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mobilenetv2

Image Classification
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@@ -2,7 +2,7 @@
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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/stm32ai-modelzoo/image_classification/LICENSE.md
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  pipeline_tag: image-classification
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  ---
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  # MobileNet v2
@@ -83,66 +83,66 @@ For an image resolution of NxM and P classes
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  ### Reference **NPU** memory footprint on food-101 and ImageNet dataset (see Accuracy for details on dataset)
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  |Model | Dataset | Format | Resolution | Series | Internal RAM | External RAM | Weights Flash | STM32Cube.AI version | STEdgeAI Core version |
85
  |----------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
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- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | food-101 | Int8 | 128x128x3 | STM32N6 | 240 | 0.0 | 715.67 | 10.0.0 | 2.0.0 |
87
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | food-101 | Int8 | 224x224x3 | STM32N6 | 980 | 0.0 | 730.7 | 10.0.0 | 2.0.0 |
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- | [MobileNet v2 1.0 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_1.0_224_fft/mobilenet_v2_1.0_224_fft_int8.tflite) | food-101 | Int8 | 224x224x3 | STM32N6 | 2058 | 0.0 | 3110.05 | 10.0.0 | 2.0.0 |
89
  | [MobileNet v2 0.35 fft](ST_pretrainedmodel_public_dataset/person/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Person | Int8 | 128x128x3 | STM32N6 | 240 | 0.0 | 589.45 | 10.0.0 | 2.0.0 |
90
- | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_128/mobilenet_v2_0.35_128_int8.tflite) | ImageNet | Int8 | 128x128x3 | STM32N6 | 240 | 0.0 | 1840.94 | 10.0.0 | 2.0.0 |
91
- | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_224/mobilenet_v2_0.35_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32N6 | 980 | 0.0 | 1855.97 | 10.0.0 | 2.0.0 |
92
- | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32N6 | 2058 | 0.0 | 4235.31 | 10.0.0 | 2.0.0 |
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- | [MobileNet v2 1.4](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.4_224/mobilenet_v2_1.4_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32N6 | 2361 | 0.0 | 7315.69 | 10.0.0 | 2.0.0 |
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95
 
96
  ### Reference **NPU** inference time on food-101 and ImageNet 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 |
98
  |--------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
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- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | food-101 | Int8 | 128x128x3 | STM32N6570-DK | NPU/MCU | 3.33 | 300.30 | 10.0.0 | 2.0.0 |
100
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | food-101 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 6.12 | 163.40 | 10.0.0 | 2.0.0 |
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- | [MobileNet v2 1.0 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_1.0_224_fft/mobilenet_v2_1.0_224_fft_int8.tflite) | food-101 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 18.08 | 55.32 | 10.0.0 | 2.0.0 |
102
  | [MobileNet v2 0.35 fft](ST_pretrainedmodel_public_dataset/person/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Person | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 2.99 | 334.45 | 10.0.0 | 2.0.0 |
103
- | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_128/mobilenet_v2_0.35_128_int8.tflite) | ImageNet | Int8 | 128x128x3 | STM32N6570-DK | NPU/MCU | 6.35 | 157.48 | 10.0.0 | 2.0.0 |
104
- | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_224/mobilenet_v2_0.35_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 9.14 | 109.40 | 10.0.0 | 2.0.0 |
105
- | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 21.08 | 47.44 | 10.0.0 | 2.0.0 |
106
- | [MobileNet v2 1.4](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.4_224/mobilenet_v2_1.4_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 35.34 | 28.30 | 10.0.0 | 2.0.0 |
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108
 
