Merge the Updated Codebase

.gitignore

@@ -1,2 +1,6 @@
 Task_1/venv/*
+Task_1/my_code
+Task_1/ucb_r*
 Task_1/fets_challenge/__pycache__/*
+*pycache*
+Task_1/cert*

Task_1/.gitignore

@@ -0,0 +1,8 @@
+FeTS_Challenge-flair.py
+FeTS_Challenge_FedPOD_partitioning2.py
+FeTS_Challenge_RL.py
+FeTS_Challenge_RecEng.py
+FeTS_Challenge_leonardklausman.py
+*final_submission*
+build*
+cert*

Task_1/FeTS_Challenge.py

@@ -14,7 +14,7 @@
 
 import os
 import numpy as np
-
+from pathlib import Path
 from fets_challenge import run_challenge_experiment
 
 
@@ -518,15 +518,23 @@ def FedAvgM_Selection(local_tensors,
 # to those you specify immediately above. Changing the below value to False will change 
 # this fact, excluding the three hausdorff measurements. As hausdorff distance is 
 # expensive to compute, excluding them will speed up your experiments.
-include_validation_with_hausdorff=True
+include_validation_with_hausdorff=True # IF SET TO FALSE WHOLE CODE RUNS SEGMENTATION FOR SOME REASON
 
 # We encourage participants to experiment with partitioning_1 and partitioning_2, as well as to create
 # other partitionings to test your changes for generalization to multiple partitionings.
 #institution_split_csv_filename = 'partitioning_1.csv'
-institution_split_csv_filename = 'small_split.csv'
+#institution_split_csv_filename = 'partitioning_1.csv'
+
+
+# Dynamically get working directory or environment variable
+data_root = Path.cwd() / 'datasets' / 'MICCAI_FeTS2022_TrainingData'
+institution_split_csv_filename = '/home/locolinux2/datasets/MICCAI_FeTS2022_TrainingData/partitioning_2.csv' 
+institution_split_csv_filename = data_root / 'sanity_partitioning.csv'
+
 
 # change this to point to the parent directory of the data
-brats_training_data_parent_dir = '/raid/datasets/FeTS22/MICCAI_FeTS2022_TrainingData'
+data_root = Path.cwd() / 'datasets' / 'MICCAI_FeTS2022_TrainingData'
+brats_training_data_parent_dir = Path.cwd() / 'datasets' / 'MICCAI_FeTS2022_Resized'
 
 # increase this if you need a longer history for your algorithms
 # decrease this if you need to reduce system RAM consumption
@@ -537,7 +545,7 @@ def FedAvgM_Selection(local_tensors,
 
 # you'll want to increase this most likely. You can set it as high as you like, 
 # however, the experiment will exit once the simulated time exceeds one week. 
-rounds_to_train = 5
+rounds_to_train = 20
 
 # (bool) Determines whether checkpoints should be saved during the experiment. 
 # The checkpoints can grow quite large (5-10GB) so only the latest will be saved when this parameter is enabled
@@ -579,7 +587,6 @@ def FedAvgM_Selection(local_tensors,
 
 
 from fets_challenge import model_outputs_to_disc
-from pathlib import Path
 
 # infer participant home folder
 home = str(Path.home())

Task_1/README.md

@@ -20,18 +20,18 @@ Please ask any additional questions in our discussion pages on our github site a
 2. ```git clone https://github.com/FETS-AI/Challenge.git```
 3. ```cd Challenge/Task_1```
 4. ```git lfs pull```
-5. Create virtual environment (python 3.6-3.8): using Anaconda, a new environment can be created and activated using the following commands: 
+5. Create virtual environment (python 3.9): using Anaconda, a new environment can be created and activated using the following commands: 
     ```sh
     ## create venv in specific path
-    conda create -p ./venv python=3.7 -y
+    conda create -p ./venv python=3.9 -y
     conda activate ./venv
     ```
 6. ```pip install --upgrade pip```
-7. Install Pytorch LTS (1.8.2) for your system (use CUDA 11):
-   ```pip3 install torch==1.8.2 torchvision==0.9.2 torchaudio==0.8.2 --extra-index-url https://download.pytorch.org/whl/lts/1.8/cu111```
-*Note all previous versions of pytorch can be found in [these instructions]([https://pytorch.org/get-started/locally/](https://pytorch.org/get-started/previous-versions/))
-9. Set the environment variable `SKLEARN_ALLOW_DEPRECATED_SKLEARN_PACKAGE_INSTALL=True` (to avoid sklearn deprecation error)
-10. ```pip install .``` 
+7. Install Pytorch (2.3.1) for your system:
+   ```pip install torch==2.3.1 torchvision==0.18.1```
+*Note all previous versions of pytorch can be found in [this link](https://pytorch.org/get-started/previous-versions/#v231).
+8. Set the environment variable `SKLEARN_ALLOW_DEPRECATED_SKLEARN_PACKAGE_INSTALL=True` (to avoid sklearn deprecation error)
+9. ```pip install .``` 
 > * _Note: if you run into ```ERROR: Failed building wheel for SimpleITK```, try running ```pip install SimpleITK --only-binary :all:``` then rerunning ```pip install .```_
 10. ```python FeTS_Challenge.py```
 > * _Note_: if you run into ```ImportError: /home/locolinux/FETS2024/fets2024env/bin/../lib/libstdc++.so.6: version GLIBCXX_3.4.30' not found (required by /home/locolinux/FETS2024/fets2024env/lib/python3.7/site-packages/SimpleITK/_SimpleITK.so)```, try installing a previous version of SimpleITK (version 2.2.0 works)

Task_1/fets_challenge/custom_aggregation_wrapper.py

@@ -1,4 +1,4 @@
-from openfl.component.aggregation_functions.experimental import PrivilegedAggregationFunction
+from openfl.interface.aggregation_functions.experimental import PrivilegedAggregationFunction
 
 
 # extends the openfl agg func interface to include challenge-relevant information