lvcat / lednet

This is an unofficial implement of LEDNet https://arxiv.org/abs/1905.02423

LEDNet

This is an unofficial implement of LEDNet.

the official version：LEDNet-official

Environment

• Python 3.6
• PyTorch 1.1

Performance

• Base Size 1024, Crop Size 768, only fine. (old-version, without dropout)

Model	Paper	OHEM	Epoch	val (crop)	val
LEDNet	/	✗	240	44.67/91.85	49.79/91.31
LEDNet	/	✗	1000	53.77/93.45	59.04/93.27

• Base Size 1356, Crop Size 1024, only fine. (old-version, without dropout)

Model	Paper	OHEM	Epoch	val (crop)	val
LEDNet	/	✗	1000	56.30/93.90

The paper only provide the test results: 69.2/86.8 (class mIoU/category mIoU)

• reference the Fast-SCNN, we choose epoch=1000

• Height 1024, Width 512. (new-version)

Model	Paper	OHEM	Epoch	val (crop)	val
LEDNet	/	✗	300	39.03/88.60	21.17/72.79
LEDNet	/	✗	800	41.70/89.46

Demo

TODO

Evaluation

The default data root is ~/.torch/datasets (You can download dataset and build a soft-link to it)

$ python eval.py [--mode testval] [--pretrained root-of-pretrained-model] [--cuda true]

Training

Recommend to using distributed training.

$ export NGPUS=4
$ python -m torch.distributed.launch --nproc_per_node=$NGPUS train.py [--dataset citys] [--batch-size 8] [--base-size 1024] [--crop-size 768] [--epochs 240] [--warmup-factor 0.1] [--warmup-iters 200] [--log-step 10] [--save-epoch 40] [--lr 0.0001]

Prepare data

Your can reference gluon-cv-cityspaces to prepare the dataset