109
  ### Reference **MCU** memory footprint based on Flowers and ImageNet dataset (see Accuracy for details on dataset)
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111
  | Model | Dataset | 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 v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Flowers | Int8 | 128x128x3 | STM32H7 | 237.32 KiB | 30.14 KiB | 406.86 KiB | 108.29 KiB | 267.46 KiB | 515.15 KiB | 10.0.0 |
114
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | Flowers | Int8 | 224x224x3 | STM32H7 | 832.64 KiB | 30.19 KiB | 406.86 KiB | 108.40 KiB | 862.83 KiB | 515.26 KiB | 10.0.0 |
115
- | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_128/mobilenet_v2_0.35_128_int8.tflite) | ImageNet | Int8 | 128x128x3 | STM32H7 | 237.32 KiB | 30.14 KiB | 1654.5 KiB KiB | 108.29 KiB | 267.46 KiB | 1762.79 KiB | 10.0.0 |
116
- | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_224/mobilenet_v2_0.35_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32H7 | 832.64 KiB | 30.19 KiB | 1654.5 KiB | 108.40 KiB | 862.83 KiB | 1762.9 KiB | 10.0.0 |
117
- | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32H7 | 1727.02 KiB | 30.19 KiB | 3458.97 KiB | 157.37 KiB | 1757.21 KiB | 3616.34 KiB | 10.0.0 |
118
- | [MobileNet v2 1.4](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.4_224/mobilenet_v2_1.4_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32H7 | 2332.2 KiB | 30.19 KiB | 6015.34 KiB | 191.16 KiB | 2362.39 KiB | 6206.53 KiB | 10.0.0 |
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120
  ### Reference **MCU** inference time based on Flowers and ImageNet dataset (see Accuracy for details on dataset)
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122
  | Model | Dataset | Format | Resolution | Board | Execution Engine | Frequency | Inference time (ms) | STM32Cube.AI version |
123
  |--------------------------------------------------------------------------------------------------------------------------------------------------|----------|--------|-------------|------------------|------------------|-------------|---------------------|-----------------------|
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- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Flowers | Int8 | 128x128x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 94.34 ms | 10.0.0 |
125
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | Flowers | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 290.75 ms | 10.0.0 |
126
- | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_128/mobilenet_v2_0.35_128_int8.tflite) | ImageNet | Int8 | 128x128x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 116.13 ms | 10.0.0 |
127
- | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_224/mobilenet_v2_0.35_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 313.92 ms | 10.0.0 |
128
- | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 1106.64 ms | 10.0.0 |
129
- | [MobileNet v2 1.4](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.4_224/mobilenet_v2_1.4_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 2010.66 ms | 10.0.0 |
130
 
131
  ### Reference **MPU** inference time based on Flowers and ImageNet dataset (see Accuracy for details on dataset)
132
  | Model | Dataset | Format | Resolution | Quantization | Board | Execution Engine | Frequency | Inference time (ms) | %NPU | %GPU | %CPU | X-LINUX-AI version | Framework |
133
  |--------------------------------------------------------------------------------------------------------------------------------------------------|----------|--------|------------|---------------|-------------------|------------------|-----------|---------------------|-------|-------|------|--------------------|-----------------------|
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- | [MobileNet v2 1.0_per_tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8_per_tensor.tflite) | ImageNet | Int8 | 224x224x3 | per-tensor | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 11.92 ms | 92.74 | 7.26 |0 | v5.1.0 | OpenVX |
135
- | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | per-channel ** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 76.29 ms | 3.13 | 96.87 |0 | v5.1.0 | OpenVX |
136
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | Flowers | Int8 | 224x224x3 | per-channel ** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 25.51 ms | 4.37 | 95.63 |0 | v5.1.0 | OpenVX |
137
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Flowers | Int8 | 128x128x3 | per-channel ** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 9.14 ms | 12.06 | 87.94 |0 | v5.1.0 | OpenVX |
138
- | [MobileNet v2 1.0_per_tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8_per_tensor.tflite) | ImageNet | Int8 | 224x224x3 | per-tensor | STM32MP157F-DK2 | 2 CPU | 800 MHz | 332.9 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
139
- | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8.tflite) | ImageNet | Int8 | 128x128x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 194.1 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
140
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | Flowers | Int8 | 224x224x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 54.52 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
141
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Flowers | Int8 | 128x128x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 17.16 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
142
- | [MobileNet v2 1.0_per_tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8_per_tensor.tflite) | ImageNet | Int8 | 224x224x3 | per-tensor | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 415.7 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
143
- | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8.tflite) | ImageNet | Int8 | 128x128x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 308.80 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
144
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | Flowers | Int8 | 224x224x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 54.85 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
145
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Flowers | Int8 | 128x128x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 27.17 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
146
 
