Update probability to p (#3980)

utils/datasets.py

@@ -22,7 +22,7 @@ from PIL import Image, ExifTags
 from torch.utils.data import Dataset
 from tqdm import tqdm
 
-from utils.augmentations import Albumentations, augment_hsv, copy_paste, letterbox, mixup, random_perspective
+from utils.augmentations import Albumentations, augment_hsv, copy_paste, letterbox, mixup, random_perspective, cutout
 from utils.general import check_requirements, check_file, check_dataset, xywh2xyxy, xywhn2xyxy, xyxy2xywhn, \
     xyn2xy, segments2boxes, clean_str
 from utils.torch_utils import torch_distributed_zero_first
@@ -572,8 +572,7 @@ class LoadImagesAndLabels(Dataset):  # for training/testing
                     labels[:, 1] = 1 - labels[:, 1]
 
             # Cutouts
-            # if random.random() < 0.9:
-            #     labels = cutout(img, labels)
+            # labels = cutout(img, labels, p=0.5)
 
         labels_out = torch.zeros((nl, 6))
         if nl:
@@ -682,7 +681,7 @@ def load_mosaic(self, index):
     # img4, labels4 = replicate(img4, labels4)  # replicate
 
     # Augment
-    img4, labels4, segments4 = copy_paste(img4, labels4, segments4, probability=self.hyp['copy_paste'])
+    img4, labels4, segments4 = copy_paste(img4, labels4, segments4, p=self.hyp['copy_paste'])
     img4, labels4 = random_perspective(img4, labels4, segments4,
                                        degrees=self.hyp['degrees'],
                                        translate=self.hyp['translate'],