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ultralytics 8.2.52 fix CenterCrop transforms for PIL Image inputs (#14308)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Lucas Buligon Antunes <lukasbuligonantunes@gmail.com>
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Glenn Jocher 2024-07-10 03:00:14 +02:00 • committed by GitHub
parent 755dcd6ca0
commit 997f2c92cd
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GPG key ID: B5690EEEBB952194
20 changed files with 38 additions and 30 deletions
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2
ultralytics/__init__.py
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@ -1,6 +1,6 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license
__version__ = "8.2.51"
__version__ = "8.2.52"
import os

2
ultralytics/cfg/datasets/african-wildlife.yaml
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@ -21,4 +21,4 @@ names:
3: zebra
# Download script/URL (optional)
download: https://ultralytics.com/assets/african-wildlife.zip
download: https://github.com/ultralytics/yolov5/releases/download/v1.0/african-wildlife.zip

2
ultralytics/cfg/datasets/brain-tumor.yaml
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@ -19,4 +19,4 @@ names:
1: positive
# Download script/URL (optional)
download: https://ultralytics.com/assets/brain-tumor.zip
download: https://github.com/ultralytics/yolov5/releases/download/v1.0/brain-tumor.zip

2
ultralytics/cfg/datasets/carparts-seg.yaml
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@ -40,4 +40,4 @@ names:
22: wheel
# Download script/URL (optional)
download: https://ultralytics.com/assets/carparts-seg.zip
download: https://github.com/ultralytics/yolov5/releases/download/v1.0/carparts-seg.zip

2
ultralytics/cfg/datasets/coco128-seg.yaml
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@ -97,4 +97,4 @@ names:
79: toothbrush
# Download script/URL (optional)
download: https://ultralytics.com/assets/coco128-seg.zip
download: https://github.com/ultralytics/yolov5/releases/download/v1.0/coco128-seg.zip

2
ultralytics/cfg/datasets/coco128.yaml
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@ -97,4 +97,4 @@ names:
79: toothbrush
# Download script/URL (optional)
download: https://ultralytics.com/assets/coco128.zip
download: https://github.com/ultralytics/yolov5/releases/download/v1.0/coco128.zip

2
ultralytics/cfg/datasets/coco8-pose.yaml
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@ -22,4 +22,4 @@ names:
0: person
# Download script/URL (optional)
download: https://ultralytics.com/assets/coco8-pose.zip
download: https://github.com/ultralytics/yolov5/releases/download/v1.0/coco8-pose.zip

2
ultralytics/cfg/datasets/coco8-seg.yaml
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@ -97,4 +97,4 @@ names:
79: toothbrush
# Download script/URL (optional)
download: https://ultralytics.com/assets/coco8-seg.zip
download: https://github.com/ultralytics/yolov5/releases/download/v1.0/coco8-seg.zip

2
ultralytics/cfg/datasets/coco8.yaml
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@ -97,4 +97,4 @@ names:
79: toothbrush
# Download script/URL (optional)
download: https://ultralytics.com/assets/coco8.zip
download: https://github.com/ultralytics/yolov5/releases/download/v1.0/coco8.zip

2
ultralytics/cfg/datasets/crack-seg.yaml
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@ -18,4 +18,4 @@ names:
0: crack
# Download script/URL (optional)
download: https://ultralytics.com/assets/crack-seg.zip
download: https://github.com/ultralytics/yolov5/releases/download/v1.0/crack-seg.zip

2
ultralytics/cfg/datasets/package-seg.yaml
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@ -18,4 +18,4 @@ names:
0: package
# Download script/URL (optional)
download: https://ultralytics.com/assets/package-seg.zip
download: https://github.com/ultralytics/yolov5/releases/download/v1.0/package-seg.zip

2
ultralytics/cfg/datasets/signature.yaml
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@ -17,4 +17,4 @@ names:
0: signature
# Download script/URL (optional)
download: https://ultralytics.com/assets/signature.zip
download: https://github.com/ultralytics/yolov5/releases/download/v1.0/signature.zip

2
ultralytics/cfg/datasets/tiger-pose.yaml
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@ -21,4 +21,4 @@ names:
0: tiger
# Download script/URL (optional)
download: https://ultralytics.com/assets/tiger-pose.zip
download: https://github.com/ultralytics/yolov5/releases/download/v1.0/tiger-pose.zip

