improved classify script

classify

@@ -25,7 +25,7 @@ def main():
 	parser.add_argument('--cpu', action='store_true', help='run on cpu')
 	parser.add_argument('--batch', type=int, default=10000, help='batch size')
 	parser.add_argument('--move', type=float, help='move files with certainty above the threshold')
-	parser.add_argument('--workers', type=int, help='max number of data loader workers', default=nproc)
+	parser.add_argument('--workers', type=int, default=nproc, help='max number of data loader workers')
 #	parser.add_argument('--train', action='store_true', help='train the model')
 #	parser.add_argument('--watch', type=str, help='folder to watch for images to classify')
 #	parser.add_argument('--folder', type=str, default='.', help='folder with images to classify (or train)')
@@ -60,17 +60,6 @@ def main():
 	else:
 		predict_in_batches(learn)
 
-
-#def debogrify_stdout():
-#	""" deal with some bogus output to stdout from pytorch or something """
-#	stdout_fd = sys.stdout.fileno()
-#	stderr_fd = sys.stderr.fileno()
-#	new_stdout_fd = os.dup(stdout_fd)
-#	os.dup2(stderr_fd, stdout_fd)
-#	out = os.fdopen(new_stdout_fd, "w")
-#	return out
-
-
 def predict_one_at_time(learn):
 	for filename in sys.stdin:
 		filename = filename.rstrip()