🔥 TorchSat 🌏

TorchSat is an open-source PyTorch framework for satellite imagery analysis. [WIP]

Hightlight

• 😉 Support multi-channels(> 3 channels, e.g. 8 channels) images and TIFF file as input.
• 😋Convenient data augmentation method for classification, sementic segmentation and object detection.
• 😍 Lots of models for satellite vision tasks, such as ResNet, DenseNet, UNet, PSPNet, SSD, FasterRCNN ...
• 😃 Lots of common satellite datasets loader.
• 😮 Training script for common satellite vision tasks.

Install

python setup.py install

How to use

• Introduction -
• Data augmentation - data-augmentation.ipynb
• Data loader
• models
• train script

Features

Transforms

We suppose all the input images, masks and bbox should be NumPy ndarray. The data shape should be [height, width] or [height, width, channels].

pixel level

Pixel-level transforms only change the input image and will leave any additional targets such as masks, bounding boxes unchanged. It support all channel images. Some transforms only support specific input channles.

Transform	Image	masks	BBoxes
ToTensor	✓	✓	✓
Normalize	✓	✓	✓
ToGray	✓	✓	✓
GaussianBlur	✓	✓	✓
RandomNoise	✓	✓	✓
RandomBrightness	✓	✓	✓
RandomContrast	✓	✓	✓

spatial-level

Spatial-level transforms will simultaneously change both an input image as well as additional targets such as masks, bounding boxes. It support all channel images.

Transform	Image	masks	BBoxes
Resize	✓	✓	✓
Pad	✓	✓	✓
RandomHorizontalFlip	✓	✓	✓
RandomVerticalFlip	✓	✓	✓
RandomFlip	✓	✓	✓
CenterCrop	✓	✓	✓
RandomCrop	✓	✓	✓
RandomResizedCrop	✓	✓	✓
ElasticTransform	✓	✓
RandomRotation	✓	✓
RandomShift	✓	✓

Models

Classification

All models support multi-channels as input (e.g. 8 channels).

• VGG: vgg11, vgg11_bn, vgg13, vgg13_bn, vgg16, vgg16_bn,vgg19_bn, vgg19
• ResNet: resnet18, resnet34, restnet50, resnet101, resnet152
• DenseNet: densenet121, densenet169, densenet201, densenet161
• Inception: inception_v3
• MobileNet: mobilenet_v2

Sementic Segmentation

• UNet: unet: unet11, unet101, unet152 (with resnet as backbone.)
• PSPNet(TODO):
• DeepLab(TODO):

Object Detection

• SSD(TODO)
• YOLO(TODO)
• FasterRCNN(TODO)

Dataloader

Classification

• SAT-4 and SAT-6 airborne datasets
• EuroSat
• PatternNet
• NWPU_redisc45

Sementic Segmentation

Object Detection

Reference

• torchvision

Note

• If you are looking for the torchvision-enhance, please checkout the enhance branch. But it was deprecated.