147
  ** **To get the most out of MP25 NPU hardware acceleration, please use per-tensor quantization**
148
  ### Accuracy with Flowers dataset
@@ -152,18 +152,18 @@ Dataset details: [link](http://download.tensorflow.org/example_images/flower_pho
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153
  | Model | Format | Resolution | Top 1 Accuracy |
154
  |-------|--------|------------|----------------|
155
- | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_tfs/mobilenet_v2_0.35_128_tfs.h5) | Float | 128x128x3 | 87.06 % |
156
- | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_tfs/mobilenet_v2_0.35_128_tfs_int8.tflite) | Int8 | 128x128x3 | 87.47 % |
157
- | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_tl/mobilenet_v2_0.35_128_tl.h5) | Float | 128x128x3 | 88.15 % |
158
- | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_tl/mobilenet_v2_0.35_128_tl_int8.tflite) | Int8 | 128x128x3 | 88.01 % |
159
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft.h5) | Float | 128x128x3 | 91.83 % |
160
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Int8 | 128x128x3 | 91.01 % |
161
- | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_tfs/mobilenet_v2_0.35_224_tfs.h5) | Float | 224x224x3 | 88.69 % |
162
- | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_tfs/mobilenet_v2_0.35_224_tfs_int8.tflite) | Int8 | 224x224x3 | 88.83 % |
163
- | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_tl/mobilenet_v2_0.35_224_tl.h5) | Float | 224x224x3 | 88.96 % |
164
- | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_tl/mobilenet_v2_0.35_224_tl_int8.tflite) | Int8 | 224x224x3 | 88.01 % |
165
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft.h5) | Float | 224x224x3 | 93.6 % |
166
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | Int8 | 224x224x3 | 92.78 % |
167
 
168
 
169
  ### Accuracy with Plant-village dataset
@@ -173,18 +173,18 @@ Dataset details: [link](https://data.mendeley.com/datasets/tywbtsjrjv/1) , Licen
173
 
174
  | Model | Format | Resolution | Top 1 Accuracy |
175
  |-------|--------|------------|----------------|
176
- | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_128_tfs/mobilenet_v2_0.35_128_tfs.h5) | Float | 128x128x3 | 99.86 % |
177
- | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_128_tfs/mobilenet_v2_0.35_128_tfs_int8.tflite) | Int8 | 128x128x3 | 99.83 % |
178
- | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_128_tl/mobilenet_v2_0.35_128_tl.h5) | Float | 128x128x3 | 93.51 % |
179
- | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_128_tl/mobilenet_v2_0.35_128_tl_int8.tflite) | Int8 | 128x128x3 | 92.33 % |
180
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft.h5) | Float | 128x128x3 | 99.77 % |
181
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Int8 | 128x128x3 | 99.48 % |
182
- | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_224_tfs/mobilenet_v2_0.35_224_tfs.h5) | Float | 224x224x3 | 99.86 % |
183
- | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_224_tfs/mobilenet_v2_0.35_224_tfs_int8.tflite) | Int8 | 224x224x3 | 99.81 % |
184
- | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_224_tl/mobilenet_v2_0.35_224_tl.h5) | Float | 224x224x3 | 93.62 % |
185
- | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_224_tl/mobilenet_v2_0.35_224_tl_int8.tflite) | Int8 | 224x224x3 | 92.8 % |
186
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft.h5) | Float | 224x224x3 | 99.95 % |
187
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | Int8 | 224x224x3 | 99.68 % |
188
 
189
 
190
  ### Accuracy with Food-101 dataset
@@ -193,20 +193,20 @@ Dataset details: [link](https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-1
193
 
