Leaderboard B - Windows Support (workaround)

README.md

@@ -1,4 +1,5 @@
 ## MDX-Net Track B Submission
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Ma5onic/mdx-net-submission/leaderboard_B)
 
 This branch contains the source code and the pretrained model that is submitted to the [Sony MDX Challenge](https://www.aicrowd.com/challenges/music-demixing-challenge-ismir-2021) Track B.
 
@@ -60,4 +61,4 @@ Just do
 conda activate mdx-submit
 ```
 
-to go back into the environment you have installed MDX's dependencies in.
+to go back into the environment you have installed MDX's dependencies in.

evaluator/music_demixing.py

@@ -10,6 +10,7 @@
 from contextlib import contextmanager
 from os import listdir
 from os.path import isfile, join
+from sys import platform
 
 import soundfile as sf
 import numpy as np
@@ -21,15 +22,18 @@ class TimeoutException(Exception): pass
 
 @contextmanager
 def time_limit(seconds):
-    def signal_handler(signum, frame):
-        raise TimeoutException("Prediction timed out!")
-
-    signal.signal(signal.SIGALRM, signal_handler)
-    signal.alarm(seconds)
-    try:
+    if platform != "win32":
+        def signal_handler(signum, frame):
+            raise TimeoutException("Prediction timed out!")
+
+            signal.signal(signal.SIGALRM, signal_handler)
+            signal.alarm(seconds)
+            try:
+                yield
+            finally:
+                signal.alarm(0)
+    else:
         yield
-    finally:
-        signal.alarm(0)
 
 
 class MusicDemixingPredictor:

predict_blend.py

@@ -57,7 +57,10 @@ def demix_base(self, mix):
                 tar_signal = tar_waves[:,:,trim:-trim].transpose(0,1).reshape(2, -1).numpy()[:, :-pad]
 
             sources.append(tar_signal)
+        print("\n======================================")
+        print("Time to execute demix_base(self, mix):")
         print(time()-start_time)
+        print("======================================\n")
         return np.array(sources)
 
     def demix_demucs(self, mix):
@@ -71,7 +74,10 @@ def demix_demucs(self, mix):
 
         sources = (sources * ref.std() + ref.mean()).cpu().numpy()
         sources[[0,1]] = sources[[1,0]]
+        print("\n========================================")
+        print("Time to execute demix_demucs(self, mix):")
         print(time() - start_time)
+        print("========================================\n")
         return sources