Paper: Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segment
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.
βββ train.py # train script
βββ MobileNetV2.py # network of MobileNetV2
βββ read_ImageNetData.py # ImageNet dataset read script
βββ ImageData # train and validation data
βββ ILSVRC2012_img_train
βββ n01440764
βββ ...
βββ n15075141
βββ ILSVRC2012_img_val
βββ ILSVRC2012_dev_kit_t12
βββ data
βββ ILSVRC2012_validation_ground_truth.txt
βββ meta.mat # the map between train file name and label
- 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-epochparameter 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