ultralytics 8.0.34 security updates and fixes (#924)

Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
Co-authored-by: Fabian Greavu <fabiangreavu@gmail.com>
Co-authored-by: Yonghye Kwon <developer.0hye@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

ultralytics/yolo/data/dataloaders/stream_loaders.py

@@ -291,7 +291,7 @@ class LoadPilAndNumpy:
         self.mode = 'image'
         # generate fake paths
         self.paths = [f"image{i}.jpg" for i in range(len(self.im0))]
-        self.bs = 1
+        self.bs = len(self.im0)
 
     @staticmethod
     def _single_check(im):

ultralytics/yolo/data/dataloaders/v5loader.py

@@ -34,6 +34,7 @@ from ultralytics.yolo.utils.checks import check_requirements, check_yaml
 from ultralytics.yolo.utils.downloads import unzip_file
 from ultralytics.yolo.utils.ops import clean_str, segments2boxes, xyn2xy, xywh2xyxy, xywhn2xyxy, xyxy2xywhn
 from ultralytics.yolo.utils.torch_utils import torch_distributed_zero_first
+
 from .v5augmentations import (Albumentations, augment_hsv, classify_albumentations, classify_transforms, copy_paste,
                               letterbox, mixup, random_perspective)
 

ultralytics/yolo/data/dataset.py

@@ -85,7 +85,6 @@ class YOLODataset(BaseDataset):
         x["results"] = nf, nm, ne, nc, len(self.im_files)
         x["msgs"] = msgs  # warnings
         x["version"] = self.cache_version  # cache version
-        self.im_files = [lb["im_file"] for lb in x["labels"]]  # update im_files
         if is_dir_writeable(path.parent):
             np.save(str(path), x)  # save cache for next time
             path.with_suffix(".cache.npy").rename(path)  # remove .npy suffix
@@ -117,6 +116,7 @@ class YOLODataset(BaseDataset):
         # Read cache
         [cache.pop(k) for k in ("hash", "version", "msgs")]  # remove items
         labels = cache["labels"]
+        self.im_files = [lb["im_file"] for lb in labels]  # update im_files
 
         # Check if the dataset is all boxes or all segments
         len_cls = sum(len(lb["cls"]) for lb in labels)