 100 | v5.1.0 | TensorFlowLite 2.11.0 |
133
+ | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft_int8.tflite) | Int8 | 224x224x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 91.42 ms | NA | NA | 100 | v5.1.0 | TensorFlowLite 2.11.0 |
134
+ | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_fft/mobilenet_v1_0.25_96_fft_int8.tflite) | Int8 | 96x96x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 6.40 ms | NA | NA | 100 | v5.1.0 | TensorFlowLite 2.11.0 |
135
+ | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_grayscale_tfs/mobilenet_v1_0.25_96_grayscale_tfs_int8.tflite) | Int8 | 96x96x1 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 5.83 ms | NA | NA | 100 | v5.1.0 | TensorFlowLite 2.11.0 |
136
+ |[MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft_int8.tflite) | Int8 | 224x224x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 52.51 ms | NA | NA | 100 | v5.1.0 | TensorFlowLite 2.11.0 |
137
+ |[MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft_int8.tflite) | Int8 | 224x224x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 145.4 ms | NA | NA | 100 | v5.1.0 | TensorFlowLite 2.11.0 |
138
+ |[MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_fft/mobilenet_v1_0.25_96_fft_int8.tflite) | Int8 | 96x96x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 9.75 ms | NA | NA | 100 | v5.1.0 | TensorFlowLite 2.11.0 |
139
+ |[MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_grayscale_tfs/mobilenet_v1_0.25_96_grayscale_tfs_int8.tflite) | Int8 | 96x96x1 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 9.01 ms | NA | NA | 100 | v5.1.0 | TensorFlowLite 2.11.0 |
140
 
141
  ** **To get the most out of MP25 NPU hardware acceleration, please use per-tensor quantization**
142
 
 
147
 
148
  | Model | Format | Resolution | Top 1 Accuracy |
149
  |-------|--------|------------|----------------|
150
+ | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_tfs/mobilenet_v1_0.25_224_tfs.h5) | Float | 224x224x3 | 88.83 % |
151
+ | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_tfs/mobilenet_v1_0.25_224_tfs_int8.tflite) | Int8 | 224x224x3 | 89.37 % |
152
+ | [MobileNet v1 0.25 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_tl/mobilenet_v1_0.25_224_tl.h5) | Float | 224x224x3 | 85.83 % |
153
+ | [MobileNet v1 0.25 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_tl/mobilenet_v1_0.25_224_tl_int8.tflite) | Int8 | 224x224x3 | 83.24 % |
154
+ | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft.h5) | Float | 224x224x3 | 93.05 % |
155
+ | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft_int8.tflite) | Int8 | 224x224x3 | 92.1 % |
156
+ | [MobileNet v1 0.5 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_tfs/mobilenet_v1_0.5_224_tfs.h5) | Float | 224x224x3 | 92.1 % |
157
+ | [MobileNet v1 0.5 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_tfs/mobilenet_v1_0.5_224_tfs_int8.tflite) | Int8 | 224x224x3 | 91.55 % |
158
+ | [MobileNet v1 0.5 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_tl/mobilenet_v1_0.5_224_tl.h5) | Float | 224x224x3 | 88.56 % |
159
+ | [MobileNet v1 0.5 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_tl/mobilenet_v1_0.5_224_tl_int8.tflite) | Int8 | 224x224x3 | 87.74 % |
160
+ | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft.h5) | Float | 224x224x3 | 95.1 % |
161
+ | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft_int8.tflite) | Int8 | 224x224x3 | 94.41 % |
162
+ | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_fft/mobilenet_v1_0.25_96_fft.h5) | Float | 96x96x3 | 87.47 % |
163
+ | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_fft/mobilenet_v1_0.25_96_fft_int8.tflite) | Int8 | 96x96x3 | 87.06 % |
164
+ | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_grayscale_tfs/mobilenet_v1_0.25_96_grayscale_tfs.h5) | Float | 96x96x1 | 74.93 % |
165
+ | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v1_0.25_96_grayscale_tfs/mobilenet_v1_0.25_96_grayscale_tfs_int8.tflite) | Int8 | 96x96x1 | 74.93 % |
166
 
