HorizontalFlip

>>> import numpy as np
>>> import albumentations as A
>>>
>>> # Prepare sample data
>>> image = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])
>>> mask = np.array([[1, 0], [0, 1]])
>>> bboxes = np.array([[0.1, 0.5, 0.3, 0.9]])  # [x_min, y_min, x_max, y_max] format
>>> keypoints = np.array([[0.1, 0.5], [0.9, 0.5]])  # [x, y] format
>>>
>>> # Create a transform with horizontal flip
>>> transform = A.Compose([
...     A.HorizontalFlip(p=1.0)  # Always apply for this example
... ], bbox_params=A.BboxParams(coord_format='yolo', label_fields=[]),
...    keypoint_params=A.KeypointParams(coord_format='normalized'))
>>>
>>> # Apply the transform
>>> transformed = transform(image=image, mask=mask, bboxes=bboxes, keypoints=keypoints)
>>>
>>> # Get the transformed data
>>> flipped_image = transformed["image"]  # Image flipped horizontally
>>> flipped_mask = transformed["mask"]    # Mask flipped horizontally
>>> flipped_bboxes = transformed["bboxes"]  # BBox coordinates adjusted for horizontal flip
>>> flipped_keypoints = transformed["keypoints"]  # Keypoint x-coordinates flipped