Update datasets.py

utils/datasets.py

@@ -56,10 +56,10 @@ def exif_size(img):
 
 
 def create_dataloader(path, imgsz, batch_size, stride, opt, hyp=None, augment=False, cache=False, pad=0.0, rect=False,
-                      rank=-1, world_size=1, workers=8, data_type="train", image_weights=False, quad=False, prefix=''):
+                      rank=-1, world_size=1, workers=8, image_weights=False, quad=False, prefix=''):
     # Make sure only the first process in DDP process the dataset first, and the following others can use the cache
     with torch_distributed_zero_first(rank):
-        dataset = LoadImagesAndLabels(path, imgsz, batch_size, data_type=data_type,
+        dataset = LoadImagesAndLabels(path, imgsz, batch_size,
                                       augment=augment,  # augment images
                                       hyp=hyp,  # augmentation hyperparameters
                                       rect=rect,  # rectangular training
@@ -337,7 +337,7 @@ def img2label_paths(img_paths):
 
 
 class LoadImagesAndLabels(Dataset):  # for training/testing
-    def __init__(self, path, img_size=640, batch_size=16, data_type="train", augment=False, hyp=None, rect=False, image_weights=False,
+    def __init__(self, path, img_size=640, batch_size=16, augment=False, hyp=None, rect=False, image_weights=False,
                  cache_images=False, single_cls=False, stride=32, pad=0.0, prefix=''):
         self.img_size = img_size
         self.augment = augment