File rename: nwpu.py -> vhr10.py

README.md

@@ -114,7 +114,7 @@ for batch in dataloader:
     # train a model, or make predictions using a pre-trained model
 ```
 
-<img src="https://raw.githubusercontent.com/microsoft/torchgeo/main/images/vhr10.png" alt="Example predictions from a Mask R-CNN model trained on the NWPU VHR-10 dataset"/>
+<img src="https://raw.githubusercontent.com/microsoft/torchgeo/main/images/vhr10.png" alt="Example predictions from a Mask R-CNN model trained on the VHR-10 dataset"/>
 
 All TorchGeo datasets are compatible with PyTorch data loaders, making them easy to integrate into existing training workflows. The only difference between a benchmark dataset in TorchGeo and a similar dataset in torchvision is that each dataset returns a dictionary with keys for each PyTorch `Tensor`.
 

docs/api/datasets.rst

@@ -312,8 +312,8 @@ Vaihingen
 
 .. autoclass:: Vaihingen2D
 
-NWPU VHR-10
-^^^^^^^^^^^
+VHR-10
+^^^^^^
 
 .. autoclass:: VHR10
 

docs/api/non_geo_datasets.csv

@@ -32,6 +32,6 @@ Dataset,Task,Source,# Samples,# Classes,Size (px),Resolution (m),Bands
 `UC Merced`_,C,USGS National Map,"21,000",21,256x256,0.3,RGB
 `USAVars`_,R,NAIP Aerial,100K,-,-,4,"RGB, NIR"
 `Vaihingen`_,S,Aerial,33,6,"1,281--3,816",0.09,RGB
-`NWPU VHR-10`_,I,"Google Earth, Vaihingen",800,10,"358--1,728",0.08--2,RGB
+`VHR-10`_,I,"Google Earth, Vaihingen",800,10,"358--1,728",0.08--2,RGB
 `xView2`_,CD,Maxar,"3,732",4,"1,024x1,024",0.8,RGB
 `ZueriCrop`_,"I, T",Sentinel-2,116K,48,24x24,10,MSI

tests/datasets/test_utils.py

@@ -87,7 +87,7 @@ def test_mock_missing_module(mock_missing_module: None) -> None:
     [
         os.path.join("cowc_detection", "COWC_Detection_Columbus_CSUAV_AFRL.tbz"),
         os.path.join("cowc_detection", "COWC_test_list_detection.txt.bz2"),
-        os.path.join("nwpu", "NWPU VHR-10 dataset.rar"),
+        os.path.join("vhr10", "NWPU VHR-10 dataset.rar"),
         os.path.join("landcoverai", "landcover.ai.v1.zip"),
         os.path.join("chesapeake", "BAYWIDE", "Baywide_13Class_20132014.zip"),
         os.path.join("sen12ms", "ROIs1158_spring_lc.tar.gz"),
@@ -107,7 +107,7 @@ def test_missing_rarfile(mock_missing_module: None) -> None:
         match="rarfile is not installed and is required to extract this dataset",
     ):
         extract_archive(
-            os.path.join("tests", "data", "nwpu", "NWPU VHR-10 dataset.rar")
+            os.path.join("tests", "data", "vhr10", "NWPU VHR-10 dataset.rar")
         )
 
 

tests/datasets/test_nwpu.py → tests/datasets/test_vhr10.py

@@ -31,13 +31,13 @@ def dataset(
         self, monkeypatch: MonkeyPatch, tmp_path: Path, request: SubRequest
     ) -> VHR10:
         pytest.importorskip("rarfile", minversion="3")
-        monkeypatch.setattr(torchgeo.datasets.nwpu, "download_url", download_url)
+        monkeypatch.setattr(torchgeo.datasets.vhr10, "download_url", download_url)
         monkeypatch.setattr(torchgeo.datasets.utils, "download_url", download_url)
-        url = os.path.join("tests", "data", "nwpu", "NWPU VHR-10 dataset.rar")
+        url = os.path.join("tests", "data", "vhr10", "NWPU VHR-10 dataset.rar")
         monkeypatch.setitem(VHR10.image_meta, "url", url)
         md5 = "5fddb0dfd56a80638831df9f90cbf37a"
         monkeypatch.setitem(VHR10.image_meta, "md5", md5)
-        url = os.path.join("tests", "data", "nwpu", "annotations.json")
+        url = os.path.join("tests", "data", "vhr10", "annotations.json")
         monkeypatch.setitem(VHR10.target_meta, "url", url)
         md5 = "833899cce369168e0d4ee420dac326dc"
         monkeypatch.setitem(VHR10.target_meta, "md5", md5)

torchgeo/datasets/__init__.py

@@ -74,7 +74,6 @@
 from .millionaid import MillionAID
 from .naip import NAIP
 from .nasa_marine_debris import NASAMarineDebris
-from .nwpu import VHR10
 from .openbuildings import OpenBuildings
 from .oscd import OSCD
 from .patternnet import PatternNet
@@ -105,6 +104,7 @@
     unbind_samples,
 )
 from .vaihingen import Vaihingen2D
+from .vhr10 import VHR10
 from .xview import XView2
 from .zuericrop import ZueriCrop
 

torchgeo/datasets/resisc45.py

@@ -15,7 +15,7 @@
 
 
 class RESISC45(NonGeoClassificationDataset):
-    """RESISC45 dataset.
+    """NWPU-RESISC45 dataset.
 
     The `RESISC45 <http://www.escience.cn/people/JunweiHan/NWPU-RESISC45.html>`__
     dataset is a dataset for remote sensing image scene classification.