Merge pull request #10 from IBM/extend/docs

Updating installation guide

Author: CarlosGomes98

README.md

@@ -16,7 +16,8 @@ The library provides:
 ### Pip
 In order to use th file `pyproject.toml` it is necessary to guarantee `pip>=21.8`. If necessary upgrade `pip` using `python -m pip install --upgrade pip`. 
 
-Install the library with `pip install git+https://github.com/IBM/terratorch.git`.
+For a stable point-release, use `pip install terratorch`. 
+If you prefer to get the most recent version of the main branch, install the library with `pip install git+https://github.com/IBM/terratorch.git`.
 
 TerraTorch requires gdal to be installed, which can be quite a complex process. If you don't have GDAL set up on your system, we reccomend using a conda environment and installing it with `conda install -c conda-forge gdal`.
 

docs/quick_start.md

@@ -4,7 +4,8 @@ To get started, make sure to have [PyTorch](https://pytorch.org/get-started/loca
 
 Installing GDAL can be quite a complex process. If you don't have GDAL set up on your system, we reccomend using a conda environment and installing it with `conda install -c conda-forge gdal`.
 
-Install TerraTorch with `pip install git+https://github.com/IBM/terratorch.git`
+For a stable point-release, use `pip install terratorch`. 
+If you prefer to get the most recent version of the main branch, install the library with `pip install git+https://github.com/IBM/terratorch.git`.
 
 To install as a developer (e.g. to extend the library) clone this repo, and run `pip install -e .`.
 
@@ -235,4 +236,4 @@ To run this training task, simply execute `terratorch fit --config <path_to_conf
 
 To test your model on the test set, execute `terratorch test --config  <path_to_config_file> --ckpt_path <path_to_checkpoint_file>`
 
-For inference, execute `terratorch predict -c <path_to_config_file> --ckpt_path<path_to_checkpoint> --predict_output_dir <path_to_output_dir> --data.init_args.predict_data_root <path_to_input_dir> --data.init_args.predict_dataset_bands <all bands in the predicted dataset, e.g. [BLUE,GREEN,RED,NIR_NARROW,SWIR_1,SWIR_2,0]>`
+For inference, execute `terratorch predict -c <path_to_config_file> --ckpt_path<path_to_checkpoint> --predict_output_dir <path_to_output_dir> --data.init_args.predict_data_root <path_to_input_dir> --data.init_args.predict_dataset_bands <all bands in the predicted dataset, e.g. [BLUE,GREEN,RED,NIR_NARROW,SWIR_1,SWIR_2,0]>`