194
  | Model | Format | Resolution | Top 1 Accuracy |
195
  |-------|--------|------------|----------------|
196
- | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_128_tfs/mobilenet_v2_0.35_128_tfs.h5) | Float | 128x128x3 | 64.22 % |
197
- | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_128_tfs/mobilenet_v2_0.35_128_tfs_int8.tflite) | Int8 | 128x128x3 | 63.41 % |
198
- | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_128_tl/mobilenet_v2_0.35_128_tl.h5) | Float | 128x128x3 | 44.74 % |
199
- | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_128_tl/mobilenet_v2_0.35_128_tl_int8.tflite) | Int8 | 128x128x3 | 42.01 % |
200
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft.h5) | Float | 128x128x3 | 64.22 % |
201
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Int8 | 128x128x3 | 63.41 % |
202
- | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_224_tfs/mobilenet_v2_0.35_224_tfs.h5) | Float | 224x224x3 | 72.31 % |
203
- | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_224_tfs/mobilenet_v2_0.35_224_tfs_int8.tflite) | Int8 | 224x224x3 | 72.05 % |
204
- | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_224_tl/mobilenet_v2_0.35_224_tl.h5) | Float | 224x224x3 | 49.01 % |
205
- | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_224_tl/mobilenet_v2_0.35_224_tl_int8.tflite) | Int8 | 224x224x3 | 47.26 % |
206
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft.h5) | Float | 224x224x3 | 73.76 % |
207
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | Int8 | 224x224x3 | 73.16 % |
208
- | [MobileNet v2 1.0 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_1.0_224_fft/mobilenet_v2_1.0_224_fft.h5) | Float | 224x224x3 | 77.77 % |
209
- | [MobileNet v2 1.0 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_1.0_224_fft/mobilenet_v2_1.0_224_fft_int8.tflite) | Int8 | 224x224x3 | 77.09 % |
210
 
211
 
212
  ### Accuracy with person dataset
@@ -216,12 +216,12 @@ Dataset details: [link](https://cocodataset.org/) , License [Creative Commons At
216
 
217
  | Model | Format | Resolution | Top 1 Accuracy |
218
  |------------|--------|-----------|----------------|
219
- | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/person/mobilenet_v2_0.35_128_tfs/mobilenet_v2_0.35_128_tfs.h5) | Float | 128x128x3 | 92.56 % |
220
- | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/person/mobilenet_v2_0.35_128_tfs/mobilenet_v2_0.35_128_tfs_int8.tflite) | Int8 | 128x128x3 | 92.44 % |
221
- | [MobileNet v2 0.35 tl ](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/person/mobilenet_v2_0.35_128_tl/mobilenet_v2_0.35_128_tl.h5) | Float | 128x128x3 | 92.28 % |
222
- | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/person/mobilenet_v2_0.35_128_tl/mobilenet_v2_0.35_128_tl_int8.tflite) | Int8 | 128x128x3 | 91.63 % |
223
- | [MobileNet v2 0.35 fft ](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/person/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft.h5) | Float | 128x128x3 | 95.37 % |
224
- | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/person/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Int8 | 128x128x3 | 94.95 % |
225
 
226
 
227
  ### Accuracy with ImageNet
@@ -233,15 +233,15 @@ For the sake of simplicity, the accuracy reported here was estimated on the 5000
233
 
234
  | Model | Format | Resolution | Top 1 Accuracy |
235
  |----------|--------|------------|----------------|
236
- | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_128/mobilenet_v2_0.35_128.h5) | Float | 128x128x3 | 46.96 % |
237
- | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_128/mobilenet_v2_0.35_128_int8.tflite) | Int8 | 128x128x3 | 43.94 % |
238
- | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_224/mobilenet_v2_0.35_224.h5) | Float | 224x224x3 | 56.44 % |
239
- | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_224/mobilenet_v2_0.35_224_int8.tflite) | Int8 | 224x224x3 | 54.7 % |
240
- | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224.h5) | Float | 224x224x3 | 68.87 % |
241
- | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8.tflite) | Int8 | 224x224x3 | 67.97 % |
242
- | [MobileNet v2 1.0_per_tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8_per_tensor.tflite) | Int8 | 224x224x3 | 64.53 % |
243
- | [MobileNet v2 1.4](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.4_224/mobilenet_v2_1.4_224.h5) | Float | 224x224x3 | 71.97 % |
244
- | [MobileNet v2 1.4](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.4_224/mobilenet_v2_1.4_224_int8.tflite) | Int8 | 224x224x3 | 71.46 % |
245
 
246
 
247
  ## Retraining and Integration in a simple example:
 
2
  license: other
3
  license_name: sla0044
4
  license_link: >-
5
+ https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/LICENSE.md
6
  pipeline_tag: image-classification
7
  ---
8
  # MobileNet v2
 
83
  ### Reference **NPU** memory footprint on food-101 and ImageNet dataset (see Accuracy for details on dataset)
84
  |Model | Dataset | Format | Resolution | Series | Internal RAM | External RAM | Weights Flash | STM32Cube.AI version | STEdgeAI Core version |
85
  |----------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
86
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | food-101 | Int8 | 128x128x3 | STM32N6 | 240 | 0.0 | 715.67 | 10.0.0 | 2.0.0 |
87
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | food-101 | Int8 | 224x224x3 | STM32N6 | 980 | 0.0 | 730.7 | 10.0.0 | 2.0.0 |
88
+ | [MobileNet v2 1.0 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_1.0_224_fft/mobilenet_v2_1.0_224_fft_int8.tflite) | food-101 | Int8 | 224x224x3 | STM32N6 | 2058 | 0.0 | 3110.05 | 10.0.0 | 2.0.0 |
89
  | [MobileNet v2 0.35 fft](ST_pretrainedmodel_public_dataset/person/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Person | Int8 | 128x128x3 | STM32N6 | 240 | 0.0 | 589.45 | 10.0.0 | 2.0.0 |
90
+ | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_128/mobilenet_v2_0.35_128_int8.tflite) | ImageNet | Int8 | 128x128x3 | STM32N6 | 240 | 0.0 | 1840.94 | 10.0.0 | 2.0.0 |
91
+ | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_224/mobilenet_v2_0.35_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32N6 | 980 | 0.0 | 1855.97 | 10.0.0 | 2.0.0 |
92
+ | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32N6 | 2058 | 0.0 | 4235.31 | 10.0.0 | 2.0.0 |
93
+ | [MobileNet v2 1.4](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.4_224/mobilenet_v2_1.4_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32N6 | 2361 | 0.0 | 7315.69 | 10.0.0 | 2.0.0 |
94
 
95
 
96
  ### Reference **NPU** inference time on food-101 and ImageNet dataset (see Accuracy for details on dataset)
97
  | Model | Dataset | Format | Resolution | Board | Execution Engine | Inference time (ms) | Inf / sec | STM32Cube.AI version | STEdgeAI Core version |
98
  |--------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
99
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | food-101 | Int8 | 128x128x3 | STM32N6570-DK | NPU/MCU | 3.33 | 300.30 | 10.0.0 | 2.0.0 |
100
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | food-101 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 6.12 | 163.40 | 10.0.0 | 2.0.0 |
101
+ | [MobileNet v2 1.0 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_1.0_224_fft/mobilenet_v2_1.0_224_fft_int8.tflite) | food-101 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 18.08 | 55.32 | 10.0.0 | 2.0.0 |
102
  | [MobileNet v2 0.35 fft](ST_pretrainedmodel_public_dataset/person/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Person | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 2.99 | 334.45 | 10.0.0 | 2.0.0 |
103
+ | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_128/mobilenet_v2_0.35_128_int8.tflite) | ImageNet | Int8 | 128x128x3 | STM32N6570-DK | NPU/MCU | 6.35 | 157.48 | 10.0.0 | 2.0.0 |
104
+ | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_224/mobilenet_v2_0.35_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 9.14 | 109.40 | 10.0.0 | 2.0.0 |
105
+ | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 21.08 | 47.44 | 10.0.0 | 2.0.0 |
106
+ | [MobileNet v2 1.4](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.4_224/mobilenet_v2_1.4_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 35.34 | 28.30 | 10.0.0 | 2.0.0 |
107
 
108
 
109
  ### Reference **MCU** memory footprint based on Flowers and ImageNet dataset (see Accuracy for details on dataset)
110
 
111
  | Model | Dataset | Format | Resolution | Series | Activation RAM | Runtime RAM | Weights Flash | Code Flash | Total RAM | Total Flash | STM32Cube.AI version |
112
  |--------------------------------------------------------------------------------------------------------------------------------------------------|----------|--------|-------------|---------|----------------|-------------|---------------|------------|------------|-------------|----------------------|
113
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Flowers | Int8 | 128x128x3 | STM32H7 | 237.32 KiB | 30.14 KiB | 406.86 KiB | 108.29 KiB | 267.46 KiB | 515.15 KiB | 10.0.0 |
114
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | Flowers | Int8 | 224x224x3 | STM32H7 | 832.64 KiB | 30.19 KiB | 406.86 KiB | 108.40 KiB | 862.83 KiB | 515.26 KiB | 10.0.0 |
115
+ | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_128/mobilenet_v2_0.35_128_int8.tflite) | ImageNet | Int8 | 128x128x3 | STM32H7 | 237.32 KiB | 30.14 KiB | 1654.5 KiB KiB | 108.29 KiB | 267.46 KiB | 1762.79 KiB | 10.0.0 |
116
+ | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_224/mobilenet_v2_0.35_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32H7 | 832.64 KiB | 30.19 KiB | 1654.5 KiB | 108.40 KiB | 862.83 KiB | 1762.9 KiB | 10.0.0 |
117
+ | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32H7 | 1727.02 KiB | 30.19 KiB | 3458.97 KiB | 157.37 KiB | 1757.21 KiB | 3616.34 KiB | 10.0.0 |
118
+ | [MobileNet v2 1.4](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.4_224/mobilenet_v2_1.4_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32H7 | 2332.2 KiB | 30.19 KiB | 6015.34 KiB | 191.16 KiB | 2362.39 KiB | 6206.53 KiB | 10.0.0 |
119
 
120
  ### Reference **MCU** inference time based on Flowers and ImageNet dataset (see Accuracy for details on dataset)
121
 
122
  | Model | Dataset | Format | Resolution | Board | Execution Engine | Frequency | Inference time (ms) | STM32Cube.AI version |
123
  |--------------------------------------------------------------------------------------------------------------------------------------------------|----------|--------|-------------|------------------|------------------|-------------|---------------------|-----------------------|
124
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Flowers | Int8 | 128x128x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 94.34 ms | 10.0.0 |
125
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | Flowers | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 290.75 ms | 10.0.0 |
126
+ | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_128/mobilenet_v2_0.35_128_int8.tflite) | ImageNet | Int8 | 128x128x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 116.13 ms | 10.0.0 |
127
+ | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_224/mobilenet_v2_0.35_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 313.92 ms | 10.0.0 |
128
+ | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 1106.64 ms | 10.0.0 |
129
+ | [MobileNet v2 1.4](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.4_224/mobilenet_v2_1.4_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 2010.66 ms | 10.0.0 |
130
 
131
  ### Reference **MPU** inference time based on Flowers and ImageNet dataset (see Accuracy for details on dataset)
132
  | Model | Dataset | Format | Resolution | Quantization | Board | Execution Engine | Frequency | Inference time (ms) | %NPU | %GPU | %CPU | X-LINUX-AI version | Framework |
133
  |--------------------------------------------------------------------------------------------------------------------------------------------------|----------|--------|------------|---------------|-------------------|------------------|-----------|---------------------|-------|-------|------|--------------------|-----------------------|
134
+ | [MobileNet v2 1.0_per_tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8_per_tensor.tflite) | ImageNet | Int8 | 224x224x3 | per-tensor | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 11.92 ms | 92.74 | 7.26 |0 | v5.1.0 | OpenVX |
135
+ | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8.tflite) | ImageNet | Int8 | 224x224x3 | per-channel ** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 76.29 ms | 3.13 | 96.87 |0 | v5.1.0 | OpenVX |
136
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | Flowers | Int8 | 224x224x3 | per-channel ** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 25.51 ms | 4.37 | 95.63 |0 | v5.1.0 | OpenVX |
137
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Flowers | Int8 | 128x128x3 | per-channel ** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 9.14 ms | 12.06 | 87.94 |0 | v5.1.0 | OpenVX |
138
+ | [MobileNet v2 1.0_per_tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8_per_tensor.tflite) | ImageNet | Int8 | 224x224x3 | per-tensor | STM32MP157F-DK2 | 2 CPU | 800 MHz | 332.9 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
139
+ | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8.tflite) | ImageNet | Int8 | 128x128x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 194.1 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
140
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | Flowers | Int8 | 224x224x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 54.52 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
141
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Flowers | Int8 | 128x128x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 17.16 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
142
+ | [MobileNet v2 1.0_per_tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8_per_tensor.tflite) | ImageNet | Int8 | 224x224x3 | per-tensor | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 415.7 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
143
+ | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8.tflite) | ImageNet | Int8 | 128x128x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 308.80 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
144
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | Flowers | Int8 | 224x224x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 54.85 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
145
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Flowers | Int8 | 128x128x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 27.17 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
146
 
