diff --git a/utils/general.py b/utils/general.py
index 239683d..8f29d1a 100755
--- a/utils/general.py
+++ b/utils/general.py
@@ -9,7 +9,7 @@ import logging
 from contextlib import contextmanager
 from copy import copy
 from pathlib import Path
-from sys import platform
+import platform
 
 import cv2
 import matplotlib
@@ -66,7 +66,7 @@ def get_latest_run(search_dir='./runs'):
 
 def check_git_status():
     # Suggest 'git pull' if repo is out of date
-    if platform in ['linux', 'darwin'] and not os.path.isfile('/.dockerenv'):
+    if platform.system() in ['Linux', 'Darwin'] and not os.path.isfile('/.dockerenv'):
         s = subprocess.check_output('if [ -d .git ]; then git fetch && git status -uno; fi', shell=True).decode('utf-8')
         if 'Your branch is behind' in s:
             print(s[s.find('Your branch is behind'):s.find('\n\n')] + '\n')
@@ -126,7 +126,7 @@ def check_anchor_order(m):
 
 
 def check_file(file):
-    # Searches for file if not found locally
+    # Search for file if not found
     if os.path.isfile(file) or file == '':
         return file
     else:
@@ -137,21 +137,25 @@ def check_file(file):
 
 def check_dataset(dict):
     # Download dataset if not found
-    train, val = os.path.abspath(dict['train']), os.path.abspath(dict['val'])  # data paths
-    if not (os.path.exists(train) and os.path.exists(val)):
-        print('\nWARNING: Dataset not found, nonexistant paths: %s' % [train, val])
-        if 'download' in dict:
-            s = dict['download']
-            print('Attempting autodownload from: %s' % s)
-            if s.startswith('http') and s.endswith('.zip'):  # URL
-                f = Path(s).name  # filename
-                torch.hub.download_url_to_file(s, f)
-                r = os.system('unzip -q %s -d ../ && rm %s' % (f, f))
-            else:  # bash script
-                r = os.system(s)
-            print('Dataset autodownload %s\n' % ('success' if r == 0 else 'failure'))  # analyze return value
-        else:
-            Exception('Dataset autodownload unavailable.')
+    val, s = dict.get('val'), dict.get('download')
+    if val and len(val):
+        val = [os.path.abspath(x) for x in (val if isinstance(val, list) else [val])]  # val path
+        if not all(os.path.exists(x) for x in val):
+            print('\nWARNING: Dataset not found, nonexistant paths: %s' % [*val])
+            if s and len(s):  # download script
+                print('Attempting autodownload from: %s' % s)
+                if s.startswith('http') and s.endswith('.zip'):  # URL
+                    f = Path(s).name  # filename
+                    if platform.system() == 'Darwin':  # avoid MacOS python requests certificate error
+                        os.system('curl -L %s -o %s' % (s, f))
+                    else:
+                        torch.hub.download_url_to_file(s, f)
+                    r = os.system('unzip -q %s -d ../ && rm %s' % (f, f))  # unzip
+                else:  # bash script
+                    r = os.system(s)
+                print('Dataset autodownload %s\n' % ('success' if r == 0 else 'failure'))  # analyze return value
+            else:
+                raise Exception('Dataset not found.')
 
 
 def make_divisible(x, divisor):