167
 
168
 
 
173
 
174
  | Model | Format | Resolution | Top 1 Accuracy |
175
  |-------|--------|------------|----------------|
176
+ | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.25_224_tfs/mobilenet_v1_0.25_224_tfs.h5) | Float | 224x224x3 | 99.92 % |
177
+ | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.25_224_tfs/mobilenet_v1_0.25_224_tfs_int8.tflite) | Int8 | 224x224x3 | 99.92 % |
178
+ | [MobileNet v1 0.25 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.25_224_tl/mobilenet_v1_0.25_224_tl.h5) | Float | 224x224x3 | 85.38 % |
179
+ | [MobileNet v1 0.25 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.25_224_tl/mobilenet_v1_0.25_224_tl_int8.tflite) | Int8 | 224x224x3 | 83.7 % |
180
+ | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft.h5) | Float | 224x224x3 | 99.95 % |
181
+ | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft_int8.tflite) | Int8 | 224x224x3 | 99.82 % |
182
+ | [MobileNet v1 0.5 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.5_224_tfs/mobilenet_v1_0.5_224_tfs.h5) | Float | 224x224x3 | 99.9 % |
183
+ | [MobileNet v1 0.5 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.5_224_tfs/mobilenet_v1_0.5_224_tfs_int8.tflite) | Int8 | 224x224x3 | 99.83 % |
184
+ | [MobileNet v1 0.5 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.5_224_tl/mobilenet_v1_0.5_224_tl.h5) | Float | 224x224x3 | 93.05 % |
185
+ | [MobileNet v1 0.5 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.5_224_tl/mobilenet_v1_0.5_224_tl_int8.tflite) | Int8 | 224x224x3 | 92.7 % |
186
+ | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft.h5) | Float | 224x224x3 | 99.94 % |
187
+ | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft_int8.tflite) | Int8 | 224x224x3 | 99.85 % |
188
 
189
 
190
  ### Accuracy with Food-101 dataset
 
194
 
195
  | Model | Format | Resolution | Top 1 Accuracy |
196
  |-------|--------|------------|----------------|
197
+ | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.25_224_tfs/mobilenet_v1_0.25_224_tfs.h5) | Float | 224x224x3 | 72.16 % |
198
+ | [MobileNet v1 0.25 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.25_224_tfs/mobilenet_v1_0.25_224_tfs_int8.tflite) | Int8 | 224x224x3 | 71.13 % |
199
+ | [MobileNet v1 0.25 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.25_224_tl/mobilenet_v1_0.25_224_tl.h5) | Float | 224x224x3 | 43.21 % |
200
+ | [MobileNet v1 0.25 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.25_224_tl/mobilenet_v1_0.25_224_tl_int8.tflite) | Int8 | 224x224x3 | 39.89 % |
201
+ | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft.h5) | Float | 224x224x3 | 72.36 % |
202
+ | [MobileNet v1 0.25 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.25_224_fft/mobilenet_v1_0.25_224_fft_int8.tflite) | Int8 | 224x224x3 | 69.52 % |
203
+ | [MobileNet v1 0.5 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.5_224_tfs/mobilenet_v1_0.5_224_tfs.h5) | Float | 224x224x3 | 76.97 % |
204
+ | [MobileNet v1 0.5 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.5_224_tfs/mobilenet_v1_0.5_224_tfs_int8.tflite) | Int8 | 224x224x3 | 76.37 % |
205
+ | [MobileNet v1 0.5 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.5_224_tl/mobilenet_v1_0.5_224_tl.h5) | Float | 224x224x3 | 48.78 % |
206
+ | [MobileNet v1 0.5 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.5_224_tl/mobilenet_v1_0.5_224_tl_int8.tflite) | Int8 | 224x224x3 | 45.89 % |
207
+ | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft.h5) | Float | 224x224x3 | 76.72 % |
208
+ | [MobileNet v1 0.5 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_0.5_224_fft/mobilenet_v1_0.5_224_fft_int8.tflite) | Int8 | 224x224x3 | 74.82 % |
209
+ | [MobileNet v1 1.0 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_1.0_224_fft/mobilenet_v1_1.0_224_fft.h5) | Float | 224x224x3 | 80.38 % |
210
+ | [MobileNet v1 1.0 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v1_1.0_224_fft/mobilenet_v1_1.0_224_fft_int8.tflite) | Int8 | 224x224x3 | 79.43 % |
211
 
212
 
213
  ### Accuracy with ImageNet dataset
 
219
 
220
  |model | Format | Resolution | Top 1 Accuracy |
221
  |---------|--------|------------|----------------|
222
+ | [MobileNet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_0.25_224/mobilenet_v1_0.25_224.h5) | Float | 224x224x3 | 48.96 % |
223
+ | [MobileNet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_0.25_224/mobilenet_v1_0.25_224_int8.tflite) | Int8 | 224x224x3 | 46.34 % |
224
+ | [MobileNet v1 0.5](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_0.5_224/mobilenet_v1_0.5_224.h5) | Float | 224x224x3 | 62.11 % |
225
+ | [MobileNet v1 0.5](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_0.5_224/mobilenet_v1_0.5_224_int8.tflite) | Int8 | 224x224x3 | 59.92 % |
226
+ | [MobileNet v1 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_1.0_224/mobilenet_v1_1.0_224.h5) | Float | 224x224x3 | 69.52 % |
227
+ | [MobileNet v1 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/blob/main/image_classification/mobilenetv1/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v1_1.0_224/mobilenet_v1_1.0_224_int8.tflite) | Int8 | 224x224x3 | 68.64 % |
228
 
229
 
230