1.3.0

Breaking changes

• Renamed method to rotate_method inside Rotate to keep consistency between naming parameters. (#1258 by @Dipet, thanks to @MichaelMonashev)

New augmentations

• RandomCropFromBorders - Crops image based on indents from image borders. (#1240 by @Dipet based on #476 by @ZFTurbo)
• BBoxSafeRandomCrop - Crops image without loss of bboxes. Instead of RandomSizedBBoxSafeCrop this implementation do not apply resize to target size. (#579 by @SunQpark)
• Spatter - Simulates corruption which can occlude a lens in the form of rain or mud. (#573 by @akarsakov)
• Defocus - Imitates lens defocusing. (#551 by @akarsakov)
• ZoomBlur - Imitates lens blur on zoomig. (#551 by @akarsakov)

Bugfixes

• Fixed wrong result in RandomBrightnessContrast when brightness_by_max=False. (#487 by @Dipet)
• Fixed wrong bbox clipping inside Perspective and Affine. (#1231 by @Dipet)
• Fixed incorrect removal of bboxes when min_visibility=0 or min_visibility=1. (#616 by @IlyaOvodov)
• Fixed wrong keypoint's cropping inside Rotate when crop_border=True. (#1250 by @Dipet, thanks to @jonkoi)
• Fixed wrong propagation of always_apply Compose children. (#561 by @albu)
• RandomSunFlare now correctly works with src_color, and use all three color values. (#1285 by @hoel-bagard)
• RandomGamma now correctly works with float gamma_limit. (#1286 by @zahragolpa)

Minor changes:

• Speeded up Normalize in some case up to 2 times. (#563 by @Dipet)
• GridDistortion, ElasticTransform and OpticalDistortion now supports bbox targets. (#476, #1262 by @ZFTurbo and @Dipet)
• MotionBlur now supports allow_shifted flag. When it's value is False only non shifted kernels generated. (#1239 by @Dipet)
• Updated versions of type formatters. (#1245 by @ternaus)
• GridDistortion now supports normalized flag. When it is set to True will be applied distortion inside image border. (#722 by @poke1024)
• Now you can describe downscale and upscale interpolation method for Downscale. This is needed to avoid interpolation artefacts. (#584 by @nathanhubens)
• Refactoring. Spatial transforms moved to geometric files. (#1241 by @ternaus)
• Refactoring. Common functions moved into albumentations.augmentations.utils.py. (#1260 by @Dipet)
• Refactoring. Blur transforms moved into albumentations.augmentations.blur. (#1259 by @Dipet)

1.2.1

Minor changes

• A.Rotate and A.ShiftScaleRotate now support new rotation method for bounding boxes, ellipse. (#1203 by @victor1cea)
• A.Rotate now supports new argument crop_border. If set to True, the rotated image will be cropped as much as possible to eliminate pixel values at the edges that were not well defined after rotation. (#1214 by @bonlime)
• Tests that use multiprocessing now run much faster (#1218 by @Dipet)
• Improved type hints (#1219 by @Dipet )
• Fixed a deprecation warning in match_histograms. (#1121 by @BloodAxe)

Bugfixes

• A.CropNonEmptyMaskIfExists modified the first element of masks in-place. Now, this behavior is fixed and A.CropNonEmptyMaskIfExists doesn't do in-place modification of input masks. (#1193 by @ORippler).
• Albumentations now correctly serialized and desirealized fill_value and mask_fill_value parameters for A.GridDropout. (#1191 by @victor1cea)
• A.ColorJitter now correctly works with A.ReplayCompose. (#1199 by @zakajd)
• Fixed incorrect behavior of A.ColorJitter for np.float32 input images when contrast is set to 0 (previously, all values were set to 0.5 instead of using the average value).. (#1207 by @Dipet)
• A.Rotate, A.Affine and A.ShiftScaleRotate now do rotation in the same way. Fixed incorrect rotation angle for A.Affine. A.Rotate and A.ShiftScaleRotate now correctly rotate the keypoints 90 degrees and don't leave black lines around the edges of the image. (#1091 by @Dipet )

1.2.0

New augmentations:

• A.UnsharpMask. This transform sharpens the input image using Unsharp Masking processing and overlays the result with the original image. (#1063 by @zakajd)
• A.RingingOvershoot. This transform creates ringing or overshoot artifacts by convolving the image with a 2D sinc filter. (#1064 by @zakajd)
• A.AdvancedBlur. This transform blurs the input image using a Generalized Normal filter with randomly selected parameters. It also adds multiplicative noise to generated kernel before convolution. (#1066 by @zakajd)
• A.PixelDropout. This transformation randomly replaces pixels with the passed value. (#1082 by @Dipet)

