Added get_logger convenience method; logging in compute

demo/src/compute.py

@@ -1,11 +1,17 @@
 import subprocess as sp
 
+from .logger import get_logger
+
+
+LOGGER = get_logger()
+
 
 def run_model(fixed_path=None, moving_path=None, fixed_seg_path=None, moving_seg_path=None, output_path=None, task="B"):
     if (fixed_seg_path is None) or (moving_seg_path is None):
-        print("The fixed or moving segmentation were not provided and are thus ignored for inference.")
+        LOGGER.info("The fixed or moving segmentation were not provided and are thus ignored for inference.")
         sp.check_call(["ddmr", "-f", fixed_path, "-m", moving_path, \
                     "-o", output_path, "-a", task, "--model", "BL-NS", "--original-resolution"])
     else:
+        LOGGER.info("All four inputs were successfully provided.")
         sp.check_call(["ddmr", "-f", fixed_path, "-m", moving_path, "-fs", fixed_seg_path, "-ms", moving_seg_path,
                     "-o", output_path, "-a", task, "--model", "BL-NS", "--original-resolution"])

demo/src/gui.py

@@ -1,6 +1,3 @@
-import logging
-import sys
-
 import gradio as gr
 
 from .compute import run_model

demo/src/logger.py

@@ -2,6 +2,10 @@ import logging
 import sys
 
 
+def get_logger():
+    logging.getLogger(__name__)
+
+
 def setup_logger():
     # clear log
     file_to_delete = open("log.log",'w')
@@ -17,7 +21,7 @@ def setup_logger():
         handlers=handlers,
     )
 
-    return logging.getLogger(__name__)
+    return get_logger()
 
 
 def read_logs():