2
ultralytics/data/augment.py
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@ -1401,6 +1401,8 @@ class CenterCrop:
Returns:
(numpy.ndarray): The center-cropped and resized image as a numpy array.
"""
if isinstance(im, Image.Image): # convert from PIL to numpy array if required
im = np.asarray(im)
imh, imw = im.shape[:2]
m = min(imh, imw) # min dimension
top, left = (imh - m) // 2, (imw - m) // 2

14
ultralytics/data/dataset.py
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@ -15,6 +15,7 @@ from torch.utils.data import ConcatDataset
from ultralytics.utils import LOCAL_RANK, NUM_THREADS, TQDM, colorstr
from ultralytics.utils.ops import resample_segments
from ultralytics.utils.torch_utils import TORCH_1_13
from .augment import (
Compose,
@ -263,7 +264,7 @@ class YOLOMultiModalDataset(YOLODataset):
super().__init__(*args, data=data, task=task, **kwargs)
def update_labels_info(self, label):
"""Add texts information for multi modal model training."""
"""Add texts information for multi-modal model training."""
labels = super().update_labels_info(label)
# NOTE: some categories are concatenated with its synonyms by `/`.
labels["texts"] = [v.split("/") for _, v in self.data["names"].items()]
@ -296,10 +297,10 @@ class GroundingDataset(YOLODataset):
with open(self.json_file, "r") as f:
annotations = json.load(f)
images = {f'{x["id"]:d}': x for x in annotations["images"]}
imgToAnns = defaultdict(list)
img_to_anns = defaultdict(list)
for ann in annotations["annotations"]:
imgToAnns[ann["image_id"]].append(ann)
for img_id, anns in TQDM(imgToAnns.items(), desc=f"Reading annotations {self.json_file}"):
img_to_anns[ann["image_id"]].append(ann)
for img_id, anns in TQDM(img_to_anns.items(), desc=f"Reading annotations {self.json_file}"):
img = images[f"{img_id:d}"]
h, w, f = img["height"], img["width"], img["file_name"]
im_file = Path(self.img_path) / f
@ -416,7 +417,10 @@ class ClassificationDataset:
import torchvision # scope for faster 'import ultralytics'
# Base class assigned as attribute rather than used as base class to allow for scoping slow torchvision import
self.base = torchvision.datasets.ImageFolder(root=root, allow_empty=True)
if TORCH_1_13: # 'allow_empty' argument first introduced in torch 1.13
self.base = torchvision.datasets.ImageFolder(root=root, allow_empty=True)
else:
self.base = torchvision.datasets.ImageFolder(root=root)
self.samples = self.base.samples
self.root = self.base.root

2
ultralytics/utils/benchmarks.py
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@ -195,7 +195,7 @@ class RF100Benchmark:
(shutil.rmtree("rf-100"), os.mkdir("rf-100")) if os.path.exists("rf-100") else os.mkdir("rf-100")
os.chdir("rf-100")
os.mkdir("ultralytics-benchmarks")
safe_download("https://ultralytics.com/assets/datasets_links.txt")
safe_download("https://github.com/ultralytics/yolov5/releases/download/v1.0/datasets_links.txt")
with open(ds_link_txt, "r") as file:
for line in file:

2
ultralytics/utils/checks.py
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@ -315,7 +315,7 @@ def check_font(font="Arial.ttf"):
return matches[0]
# Download to USER_CONFIG_DIR if missing
url = f"https://ultralytics.com/assets/{name}"
url = f"https://github.com/ultralytics/yolov5/releases/download/v1.0/{name}"
if downloads.is_url(url, check=True):
downloads.safe_download(url=url, file=file)
return file

6
ultralytics/utils/downloads.py
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@ -194,12 +194,14 @@ def unzip_file(file, path=None, exclude=(".DS_Store", "__MACOSX"), exist_ok=Fals
return path # return unzip dir
def check_disk_space(url="https://ultralytics.com/assets/coco128.zip", path=Path.cwd(), sf=1.5, hard=True):
def check_disk_space(
url="https://github.com/ultralytics/yolov5/releases/download/v1.0/coco8.zip", path=Path.cwd(), sf=1.5, hard=True
):
"""
Check if there is sufficient disk space to download and store a file.
Args:
url (str, optional): The URL to the file. Defaults to 'https://ultralytics.com/assets/coco128.zip'.
url (str, optional): The URL to the file. Defaults to 'https://ultralytics.com/assets/coco8.zip'.
path (str | Path, optional): The path or drive to check the available free space on.
sf (float, optional): Safety factor, the multiplier for the required free space. Defaults to 2.0.
hard (bool, optional): Whether to throw an error or not on insufficient disk space. Defaults to True.