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ValueError: Expected x_min for bbox (...) to be in the range [0.0, 1.0], got -0.0020000000000000018 #1497

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MarcosRodrigoT opened this issue Nov 10, 2023 · 0 comments 路 May be fixed by #1498
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ValueError: Expected x_min for bbox (...) to be in the range [0.0, 1.0], got -0.0020000000000000018 #1497

MarcosRodrigoT opened this issue Nov 10, 2023 · 0 comments 路 May be fixed by #1498

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@MarcosRodrigoT
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馃悰 Bug

Albumentations is raising ValueError: Expected x_min for bbox (-0.002499499999999988, 0.3245773732394366, 0.5367755, 0.9829923732394366, 22.0) to be in the range [0.0, 1.0], got -0.002499499999999988.

To Reproduce

Steps to reproduce the behavior:

  1. Create an albumentations compose object.
  2. Pass some bounding boxes in the yolo format.

Expected behavior

Environment

  • Albumentations version: 1.3.1
  • Python version: 3.10.12
  • OS (e.g., Linux): Ubuntu 22.04
  • How you installed albumentations: pip

Additional context

Code to reproduce the error:

import albumentations as A
import cv2
import numpy as np
from PIL import Image


img_path = "COCO/images/COCO_train2014_000000394974.jpg"
label_path = "COCO/images/COCO_train2014_000000394974.txt"

image = np.array(Image.open(img_path).convert("RGB"))
bboxes = np.roll(
    np.loadtxt(fname=label_path, delimiter=" ", ndmin=2),
    shift=4,
    axis=1,
).tolist()

"""BEFORE AUGMENTATION"""
print(f"Image file: {img_path}")
print(f"Image shape: {image.shape}")
print(f"Label file: {label_path}")
print("Bboxes before augmentation:")
for bbox in bboxes:
    print(bbox)

augmentor = A.Compose(
    [
        A.LongestMaxSize(max_size=416),
        A.PadIfNeeded(
            min_height=416, min_width=416, border_mode=cv2.BORDER_CONSTANT
        ),
        A.Normalize(
            mean=[0, 0, 0],
            std=[1, 1, 1],
            max_pixel_value=255,
        ),
        ToTensorV2(),
    ],
    bbox_params=A.BboxParams(format="yolo", min_visibility=0.4, label_fields=[]),
)
augmentations = augmentor(image=image, bboxes=bboxes)

"""AFTER AUGMENTATION"""
image = augmentations["image"]
bboxes = augmentations["bboxes"]
print("Bboxes after augmentation:")
for bbox in bboxes:
    print(bbox)

Result obtained from the above code snippet:

Image file: COCO/images/COCO_train2014_000000394974.jpg
Image shape: (284, 400, 3)
Label file: /home/marcos/Datasets/COCO/labels/COCO_train2014_000000394974.txt

Bboxes before augmentation:
[0.4514250000000001, 0.4515318732394366, 0.3494, 0.541585, 22.0]
[0.267138, 0.6537848732394366, 0.539275, 0.658415, 22.0]
[0.285525, 0.7203518732394366, 0.38795, 0.406831, 22.0]

Traceback (most recent call last):
  File "/home/marcos/Projects/YOLOv3/PyTorch/dataset.py", line 155, in <module>
    test()
  File "/home/marcos/Projects/YOLOv3/PyTorch/dataset.py", line 137, in test
    for x, y in loader:
  File "/home/marcos/Projects/YOLOv3/venv/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 630, in __next__
    data = self._next_data()
  File "/home/marcos/Projects/YOLOv3/venv/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 674, in _next_data
    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
  File "/home/marcos/Projects/YOLOv3/venv/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py", line 51, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/home/marcos/Projects/YOLOv3/venv/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py", line 51, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/home/marcos/Projects/YOLOv3/PyTorch/dataset.py", line 70, in __getitem__
    augmentations = self.transform(image=image, bboxes=bboxes)
  File "/home/marcos/Projects/YOLOv3/venv/lib/python3.10/site-packages/albumentations/core/composition.py", line 207, in __call__
    p.preprocess(data)
  File "/home/marcos/Projects/YOLOv3/venv/lib/python3.10/site-packages/albumentations/core/utils.py", line 83, in preprocess
    data[data_name] = self.check_and_convert(data[data_name], rows, cols, direction="to")
  File "/home/marcos/Projects/YOLOv3/venv/lib/python3.10/site-packages/albumentations/core/utils.py", line 91, in check_and_convert
    return self.convert_to_albumentations(data, rows, cols)
  File "/home/marcos/Projects/YOLOv3/venv/lib/python3.10/site-packages/albumentations/core/bbox_utils.py", line 142, in convert_to_albumentations
    return convert_bboxes_to_albumentations(data, self.params.format, rows, cols, check_validity=True)
  File "/home/marcos/Projects/YOLOv3/venv/lib/python3.10/site-packages/albumentations/core/bbox_utils.py", line 408, in convert_bboxes_to_albumentations
    return [convert_bbox_to_albumentations(bbox, source_format, rows, cols, check_validity) for bbox in bboxes]
  File "/home/marcos/Projects/YOLOv3/venv/lib/python3.10/site-packages/albumentations/core/bbox_utils.py", line 408, in <listcomp>
    return [convert_bbox_to_albumentations(bbox, source_format, rows, cols, check_validity) for bbox in bboxes]
  File "/home/marcos/Projects/YOLOv3/venv/lib/python3.10/site-packages/albumentations/core/bbox_utils.py", line 352, in convert_bbox_to_albumentations
    check_bbox(bbox)
  File "/home/marcos/Projects/YOLOv3/venv/lib/python3.10/site-packages/albumentations/core/bbox_utils.py", line 435, in check_bbox
    raise ValueError(f"Expected {name} for bbox {bbox} to be in the range [0.0, 1.0], got {value}.")
ValueError: Expected x_min for bbox (-0.002499499999999988, 0.3245773732394366, 0.5367755, 0.9829923732394366, 22.0) to be in the range [0.0, 1.0], got -0.002499499999999988.
@MarcosRodrigoT MarcosRodrigoT linked a pull request Nov 10, 2023 that will close this issue
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Fix bounding box conversion from yolo format MarcosRodrigoT/albumentations
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@MarcosRodrigoT