Bugfixes

• Fixed a problem that prevented A.RandomShadow from working with non-contiguous input. (#1117 by @i-aki-y)
• A.PadIfNeeded now works with an arbitrary number of channels. (#1069 by @BloodAxe)
• Fixed all np.random use cases to prevent identical values when using multiprocessing. (#1070 by @Dipet)
• The slant param now has an effect in A.RandomRain. (#1179 by @victor1cea)
• translate_percent now uses 0 as a default value in the A.Affine transform. (#1183 by @victor1cea)
• A.SafeRotate no longer loses blocks and keypoints. (#1109 by @Dipet)
• A.CropAndPad now correctly handles bboxes when keep_size=True. (#1059 by @cannon)
• A.RandomCrop, A.RandomSizedCrop, and A.RandomSizedBBoxSafeCrop now sample last pixel. (#1080 by @Multihuntr)

Minor changes:

• Old code is refactored, and more type hints are added (#1052 by @Dipet).
• A.Compose now warns the user if it receives a single augmentation instead of a sequence of augmentations. (#1055 by @Dipet)
• A.CoarseDropout and A.RandomGridShuffle now support keypoints. (#1084 by @BloodAxe)
• A.ToTensorV2 now supports the masks target. (#1097 by @alessiobonfiglio)
• A.PadIfNeeded now supports random padding. (#1160 by @mys007 )
• Improved and corrected documentation: #1047 by @shyn, #1164 by @notplus, #1105 by @i-aki-y
• Speeded up tests by removing unnecessary tests. (#1188 by @creafz)
• A.Affine now has keep_ratio flag. (#1104 by @i-aki-y)

1.1.0

New augmentations

• TemplateTransform. This transform allows the blending of an input image with specified templates. (#572 by @akarsakov )
• PixelDistributionAdaptation. A new domain adaptation augmentation. It fits a simple transform on both the original and reference image, transforms the original image with transform trained on this image, and performs inverse transformation using transform fitted on the reference image. See the examples of this transform in the qudida repository. (#959 by @arsenyinfo)

Minor changes:

• LongestMaxSize and SmallestMaxSize now can also accept a list of sizes as their max_size argument and the actual max_size value will be sampled randomly from this list. (#930 by @kmistry-wx )
• A.Affine now accepts mask_interpolation as a parameter. (#975 by @dskkato )
• A.RandomRain now alters brightness in HSV space instead of HLS space to prevent image corruption. (#990 by @ErlingLie)
• Albumentations now raises ValueError if bbox_params is not specified and bbox transformation is called (#1013 by @VirajBagal)
• CoarseDropout can now set the height and width of holes based on the fraction of original image height and width (#1014 by @VirajBagal )
• ElasticTransform got performance optimizations. (#1004 by @b0nce)

Bugfixes

• Fixed a bug when CropNonEmptyMaskIfExists thrown an error when it was used with a keypoint even though keypoints were mentioned as a correct target. (#986 by @GalDude33 )
• Fixed KeyError with RandomCropNearBBox when it received values with x_min <= 0 or y_min <= 0 (#993 by @Dipet )

1.0.3

• Fixed problem with incorrect shape at keypoints and bboxes processors after ToTensorV2 #963
• Fixed problems with float values in YOLO format in edge cases #958

1.0.2

1. Fixed YOLO format conversion problem when bbox greater than image by 1 pixel.
   Now YOLO bbox will be converted to Albumentations format without bbox denormalization.
   More info in PR: #924
2. Removed redundant search of first & last dual transform #946

1.0.1

Added position argument to PadIfNeeded (#933 by @yisaienkov)

Possible values: center top_left, top_right, bottom_left, bottom_right, with center being the default value.

One possible use case for this feature is object detection where you need to pad an image to square, but you want predicted bounding boxes being equal to the bounding box of the unpadded image.

image source

1.0.0

Breaking changes

• imgaug dependency is now optional, and by default, Albumentations won't install it. This change was necessary to prevent simultaneous install of both opencv-python-headless and opencv-python (you can read more about the problem in this issue). If you still need imgaug as a dependency, you can use the pip install -U albumentations[imgaug] command to install Albumentations with imgaug.
• Deprecated augmentation ToTensor that converts NumPy arrays to PyTorch tensors is completely removed from Albumentations. You will get a RuntimeError exception if you try to use it. Please switch to ToTensorV2 in your pipelines.

