Change Detection Models (Remote Sensing)

Python library with Neural Networks for Change Detection based on PyTorch.

🌱 How to use

Please refer to local_test.py temporarily.


🔭 Models

Architectures

Encoders

The following is a list of supported encoders in the CDP. Select the appropriate family of encoders and click to expand the table and select a specific encoder and its pre-trained weights (encoder_name and encoder_weights parameters).

ResNet
Encoder Weights Params, M
resnet18 imagenet / ssl / swsl 11M
resnet34 imagenet 21M
resnet50 imagenet / ssl / swsl 23M
resnet101 imagenet 42M
resnet152 imagenet 58M
ResNeXt
Encoder Weights Params, M
resnext50_32x4d imagenet / ssl / swsl 22M
resnext101_32x4d ssl / swsl 42M
resnext101_32x8d imagenet / instagram / ssl / swsl 86M
resnext101_32x16d instagram / ssl / swsl 191M
resnext101_32x32d instagram 466M
resnext101_32x48d instagram 826M
ResNeSt
Encoder Weights Params, M
timm-resnest14d imagenet 8M
timm-resnest26d imagenet 15M
timm-resnest50d imagenet 25M
timm-resnest101e imagenet 46M
timm-resnest200e imagenet 68M
timm-resnest269e imagenet 108M
timm-resnest50d_4s2x40d imagenet 28M
timm-resnest50d_1s4x24d imagenet 23M
Res2Ne(X)t
Encoder Weights Params, M
timm-res2net50_26w_4s imagenet 23M
timm-res2net101_26w_4s imagenet 43M
timm-res2net50_26w_6s imagenet 35M
timm-res2net50_26w_8s imagenet 46M
timm-res2net50_48w_2s imagenet 23M
timm-res2net50_14w_8s imagenet 23M
timm-res2next50 imagenet 22M
RegNet(x/y)
Encoder Weights Params, M
timm-regnetx_002 imagenet 2M
timm-regnetx_004 imagenet 4M
timm-regnetx_006 imagenet 5M
timm-regnetx_008 imagenet 6M
timm-regnetx_016 imagenet 8M
timm-regnetx_032 imagenet 14M
timm-regnetx_040 imagenet 20M
timm-regnetx_064 imagenet 24M
timm-regnetx_080 imagenet 37M
timm-regnetx_120 imagenet 43M
timm-regnetx_160 imagenet 52M
timm-regnetx_320 imagenet 105M
timm-regnety_002 imagenet 2M
timm-regnety_004 imagenet 3M
timm-regnety_006 imagenet 5M
timm-regnety_008 imagenet 5M
timm-regnety_016 imagenet 10M
timm-regnety_032 imagenet 17M
timm-regnety_040 imagenet 19M
timm-regnety_064 imagenet 29M
timm-regnety_080 imagenet 37M
timm-regnety_120 imagenet 49M
timm-regnety_160 imagenet 80M
timm-regnety_320 imagenet 141M
GERNet
Encoder Weights Params, M
timm-gernet_s imagenet 6M
timm-gernet_m imagenet 18M
timm-gernet_l imagenet 28M
SE-Net
Encoder Weights Params, M
senet154 imagenet 113M
se_resnet50 imagenet 26M
se_resnet101 imagenet 47M
se_resnet152 imagenet 64M
se_resnext50_32x4d imagenet 25M
se_resnext101_32x4d imagenet 46M
SK-ResNe(X)t
Encoder Weights Params, M
timm-skresnet18 imagenet 11M
timm-skresnet34 imagenet 21M
timm-skresnext50_32x4d imagenet 25M
DenseNet
Encoder Weights Params, M
densenet121 imagenet 6M
densenet169 imagenet 12M
densenet201 imagenet 18M
densenet161 imagenet 26M
Inception
Encoder Weights Params, M
inceptionresnetv2 imagenet / imagenet+background 54M
inceptionv4 imagenet / imagenet+background 41M
xception imagenet 22M
EfficientNet
Encoder Weights Params, M
efficientnet-b0 imagenet 4M
efficientnet-b1 imagenet 6M
efficientnet-b2 imagenet 7M
efficientnet-b3 imagenet 10M
efficientnet-b4 imagenet 17M
efficientnet-b5 imagenet 28M
efficientnet-b6 imagenet 40M
efficientnet-b7 imagenet 63M
timm-efficientnet-b0 imagenet / advprop / noisy-student 4M
timm-efficientnet-b1 imagenet / advprop / noisy-student 6M
timm-efficientnet-b2 imagenet / advprop / noisy-student 7M
timm-efficientnet-b3 imagenet / advprop / noisy-student 10M
timm-efficientnet-b4 imagenet / advprop / noisy-student 17M
timm-efficientnet-b5 imagenet / advprop / noisy-student 28M
timm-efficientnet-b6 imagenet / advprop / noisy-student 40M
timm-efficientnet-b7 imagenet / advprop / noisy-student 63M
timm-efficientnet-b8 imagenet / advprop 84M
timm-efficientnet-l2 noisy-student 474M
timm-efficientnet-lite0 imagenet 4M
timm-efficientnet-lite1 imagenet 5M
timm-efficientnet-lite2 imagenet 6M
timm-efficientnet-lite3 imagenet 8M
timm-efficientnet-lite4 imagenet 13M
MobileNet
Encoder Weights Params, M
mobilenet_v2 imagenet 2M
timm-mobilenetv3_large_075 imagenet 1.78M
timm-mobilenetv3_large_100 imagenet 2.97M
timm-mobilenetv3_large_minimal_100 imagenet 1.41M
timm-mobilenetv3_small_075 imagenet 0.57M
timm-mobilenetv3_small_100 imagenet 0.93M
timm-mobilenetv3_small_minimal_100 imagenet 0.43M
DPN
Encoder Weights Params, M
dpn68 imagenet 11M
dpn68b imagenet+5k 11M
dpn92 imagenet+5k 34M
dpn98 imagenet 58M
dpn107 imagenet+5k 84M
dpn131 imagenet 76M
VGG
Encoder Weights Params, M
vgg11 imagenet 9M
vgg11_bn imagenet 9M
vgg13 imagenet 9M
vgg13_bn imagenet 9M
vgg16 imagenet 14M
vgg16_bn imagenet 14M
vgg19 imagenet 20M
vgg19_bn imagenet 20M

:truck: Dataset

:page_with_curl: Citing

@misc{likyoocdp:2021,
  Author = {Kaiyu Li, Fulin Sun},
  Title = {Change Detection Pytorch},
  Year = {2021},
  Publisher = {GitHub},
  Journal = {GitHub repository},
  Howpublished = {\url{https://github.com/likyoo/change_detection.pytorch}}
}

GitHub

https://github.com/likyoo/change_detection.pytorch