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[Feature] Add ENet (PaddlePaddle#1623)
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ETTR123 authored Jan 24, 2022
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14 changes: 14 additions & 0 deletions configs/enet/README.md
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# ENet: A Deep Neural Network Architecture forReal-Time Semantic Segmentation

## Reference
> Abhishek Chaurasia, Sangpil Kim, Eugenio Culurciello. "ENet: A Deep Neural Network Architecture for
Real-Time Semantic Segmentation." arXiv preprint arXiv:1606.02147(2016).

## Performance

### Cityscapes

| Model | Backbone | Resolution | Training Iters | mIoU | mIoU (flip) | mIoU (ms+flip) | Links |
|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
|ENet|-|1024x512|80000|67.42%|68.11%|67.99%|[model](https://bj.bcebos.com/paddleseg/dygraph/cityscapes/bisenetv1_cityscapes_1024x512_160k/model.pdparams)\|[log](https://bj.bcebos.com/paddleseg/dygraph/cityscapes/bisenetv1_cityscapes_1024x512_160k/train.log)\|[vdl](https://paddlepaddle.org.cn/paddle/visualdl/service/app?id=5d57386cdfcdb6a6bcb5135af134a0f2)|
|
31 changes: 31 additions & 0 deletions configs/enet/enet_cityscapes_1024x512_adam_0.002_80k.yml
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_base_: '../_base_/cityscapes.yml'
batch_size: 8

train_dataset:
type: Cityscapes
dataset_root: data/cityscapes
transforms:
- type: RandomPaddingCrop
crop_size: [1024, 512]
- type: RandomDistort
brightness_range: 0.4
contrast_range: 0.4
saturation_range: 0.4
- type: Normalize
mode: train

model:
type: ENet
num_classes: 19
pretrained: Null

optimizer:
_inherited_: False
type: adam
weight_decay: 0.0002

lr_scheduler:
end_lr: 0
learning_rate: 0.001
power: 0.9
type: PolynomialDecay
3 changes: 2 additions & 1 deletion paddleseg/models/__init__.py
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from .espnet import ESPNetV2
from .dmnet import DMNet
from .espnetv1 import ESPNetV1
from .enet import ENet
from .bisenetv1 import BiseNetV1
from .fastfcn import FastFCN
from .pfpnnet import PFPNNet
from .pfpnnet import PFPNNet
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