Expected x_max for bbox (0.4358974358974359, 0.30288461538461536, 1.061965811965812, 0.9663461538461539, 13) to be in the range [0.0, 1.0], got 1.061965811965812.

[aliceinland]

🐛 Bug

When trying to perform data augmentation with bounding boxes and mask in yolo format, this is the output the is produced.

To Reproduce

Steps to reproduce the behavior:

File "/workspace/deepfashion_train/dataset.py", line 126, in __getitem__
    transformed = self.trans(image=np.asarray(img), masks=mask_list, bboxes = boxes.detach().tolist(), class_labels = labels.detach().tolist())  #bboxes = bbox_labels)
  File "/opt/conda/lib/python3.8/site-packages/albumentations/core/composition.py", line 180, in __call__
    p.preprocess(data)
  File "/opt/conda/lib/python3.8/site-packages/albumentations/core/utils.py", line 62, in preprocess
    data[data_name] = self.check_and_convert(data[data_name], rows, cols, direction="to")
  File "/opt/conda/lib/python3.8/site-packages/albumentations/core/utils.py", line 70, in check_and_convert
    return self.convert_to_albumentations(data, rows, cols)
  File "/opt/conda/lib/python3.8/site-packages/albumentations/augmentations/bbox_utils.py", line 51, in convert_to_albumentations
    return convert_bboxes_to_albumentations(data, self.params.format, rows, cols, check_validity=True)
  File "/opt/conda/lib/python3.8/site-packages/albumentations/augmentations/bbox_utils.py", line 302, in convert_bboxes_to_albumentations
    return [convert_bbox_to_albumentations(bbox, source_format, rows, cols, check_validity) for bbox in bboxes]
  File "/opt/conda/lib/python3.8/site-packages/albumentations/augmentations/bbox_utils.py", line 302, in <listcomp>
    return [convert_bbox_to_albumentations(bbox, source_format, rows, cols, check_validity) for bbox in bboxes]
  File "/opt/conda/lib/python3.8/site-packages/albumentations/augmentations/bbox_utils.py", line 251, in convert_bbox_to_albumentations
    check_bbox(bbox)
  File "/opt/conda/lib/python3.8/site-packages/albumentations/augmentations/bbox_utils.py", line 327, in check_bbox
    raise ValueError(
ValueError: Expected x_max for bbox (0.4358974358974359, 0.30288461538461536, 1.061965811965812, 0.9663461538461539, 13) to be in the range [0.0, 1.0], got 1.061965811965812.

The code that generates this error is:

self.trans = A.Compose([
                A.Resize(224, 224),
                        #A.Resize(256, 128),
                        #A.RandomRotate90(),
                A.Flip(),
                A.ColorJitter(brightness= 0.3, contrast= 0.3,saturation=0.1, hue=0.1, p=0.3),
                #A.Transpose(),
                A.GaussNoise(),
                #A.RandomCrop(width=224, height=224),
                A.OneOf([
                    A.MotionBlur(p=.5),
                    A.MedianBlur(blur_limit=3, p=0.5),
                    A.Blur(blur_limit=3, p=0.5),
                ], p=0.5),
                A.ShiftScaleRotate(shift_limit=0.0625, scale_limit=0.2, rotate_limit=45, p=0.5),
                A.OneOf([
                    A.OpticalDistortion(p=0.5),
                    A.GridDistortion(p=.3),
                    A.PiecewiseAffine(p=0.5),
                ], p=0.5),
                A.OneOf([
                    A.CLAHE(clip_limit=2),
                    A.Emboss(),
                    A.RandomBrightnessContrast(),            
                ], p=0.5),
                A.HueSaturationValue(p=0.5),
                    #A.Normalize(mean=(0.486, 0.459, 0.408), std=(0.229, 0.224, 0.225)),
                    ToTensorV2()
                ], bbox_params=A.BboxParams(format='coco', label_fields=['class_labels']))
        else:
            self.trans = A.Compose([
                A.Resize(224, 224),
                ToTensorV2()
            ], bbox_params = A.BboxParams(format='coco', label_fields=['class_labels']))

Expected behavior

Perform some image augmentations technique over the dataset with bounding boxes and masks.

Environment

• Albumentations version (e.g., 0.1.8): 1.0.0
• Python version (e.g., 3.7): 3.7
• OS (e.g., Linux): Linux
• How you installed albumentations (conda, pip, source): pip

[yisaienkov]

I think it happens because your box extends beyond the right edge of the input image.

[aliceinland]

Yes, but this happens during the process of data augmentation performed with albumentation.
The same issue was report in issue #922, #903 and other ones linked in issue #922.

[Dipet]

Should be fixed by #924