New augmentations

• A.RandomToneCurve. See a notebook for examples of this augmentation (#839 by @aaroswings)
• SafeRotate. Safely Rotate Images Without Cropping (#888 by @deleomike)
• SomeOf transform that applies N augmentations from a list. Generalizing of OneOf (#889 by @henrique)
• We are deprecating imgaug transforms and providing Albumentations' implementations for them.
  (#786 by @KiriLev, #787 by @KiriLev, #790, #843, #844, #849, #885, #892)

By default, Albumentations doesn't require imgaug as a dependency. But if you need imgaug, you can install it along with Albumentations by running pip install -U albumentations[imgaug].

Here is a table of deprecated imgaug augmentations and respective augmentations from Albumentations that you should use instead:

Old deprecated augmentation	New augmentation
IAACropAndPad	CropAndPad
IAAFliplr	HorizontalFlip
IAAFlipud	VerticalFlip
IAAEmboss	Emboss
IAASharpen	Sharpen
IAAAdditiveGaussianNoise	GaussNoise
IAAPerspective	Perspective
IAASuperpixels	Superpixels
IAAAffine	Affine
IAAPiecewiseAffine	PiecewiseAffine

Major changes

• Serialization logic is updated. Previously, Albumentations used the full classpath to identify an augmentation (e.g. albumentations.augmentations.transforms.RandomCrop). With the updated logic, Albumentations will use only the class name for augmentations defined in the library (e.g., RandomCrop). For custom augmentations created by users and not distributed with Albumentations, the library will continue to use the full classpath to avoid name collisions (e.g., when a user creates a custom augmentation named RandomCrop and uses it in a pipeline).

  This new logic will allow us to refactor the code without breaking serialized augmentation pipelines created using previous versions of Albumentations. This change will also reduce the size of YAML and JSON files with serialized data.

  The new serialization logic is backward compatible. You can load serialized augmentation pipelines created in previous versions of Albumentations because Albumentations supports the old format.

Bugfixes

• Fixed a bug that prevented A.ReplayCompose to work with bounding boxes and keypoints correctly. (#748)
• A.GlassBlur now correctly works with float32 inputs (#826)
• MultiplicativeNoise now correctly works with gray images with shape [h, w, 1]. (#793)

Minor changes

• Code for geometric transforms moved to a standalone module albumentations.augmentations.geometric. (#784)
• Code for crop transforms moved to a standalone module albumentations.augmentations.crops. (#791)
• CI now runs tests under Python 3.9 as well (#830)
• Linters and code formatters for CI and pre-commit hooks are updated to the latest versions (#831)
• Logic in setup.py that detects existing installations of OpenCV now also looks for opencv-contrib-python and opencv-contrib-python-headless (#837 by @agchang-cgl)

0.5.2

Minor changes

• ToTensorV2 now automatically expands grayscale images with the shape [H, W] to the shape [H, W, 1]. PR #604 by @Ingwar.
• CropNonEmptyMaskIfExists now also works with multiple masks that are provided by the masks argument to the transform function. Previously this augmentation worked only with a single mask provided by the mask argument. PR #761

0.5.1

Breaking changes

• API for A.FDA is changed to resemble API of A.HistogramMatching. Now, both transformations expect to receive a list of reference images, a function to read those image, and additional augmentation parameters. (#734)
• A.HistogramMatching now usesread_rgb_image as a default read_fn. This function reads an image from the disk as an RGB NumPy array. Previously, the default read_fn was cv2.imread which read an image as a BGR NumPy array. (#734)

New transformations

• A.Sequential transform that can apply augmentations in a sequence. This transform is not intended to be a replacement for A.Compose. Instead, it should be used inside A.Compose the same way A.OneOf or A.OneOrOther. For instance, you can combine A.OneOf with A.Sequential to create an augmentation pipeline containing multiple sequences of augmentations and apply one randomly chosen sequence to input data. (#735)

Minor changes

• A.ShiftScaleRotate now has two additional optional parameters: shift_limit_x and shift_limit_y. If either of those parameters (or both of them) is set A.ShiftScaleRotate will use the set values to shift images on the respective axis. (#735)
• A.ToTensorV2 now supports an additional argument transpose_mask (False by default). If the argument is set to True and an input mask has 3 dimensions, A.ToTensorV2 will transpose dimensions of a mask tensor in addition to transposing dimensions of an image tensor. (#735)

Bugfixes

• A.FDA now correctly uses coordinates of the center of an image. (#730)
• Fixed problems with grayscale images for A.HistogramMatching. (#734)
• Fixed a bug that led to an exception when A.load() was called to deserialize a pipeline that contained A.ToTensor or A.ToTensorV2, but those transforms were not imported in the code before the call. (#735)