LightNet++
EfficientNet.PyTorch: Concise, Modular, Human-friendly PyTorch implementation of EfficientNet with Pre-trained Weights
!!!New Repo.!!! ⇒MixNet-Pytorch: Concise, Modular, Human-friendly PyTorch implementation of MixNet with Pre-trained Weights
!!!New Repo.!!! ⇒This repository contains the code (PyTorch-1.0+, W.I.P.) for: "LightNet++: Boosted Light-weighted Networks for Real-time Semantic Segmentation" by Huijun Liu.
LightNet++ is an advanced version of LightNet, which purpose to get more concise model design,
smaller models, and better performance.
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MobileNetV2Plus: Modified MobileNetV2 (backbone)[1,8] + DSASPPInPlaceABNBlock[2,3] + Parallel Bottleneck Channel-Spatial Attention Block (PBCSABlock)[6] + UnSharp Masking (USM) + Encoder-Decoder Arch.[3] + InplaceABN[4].
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ShuffleNetV2Plus: Modified ShuffleNetV2 (backbone)[1,8] + DSASPPInPlaceABNBlock[2,3] + Parallel Bottleneck Channel-Spatial Attention Block (PBCSABlock)[6]+ UnSharp Masking (USM) + Encoder-Decoder Arch.[3] + InplaceABN[4].
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MixSeg-MixBiFPN: Modified MixNet (backbone)[1,8] + MixBiFPNBlock[2,3] + Encoder-Decoder Arch.[3]
More about USM(Unsharp Mask)-Operator Block see Repo: SharpPeleeNet
Dependencies
- Python3.6
- PyTorch(1.0.1+)
- inplace_abn
- apex: Tools for easy mixed precision and distributed training in Pytorch
- tensorboard
- tensorboardX
- tqdm
Datasets for Autonomous Driving
Results
Results on Cityscapes (Pixel-level/Semantic Segmentation)
Model | mIoU (S.S* Mixed Precision) | Model Weight |
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MobileNetV2Plus X1.0 | 71.5314 (WIP) | cityscapes_mobilenetv2plus_x1.0.pkl (14.3 MB) |
ShuffleNetV2Plus X1.0 | 69.0885-72.5255 (WIP) | cityscapes_shufflenetv2plus_x1.0.pkl (8.59 MB) |
MixSeg+MixBiFPN ArchS | 72.2321 (WIP) | cityscapes_mixseg_archs_mixbifpn.pkl (16.4 MB) |
- S.S.: Single Scale (1024x2048)