ShuffleNetV2 Pytorch Save

Implementation of ShuffleNetV2 for pytorch

Project README

ShuffleNetv2 in PyTorch

An implementation of ShuffleNetv2 in PyTorch. ShuffleNetv2 is an efficient convolutional neural network architecture for mobile devices. For more information check the paper: ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design

Usage

Clone the repo:

git clone https://github.com/Randl/ShuffleNetV2-pytorch
pip install -r requirements.txt

Use the model defined in model.py to run ImageNet example:

python imagenet.py --dataroot "/path/to/imagenet/"

To continue training from checkpoint

python imagenet.py --dataroot "/path/to/imagenet/" --resume "/path/to/checkpoint/folder"

Results

For x0.5 model I achieved 0.4% lower top-1 accuracy than claimed.

Classification Checkpoint MACs (M) Parameters (M) Top-1 Accuracy Top-5 Accuracy Claimed top-1 Claimed top-5
[shufflenet_v2_0.5] 41 1.37 59.86 81.63 60.3 -

You can test it with

python imagenet.py --dataroot "/path/to/imagenet/" --resume "results/shufflenet_v2_0.5/model_best.pth.tar" -e --scaling 0.5
Open Source Agenda is not affiliated with "ShuffleNetV2 Pytorch" Project. README Source: Randl/ShuffleNetV2-pytorch
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2 years ago
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