We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
It is not an issue, more like a note.
image augmentation library Albumentations has transform XYSPec, which is a generalization of SpecAugment.
Works on
Applies masking strips to an image, either horizontally (X axis) or vertically (Y axis), simulating occlusions. This transform is useful for training models to recognize images with varied visibility conditions. It's particularly effective for spectrogram images, allowing spectral and frequency masking to improve model robustness. At least one of `max_x_length` or `max_y_length` must be specified, dictating the mask's maximum size along each axis. Args: num_masks_x (int | tuple[int, int]): Number or range of horizontal regions to mask. Defaults to 0. num_masks_y (int | tuple[int, int]): Number or range of vertical regions to mask. Defaults to 0. mask_x_length (int | tuple[int, int]): Specifies the length of the masks along the X (horizontal) axis. If an integer is provided, it sets a fixed mask length. If a tuple of two integers (min, max) is provided, the mask length is randomly chosen within this range for each mask. This allows for variable-length masks in the horizontal direction. mask_y_length (int | tuple[int, int]): Specifies the height of the masks along the Y (vertical) axis. Similar to `mask_x_length`, an integer sets a fixed mask height, while a tuple (min, max) allows for variable-height masks, chosen randomly within the specified range for each mask. This flexibility facilitates creating masks of various sizes in the vertical direction. fill_value (int | float | list[int] | list[float] | str): Value to fill image masks. Defaults to 0. mask_fill_value (int | float | list[int] | list[float] | None): Value to fill masks in the mask. If `None`, uses mask is not affected. Default: `None`. p (float): Probability of applying the transform. Defaults to 0.5. Targets: image, mask, bboxes, keypoints Image types: uint8, float32 Note: Either `max_x_length` or `max_y_length` or both must be defined.
Link to play with https://explore.albumentations.ai/transform/XYMasking
The text was updated successfully, but these errors were encountered:
No branches or pull requests
It is not an issue, more like a note.
image augmentation library Albumentations has transform XYSPec, which is a generalization of SpecAugment.
Works on
Link to play with https://explore.albumentations.ai/transform/XYMasking
The text was updated successfully, but these errors were encountered: