Hugging Face's logo

STMicroelectronics
/
mobilenetv1

Image Classification
Model card Files Community
FBAGSTM commited on
Commit
794388c
·
verified ·
1 Parent(s): 0937188

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +12 -12
README.md CHANGED
@@ -75,24 +75,24 @@ For an image resolution of NxM and P classes
75
  ### Reference **NPU** memory footprint on food-101 and ImageNet dataset (see Accuracy for details on dataset)
76
  |Model | Dataset | Format | Resolution | Series | Internal RAM | External RAM | Weights Flash | STM32Cube.AI version | STEdgeAI Core version |
77
  |----------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
78
- | [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) | food-101 | Int8 | 224x224x3 | STM32N6 | 588 | 0.0 | 321.66 | 10.0.0 | 2.0.0 |
79
- | [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) | food-101 | Int8 | 224x224x3 | STM32N6 | 588 | 0.0 | 1025.63 | 10.0.0 | 2.0.0 |
80
- | [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) | food-101 | Int8 | 224x224x3 | STM32N6 | 1568 | 0.0 | 3649.97 | 10.0.0 | 2.0.0 |
81
- | [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) | ImageNet | Int8 | 224x224x3 | STM32N6 | 588 | 0.0 | 549.88 | 10.0.0 | 2.0.0 |
82
- | [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) | ImageNet | Int8 | 224x224x3 | STM32N6 | 588 | 0.0 | 1478.58 | 10.0.0 | 2.0.0 |
83
- | [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) | ImageNet | Int8 | 224x224x3 | STM32N6 | 1568 | 0.0 | 4552.42 | 10.0.0 | 2.0.0 |
84
 
85
  ### Reference **NPU** inference time on food-101 and ImageNet dataset (see Accuracy for details on dataset)
86
 
87
 
88
  | Model | Dataset | Format | Resolution | Board | Execution Engine | Inference time (ms) | Inf / sec | STM32Cube.AI version | STEdgeAI Core version |
89
  |--------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
90
- | [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) | food-101 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 2.83 | 353.36 | 10.0.0 | 2.0.0 |
91
- | [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) | food-101 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 6.06 | 165.02 | 10.0.0 | 2.0.0 |
92
- | [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) | food-101 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 16.94 | 59.03| 10.0.0 | 2.0.0 |
93
- | [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) | food-101 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 3.57 | 280.11 | 10.0.0 | 2.0.0 |
94
- | [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) | food-101 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 7.38 | 135.50 | 10.0.0 | 2.0.0 |
95
- | [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) | food-101 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 19.41 | 51.53 | 10.0.0 | 2.0.0 |
96
 
97
 
98
  ### Reference **MCU** memory footprint based on Flowers dataset and ImageNet dataset (see Accuracy for details on dataset)
 
75
  ### Reference **NPU** memory footprint on food-101 and ImageNet dataset (see Accuracy for details on dataset)
76
  |Model | Dataset | Format | Resolution | Series | Internal RAM | External RAM | Weights Flash | STM32Cube.AI version | STEdgeAI Core version |
77
  |----------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
78
+ | [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) | food-101 | Int8 | 224x224x3 | STM32N6 | 588 | 0.0 | 321.66 | 10.0.0 | 2.0.0 |
79
+ | [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) | food-101 | Int8 | 224x224x3 | STM32N6 | 588 | 0.0 | 1025.63 | 10.0.0 | 2.0.0 |
80
+ | [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) | food-101 | Int8 | 224x224x3 | STM32N6 | 1568 | 0.0 | 3649.97 | 10.0.0 | 2.0.0 |
81
+ | [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) | ImageNet | Int8 | 224x224x3 | STM32N6 | 588 | 0.0 | 549.88 | 10.0.0 | 2.0.0 |
82
+ | [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) | ImageNet | Int8 | 224x224x3 | STM32N6 | 588 | 0.0 | 1478.58 | 10.0.0 | 2.0.0 |
83
+ | [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) | ImageNet | Int8 | 224x224x3 | STM32N6 | 1568 | 0.0 | 4552.42 | 10.0.0 | 2.0.0 |
84
 
85
  ### Reference **NPU** inference time on food-101 and ImageNet dataset (see Accuracy for details on dataset)
86
 
87
 
88
  | Model | Dataset | Format | Resolution | Board | Execution Engine | Inference time (ms) | Inf / sec | STM32Cube.AI version | STEdgeAI Core version |
89
  |--------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
90
+ | [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) | food-101 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 2.83 | 353.36 | 10.0.0 | 2.0.0 |
91
+ | [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) | food-101 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 6.06 | 165.02 | 10.0.0 | 2.0.0 |
92
+ | [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) | food-101 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 16.94 | 59.03| 10.0.0 | 2.0.0 |
93
+ | [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) | food-101 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 3.57 | 280.11 | 10.0.0 | 2.0.0 |
94
+ | [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) | food-101 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 7.38 | 135.50 | 10.0.0 | 2.0.0 |
95
+ | [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) | food-101 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 19.41 | 51.53 | 10.0.0 | 2.0.0 |
96
 
97
 
98
  ### Reference **MCU** memory footprint based on Flowers dataset and ImageNet dataset (see Accuracy for details on dataset)