Update info on LightningCLI (#1628)

* Add info

* Address comments

README.md

@@ -146,12 +146,66 @@ trainer.fit(model=task, datamodule=datamodule)
 
 <img src="https://raw.githubusercontent.com/microsoft/torchgeo/main/images/inria.png" alt="Building segmentations produced by a U-Net model trained on the Inria Aerial Image Labeling dataset"/>
 
-In our GitHub repo, we provide `train.py` and `evaluate.py` scripts to train and evaluate the performance of models using these datamodules and trainers. These scripts are configurable via the command line and/or via YAML configuration files. See the [conf](https://github.com/microsoft/torchgeo/blob/main/conf) directory for example configuration files that can be customized for different training runs.
+TorchGeo also supports command-line interface training using [LightningCLI](https://lightning.ai/docs/pytorch/stable/cli/lightning_cli.html). It can be invoked in two ways:
 
 ```console
-$ python train.py config_file=conf/landcoverai.yaml
+# If torchgeo has been installed
+torchgeo
+# If torchgeo has been installed, or if it has been cloned to the current directory
+python3 -m torchgeo
 ```
 
+It supports command-line configuration or YAML/JSON config files. Valid options can be found from the help messages:
+
+```console
+# See valid stages
+torchgeo --help
+# See valid trainer options
+torchgeo fit --help
+# See valid model options
+torchgeo fit --model.help ClassificationTask
+# See valid data options
+torchgeo fit --data.help EuroSAT100DataModule
+```
+
+Using the following config file:
+```yaml
+trainer:
+  max_epochs: 20
+model:
+  class_path: ClassificationTask
+  init_args:
+    model: "resnet18"
+    in_channels: 13
+    num_classes: 10
+data:
+  class_path: EuroSAT100DataModule
+  init_args:
+    batch_size: 8
+  dict_kwargs:
+    download: true
+```
+
+we can see the script in action:
+```console
+# Train and validate a model
+torchgeo fit --config config.yaml
+# Validate-only
+torchgeo validate --config config.yaml
+# Calculate and report test accuracy
+torchgeo test --config config.yaml --trainer.ckpt_path=...
+```
+
+It can also be imported and used in a Python script if you need to extend it to add new features:
+
+```python
+from torchgeo.main import main
+
+main(["fit", "--config", "config.yaml"])
+```
+
+See the [Lightning documentation](https://lightning.ai/docs/pytorch/stable/cli/lightning_cli.html) for more details.
+
 ## Citation
 
 If you use this software in your work, please cite our [paper](https://dl.acm.org/doi/10.1145/3557915.3560953):