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README.md

MobileNet v2 1.0 224 UINT8

Description

MobileNet v2 is an efficient image classification neural network, targeted for mobile and embedded use cases. This model is trained on the ImageNet dataset and is quantized to the UINT8 datatype by Google.

License

Apache-2.0

Related Materials

Class Labels

The class labels associated with this model can be downloaded by running the script get_class_labels.sh.

How-To Guide

A guide on how to deploy this model using the Arm NN SDK can be found here.

Network Information

Network Information Value
Framework TensorFlow Lite
SHA-1 Hash 275c9649cb395139103b6d15f53011b1b949ad00
Size (Bytes) 3577760
Provenance https://tfhub.dev/tensorflow/lite-model/mobilenet_v2_1.0_224_quantized/1/default/1
Paper https://arxiv.org/pdf/1801.04381.pdf

Performance

Platform Optimized
Cortex-A ✖️
Cortex-M ✖️
Mali GPU ✔️
Ethos U ✔️

Key

  • ✔️ - Will run on this platform.
  • ✖️ - Will not run on this platform.

Accuracy

Dataset: Ilsvrc 2012

Metric Value
Top 1 Accuracy 0.708

Optimizations

Optimization Value
Quantization UINT8

Network Inputs

Input Node Name Shape Description
input (1, 224, 224, 3) Single 224x224 RGB image with UINT8 values between 0 and 255

Network Outputs

Output Node Name Shape Description
output (1, 1001) Per-class confidence for 1001 ImageNet classes