147
  ** **To get the most out of MP25 NPU hardware acceleration, please use per-tensor quantization**
148
  ### Accuracy with Flowers dataset
 
152
 
153
  | Model | Format | Resolution | Top 1 Accuracy |
154
  |-------|--------|------------|----------------|
155
+ | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_tfs/mobilenet_v2_0.35_128_tfs.h5) | Float | 128x128x3 | 87.06 % |
156
+ | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_tfs/mobilenet_v2_0.35_128_tfs_int8.tflite) | Int8 | 128x128x3 | 87.47 % |
157
+ | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_tl/mobilenet_v2_0.35_128_tl.h5) | Float | 128x128x3 | 88.15 % |
158
+ | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_tl/mobilenet_v2_0.35_128_tl_int8.tflite) | Int8 | 128x128x3 | 88.01 % |
159
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft.h5) | Float | 128x128x3 | 91.83 % |
160
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Int8 | 128x128x3 | 91.01 % |
161
+ | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_tfs/mobilenet_v2_0.35_224_tfs.h5) | Float | 224x224x3 | 88.69 % |
162
+ | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_tfs/mobilenet_v2_0.35_224_tfs_int8.tflite) | Int8 | 224x224x3 | 88.83 % |
163
+ | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_tl/mobilenet_v2_0.35_224_tl.h5) | Float | 224x224x3 | 88.96 % |
164
+ | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_tl/mobilenet_v2_0.35_224_tl_int8.tflite) | Int8 | 224x224x3 | 88.01 % |
165
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft.h5) | Float | 224x224x3 | 93.6 % |
166
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/flowers/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | Int8 | 224x224x3 | 92.78 % |
167
 
168
 
169
  ### Accuracy with Plant-village dataset
 
173
 
174
  | Model | Format | Resolution | Top 1 Accuracy |
175
  |-------|--------|------------|----------------|
176
+ | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_128_tfs/mobilenet_v2_0.35_128_tfs.h5) | Float | 128x128x3 | 99.86 % |
177
+ | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_128_tfs/mobilenet_v2_0.35_128_tfs_int8.tflite) | Int8 | 128x128x3 | 99.83 % |
178
+ | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_128_tl/mobilenet_v2_0.35_128_tl.h5) | Float | 128x128x3 | 93.51 % |
179
+ | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_128_tl/mobilenet_v2_0.35_128_tl_int8.tflite) | Int8 | 128x128x3 | 92.33 % |
180
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft.h5) | Float | 128x128x3 | 99.77 % |
181
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Int8 | 128x128x3 | 99.48 % |
182
+ | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_224_tfs/mobilenet_v2_0.35_224_tfs.h5) | Float | 224x224x3 | 99.86 % |
183
+ | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_224_tfs/mobilenet_v2_0.35_224_tfs_int8.tflite) | Int8 | 224x224x3 | 99.81 % |
184
+ | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_224_tl/mobilenet_v2_0.35_224_tl.h5) | Float | 224x224x3 | 93.62 % |
185
+ | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_224_tl/mobilenet_v2_0.35_224_tl_int8.tflite) | Int8 | 224x224x3 | 92.8 % |
186
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft.h5) | Float | 224x224x3 | 99.95 % |
187
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/plant-village/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | Int8 | 224x224x3 | 99.68 % |
188
 
