Merge pull request #4 from pnlbwh/revert-3-revise-installation

Revert "Revise installation infrastructure"

HD_BET/paths.py

@@ -1,4 +1,4 @@
-from os.path import dirname, abspath, join as pjoin
+import os
 
 # please refer to the readme on where to get the parameters. Save them in this folder:
-folder_with_parameter_files = pjoin(dirname(abspath(__file__)),'params')
+folder_with_parameter_files = os.path.join(os.path.expanduser('~'), 'hd-bet_params')

readme.md

@@ -26,37 +26,30 @@ coefficient and -0.80 to -2.75 mm for the Hausdorff distance (Bonferroni-adjuste
 - HD-BET is very fast on GPU with <10s run time per MRI sequence. Even on CPU it is not slower than other commonly 
 used tools.
 
-## Installation Instructions
-
-Psychiatry Neuroimaging Laboratory has redefined the installation scheme for this program to work on
-all modern GPUs: RTX 4080, RTX 4090, RTX A6000, A100, and GTX 1080. This redefinition came out of days of research
-at Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, Massachusetts. The steps are:
+## Installation Instructions 
+Note that you need to have a python3 installation for HD-BET to work. Please also make sure to install HD-BET with the
+correct pip version (the one that is connected to python3). You can verify this using the `--version` command:
 
 ```
-conda create -y -n hd-bet python=3.6
-conda activate hd-bet
-
-git clone --single-branch --branch pnl [email protected]:pnlbwh/HD-BET.git
-cd HD-BET/
-pip install .
-
-conda install pytorch torchvision pytorch-cuda=12.1 -c pytorch -c nvidia
+(dl_venv) fabian@Fabian:~$ pip --version
+pip 20.0.2 from /home/fabian/dl_venv/lib/python3.6/site-packages/pip (python 3.6)
 ```
 
-The last `pytorch-cuda=12.1` makes it possible to run `hd-bet` on our GPUs that are CUDA `v12.*` compatible.
-Both channels `-c pytorch -c nvidia` are necessary to install dependencies of `pytorch-cuda=12.1`
-
-After completing installation, you can invoke `hd-bet` by absolute path without sourcing or activating any environment:
-
-> /path/to/miniconda3/envs/hd-bet/bin/hd-bet --help
+If it does not show python 3.X, you can try pip3. If that also does not work you probably need to install python3 first.
 
-<details><summary>References</summary>
-
-* https://anaconda.org/pytorch/pytorch-cuda/files
-* https://www.reddit.com/r/pytorch/comments/11z9vkf/pytorch_installation_with_cuda_121/
-* https://pytorch.org/get-started/locally/
+Once python 3 and pip are set up correctly, run the following commands to install HD-BET:
+1) Clone this repository:
+    ```bash
+    git clone https://github.com/MIC-DKFZ/HD-BET
+    ```
+2) Go into the repository (the folder with the setup.py file) and install:
+    ```
+    cd HD-BET
+    pip install -e .
+    ```
+3) Per default, model parameters will be downloaded to ~/hd-bet_params. If you wish to use a different folder, open 
+HD_BET/paths.py in a text editor and modify ```folder_with_parameter_files```
 
-</details>
 
 ## How to use it 
 
@@ -129,4 +122,4 @@ This depends on your MRI image size. Typical run times (preprocessing, postproce
 
 <sup>1</sup>https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Fslutils
 
-<sup>2</sup>https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Orientation%20Explained
+<sup>2</sup>https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Orientation%20Explained

requirements.txt

@@ -1,3 +1,4 @@
 numpy>=1.14.5
+torch>=0.4.0
 scikit-image>=0.14.0
 SimpleITK==2.0.2