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Task_1/fets_challenge/README.md

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+Instructions for challenge organizer (Participants, ignore this)
+
+During testing phase:
+- first generate a csv file for the testing set per the "create_test_csv.py" script
+- use "generate_predictions.py" to run inference using the generated csv (final_test.csv)

Task_1/fets_challenge/create_test_csv.py

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+import os
+import csv
+
+# This script generates a CSV file named 'final_test.csv' in the current directory.
+# The CSV file has two columns: 'Partition_ID' and 'Subject_ID'.
+# 'Partition_ID' is set to -1 for all rows.
+# 'Subject_ID' is populated with the names of folders in the specified directory.
+# This is intended to replicate the format of 'validation.csv' in the FeTS Challenge repository.
+# The generated CSV file can be used to list all test samples in your data path.
+
+# Specify the directory containing the test data folders
+data_dir = "/home/locolinux2/datasets/RSNA_ASNR_MICCAI_BraTS2021_TestingData"
+
+dir_list = [d for d in os.listdir(data_dir) if os.path.isdir(os.path.join(data_dir, d))]
+
+output_csv =  '/home/locolinux2/.local/workspace/final_test.csv'
+
+# Write the CSV file
+with open(output_csv, mode='w', newline='') as file:
+    writer = csv.writer(file)
+    writer.writerow(['Partition_ID', 'Subject_ID'])
+
+    for directory in dir_list:
+        writer.writerow(['-1', directory])
+
+print(f'CSV file "{output_csv}" has been created with the folder names.')