Sathya77/swin-transformer-satellite

Swin Transformer — Satellite Image Classification

PyTorch implementation of Swin Transformer (Liu et al. 2021) trained on NWPU-RESISC45 satellite imagery dataset.

Model Details

Classes

airplane, airport, baseballdiamond, basketballcourt, beach, bridge, chaparral, church, circularfarmland, cloud, commercialarea, denseresidential, desert, forest, freeway, golfcourse, groundtrackfield, harbor, industrialarea, intersection, island, lake, meadow, mediumresidential, mobilehomepark, mountain, overpass, palace, parkinglot, railway, railwaystation, rectangularfarmland, river, roundabout, runway, seaice, ship, snowberg, sparseresidential, stadium, storagetank, tenniscourt, terrace, thermalpower_station, wetland

Usage

from huggingface_hub import hf_hub_download
import torch
from torchvision import transforms
from PIL import Image

checkpoint = torch.load(
    hf_hub_download("Sathya77/swin-transformer-satellite", "swin_resisc45.pth"),
    map_location='cpu'
)

model = SwinTransformer(embed_dim=96, num_classes=45)
model.load_state_dict(checkpoint['model_state_dict'])
model.eval()

Live Demo

Try it here: Sathya77/swin-transformer-satellite

References

• —Swin Transformer Paper — Liu et al. 2021
• —NWPU-RESISC45 Dataset