Skip to content

Commit d9e8c6b

Browse files
authored
Update 2022-6-12-geospatial-deep-learning-with-torchgeo.md
Remove code block
1 parent 54658e5 commit d9e8c6b

File tree

1 file changed

+0
-2
lines changed

1 file changed

+0
-2
lines changed

_posts/2022-6-12-geospatial-deep-learning-with-torchgeo.md

Lines changed: 0 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -60,9 +60,7 @@ At the moment, it can be quite challenging to work with both deep learning model
6060

6161
TorchGeo is not just a research project, but a production-quality library that uses continuous integration to test every commit with a range of Python versions on a range of platforms (Linux, macOS, Windows). It can be easily installed with any of your favorite package managers, including pip, conda, and [spack](https://spack.io):
6262

63-
```Python
6463
$ pip install torchgeo
65-
```
6664

6765
TorchGeo is designed to have the same API as other PyTorch domain libraries like torchvision, torchtext, and torchaudio. If you already use torchvision in your workflow for computer vision datasets, you can switch to TorchGeo by changing only a few lines of code. All TorchGeo datasets and samplers are compatible with the PyTorch DataLoader class, meaning that you can take advantage of wrapper libraries like [PyTorch Lightning](https://www.pytorchlightning.ai/) for distributed training. In the following sections, we'll explore possible use cases for TorchGeo to show how simple it is to use.
6866

0 commit comments

Comments
 (0)