5waNg / MobileNetV2-PyTorch

This is the PyTorch implement of MobileNet V2

This is the PyTorch implement of MobileNet V2 (train on ImageNet dataset)

Paper: Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segment

Usage

Prepare data

This code takes ImageNet dataset as example. You can download ImageNet dataset and put them as follows. I only provide ILSVRC2012_dev_kit_t12 due to the restriction of memory, in other words, you need download ILSVRC2012_img_train and ILSVRC2012_img_val.

├── train.py # train script
├── MobileNetV2.py # network of MobileNetV2
├── read_ImageNetData.py # ImageNet dataset read script
├── ImageData # train and validation data
	├── ILSVRC2012_img_train
		├── n01440764
		├──    ...
		├── n15075141
	├── ILSVRC2012_img_val
	├── ILSVRC2012_dev_kit_t12
		├── data
			├── ILSVRC2012_validation_ground_truth.txt
			├── meta.mat # the map between train file name and label

Train

• If you want to train from scratch, you can run as follows:

python train.py --batch-size 256 --gpus 0,1,2,3

• If you want to train from one checkpoint, you can run as follows(for example train from epoch_4.pth.tar, the --start-epoch parameter is corresponding to the epoch of the checkpoint):

python train.py --batch-size 256 --gpus 0,1,2,3 --resume output/epoch_4.pth.tar --start-epoch 4