STMicroelectronics
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efficientnet

Image Classification

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FBAGSTM commited on Dec 10, 2024

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@@ -2,7 +2,7 @@
 license: other
 license_name: sla0044
 license_link: >-
-  https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/efficientnet/ST_pretrainedmodel_public_dataset/LICENSE.md
 pipeline_tag: image-classification
 ---
 # EfficientNet
@@ -71,14 +71,14 @@ For an image resolution of NxM and P classes :
 ### Reference **NPU** memory footprint on food-101 dataset (see Accuracy for details on dataset)
 |Model      |  Format   | Resolution | Series    | Internal RAM (KiB) | External RAM (KiB) | Weights Flash (KiB)| STM32Cube.AI version | STEdgeAI Core version |
 |----------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
-| [ST EfficientNet LC v1 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/efficientnet/ST_pretrainedmodel_public_dataset/food-101/st_efficientnet_lc_v1_128_tfs/st_efficientnet_lc_v1_128_tfs_int8.tflite) |  Int8     | 128x128x3  | STM32N6   | 256 | 0 | 625.8 | 10.0.0 | 2.0.0 |
-|  [ST EfficientNet LC v1 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/efficientnet/ST_pretrainedmodel_public_dataset/food-101/st_efficientnet_lc_v1_224_tfs/st_efficientnet_lc_v1_224_tfs_int8.tflite)  | Int8     | 224x224x3  | STM32N6   | 784.02 | 0 | 632.55 | 10.0.0 | 2.0.0 |
 ### Reference **NPU**  inference time on food-101 dataset (see Accuracy for details on dataset)
 | Model  |  Format | Resolution  | Board            | Execution Engine | Inference time (ms) | Inf / sec   | STM32Cube.AI version  |  STEdgeAI Core version |
 |--------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
-| [ST EfficientNet LC v1 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/efficientnet/ST_pretrainedmodel_public_dataset/food-101/st_efficientnet_lc_v1_128_tfs/st_efficientnet_lc_v1_128_tfs_int8.tflite)|  Int8 |  128x128x3  | STM32N6570-DK   |   NPU/MCU      |        6.87        |       145.55      |       10.0.0        |     2.0.0   |
-| [ST EfficientNet LC v1 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/image_classification/efficientnet/ST_pretrainedmodel_public_dataset/food-101/st_efficientnet_lc_v1_224_tfs/st_efficientnet_lc_v1_224_tfs_int8.tflite) |  Int8     |  224x224x3 | STM32N6570-DK   |   NPU/MCU      |      15.8     |     63.29        |       10.0.0        |     2.0.0   |
 ### Reference **MCU** memory footprints based on Flowers dataset (see Accuracy for details on dataset)

 license: other
 license_name: sla0044
 license_link: >-
+  https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/efficientnet/ST_pretrainedmodel_public_dataset/LICENSE.md
 pipeline_tag: image-classification
 ---
 # EfficientNet
 ### Reference **NPU** memory footprint on food-101 dataset (see Accuracy for details on dataset)
 |Model      |  Format   | Resolution | Series    | Internal RAM (KiB) | External RAM (KiB) | Weights Flash (KiB)| STM32Cube.AI version | STEdgeAI Core version |
 |----------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
+| [ST EfficientNet LC v1 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/efficientnet/ST_pretrainedmodel_public_dataset/food-101/st_efficientnet_lc_v1_128_tfs/st_efficientnet_lc_v1_128_tfs_int8.tflite) |  Int8     | 128x128x3  | STM32N6   | 256 | 0 | 625.8 | 10.0.0 | 2.0.0 |
+|  [ST EfficientNet LC v1 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/efficientnet/ST_pretrainedmodel_public_dataset/food-101/st_efficientnet_lc_v1_224_tfs/st_efficientnet_lc_v1_224_tfs_int8.tflite)  | Int8     | 224x224x3  | STM32N6   | 784.02 | 0 | 632.55 | 10.0.0 | 2.0.0 |
 ### Reference **NPU**  inference time on food-101 dataset (see Accuracy for details on dataset)
 | Model  |  Format | Resolution  | Board            | Execution Engine | Inference time (ms) | Inf / sec   | STM32Cube.AI version  |  STEdgeAI Core version |
 |--------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
+| [ST EfficientNet LC v1 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/efficientnet/ST_pretrainedmodel_public_dataset/food-101/st_efficientnet_lc_v1_128_tfs/st_efficientnet_lc_v1_128_tfs_int8.tflite)|  Int8 |  128x128x3  | STM32N6570-DK   |   NPU/MCU      |        6.87        |       145.55      |       10.0.0        |     2.0.0   |
+| [ST EfficientNet LC v1 tfs](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/image_classification/efficientnet/ST_pretrainedmodel_public_dataset/food-101/st_efficientnet_lc_v1_224_tfs/st_efficientnet_lc_v1_224_tfs_int8.tflite) |  Int8     |  224x224x3 | STM32N6570-DK   |   NPU/MCU      |      15.8     |     63.29        |       10.0.0        |     2.0.0   |
 ### Reference **MCU** memory footprints based on Flowers dataset (see Accuracy for details on dataset)