diff --git a/utils/datasets.py b/utils/datasets.py
index 35f7c702..ff1a0a11 100755
--- a/utils/datasets.py
+++ b/utils/datasets.py
@@ -131,15 +131,20 @@ class LoadWebcam:  # for inference
 class LoadImagesAndLabels(Dataset):  # for training/testing
     def __init__(self, path, img_size=416, augment=False):
         with open(path, 'r') as file:
-            self.img_files = file.read().splitlines()
-            self.img_files = list(filter(lambda x: len(x) > 0, self.img_files))
-        assert len(self.img_files) > 0, 'No images found in %s' % path
+            img_files = file.read().splitlines()
+            self.img_files = list(filter(lambda x: len(x) > 0, img_files))
+
+        n = len(self.img_files)
+        assert n > 0, 'No images found in %s' % path
         self.img_size = img_size
         self.augment = augment
         self.label_files = [
             x.replace('images', 'labels').replace('.bmp', '.txt').replace('.jpg', '.txt').replace('.png', '.txt')
             for x in self.img_files]
 
+        if n < 200:  # preload all images into memory if possible
+            self.imgs = (cv2.imread(img_files[i]) for i in range(n))
+
     def __len__(self):
         return len(self.img_files)
 
@@ -147,7 +152,10 @@ class LoadImagesAndLabels(Dataset):  # for training/testing
         img_path = self.img_files[index]
         label_path = self.label_files[index]
 
-        img = cv2.imread(img_path)  # BGR
+        if hasattr(self, 'imgs'):
+            img = self.imgs[index]  # BGR
+        else:
+            img = cv2.imread(img_path)  # BGR
         assert img is not None, 'File Not Found ' + img_path
 
         augment_hsv = True