189
 
190
  ### Accuracy with Food-101 dataset
 
193
 
194
  | Model | Format | Resolution | Top 1 Accuracy |
195
  |-------|--------|------------|----------------|
196
+ | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_128_tfs/mobilenet_v2_0.35_128_tfs.h5) | Float | 128x128x3 | 64.22 % |
197
+ | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_128_tfs/mobilenet_v2_0.35_128_tfs_int8.tflite) | Int8 | 128x128x3 | 63.41 % |
198
+ | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_128_tl/mobilenet_v2_0.35_128_tl.h5) | Float | 128x128x3 | 44.74 % |
199
+ | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_128_tl/mobilenet_v2_0.35_128_tl_int8.tflite) | Int8 | 128x128x3 | 42.01 % |
200
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft.h5) | Float | 128x128x3 | 64.22 % |
201
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Int8 | 128x128x3 | 63.41 % |
202
+ | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_224_tfs/mobilenet_v2_0.35_224_tfs.h5) | Float | 224x224x3 | 72.31 % |
203
+ | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_224_tfs/mobilenet_v2_0.35_224_tfs_int8.tflite) | Int8 | 224x224x3 | 72.05 % |
204
+ | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_224_tl/mobilenet_v2_0.35_224_tl.h5) | Float | 224x224x3 | 49.01 % |
205
+ | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_224_tl/mobilenet_v2_0.35_224_tl_int8.tflite) | Int8 | 224x224x3 | 47.26 % |
206
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft.h5) | Float | 224x224x3 | 73.76 % |
207
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_0.35_224_fft/mobilenet_v2_0.35_224_fft_int8.tflite) | Int8 | 224x224x3 | 73.16 % |
208
+ | [MobileNet v2 1.0 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_1.0_224_fft/mobilenet_v2_1.0_224_fft.h5) | Float | 224x224x3 | 77.77 % |
209
+ | [MobileNet v2 1.0 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/food-101/mobilenet_v2_1.0_224_fft/mobilenet_v2_1.0_224_fft_int8.tflite) | Int8 | 224x224x3 | 77.09 % |
210
 
211
 
212
  ### Accuracy with person dataset
 
216
 
217
  | Model | Format | Resolution | Top 1 Accuracy |
218
  |------------|--------|-----------|----------------|
219
+ | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/person/mobilenet_v2_0.35_128_tfs/mobilenet_v2_0.35_128_tfs.h5) | Float | 128x128x3 | 92.56 % |
220
+ | [MobileNet v2 0.35 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/person/mobilenet_v2_0.35_128_tfs/mobilenet_v2_0.35_128_tfs_int8.tflite) | Int8 | 128x128x3 | 92.44 % |
221
+ | [MobileNet v2 0.35 tl ](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/person/mobilenet_v2_0.35_128_tl/mobilenet_v2_0.35_128_tl.h5) | Float | 128x128x3 | 92.28 % |
222
+ | [MobileNet v2 0.35 tl](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/person/mobilenet_v2_0.35_128_tl/mobilenet_v2_0.35_128_tl_int8.tflite) | Int8 | 128x128x3 | 91.63 % |
223
+ | [MobileNet v2 0.35 fft ](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/person/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft.h5) | Float | 128x128x3 | 95.37 % |
224
+ | [MobileNet v2 0.35 fft](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/ST_pretrainedmodel_public_dataset/person/mobilenet_v2_0.35_128_fft/mobilenet_v2_0.35_128_fft_int8.tflite) | Int8 | 128x128x3 | 94.95 % |
225
 
226
 
227
  ### Accuracy with ImageNet
 
233
 
234
  | Model | Format | Resolution | Top 1 Accuracy |
235
  |----------|--------|------------|----------------|
236
+ | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_128/mobilenet_v2_0.35_128.h5) | Float | 128x128x3 | 46.96 % |
237
+ | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_128/mobilenet_v2_0.35_128_int8.tflite) | Int8 | 128x128x3 | 43.94 % |
238
+ | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_224/mobilenet_v2_0.35_224.h5) | Float | 224x224x3 | 56.44 % |
239
+ | [MobileNet v2 0.35](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_0.35_224/mobilenet_v2_0.35_224_int8.tflite) | Int8 | 224x224x3 | 54.7 % |
240
+ | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224.h5) | Float | 224x224x3 | 68.87 % |
241
+ | [MobileNet v2 1.0](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8.tflite) | Int8 | 224x224x3 | 67.97 % |
242
+ | [MobileNet v2 1.0_per_tensor](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.0_224/mobilenet_v2_1.0_224_int8_per_tensor.tflite) | Int8 | 224x224x3 | 64.53 % |
243
+ | [MobileNet v2 1.4](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.4_224/mobilenet_v2_1.4_224.h5) | Float | 224x224x3 | 71.97 % |
244
+ | [MobileNet v2 1.4](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/mobilenetv2/Public_pretrainedmodel_public_dataset/ImageNet/mobilenet_v2_1.4_224/mobilenet_v2_1.4_224_int8.tflite) | Int8 | 224x224x3 | 71.46 % |
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  ## Retraining and Integration in a simple example: