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4.3 KiB

Argument Type Default Range Description
hsv_h float 0.015 0.0 - 1.0 Adjusts the hue of the image by a fraction of the color wheel, introducing color variability. Helps the model generalize across different lighting conditions.
hsv_s float 0.7 0.0 - 1.0 Alters the saturation of the image by a fraction, affecting the intensity of colors. Useful for simulating different environmental conditions.
hsv_v float 0.4 0.0 - 1.0 Modifies the value (brightness) of the image by a fraction, helping the model to perform well under various lighting conditions.
degrees float 0.0 -180 - +180 Rotates the image randomly within the specified degree range, improving the model's ability to recognize objects at various orientations.
translate float 0.1 0.0 - 1.0 Translates the image horizontally and vertically by a fraction of the image size, aiding in learning to detect partially visible objects.
scale float 0.5 >=0.0 Scales the image by a gain factor, simulating objects at different distances from the camera.
shear float 0.0 -180 - +180 Shears the image by a specified degree, mimicking the effect of objects being viewed from different angles.
perspective float 0.0 0.0 - 0.001 Applies a random perspective transformation to the image, enhancing the model's ability to understand objects in 3D space.
flipud float 0.0 0.0 - 1.0 Flips the image upside down with the specified probability, increasing the data variability without affecting the object's characteristics.
fliplr float 0.5 0.0 - 1.0 Flips the image left to right with the specified probability, useful for learning symmetrical objects and increasing dataset diversity.
bgr float 0.0 0.0 - 1.0 Flips the image channels from RGB to BGR with the specified probability, useful for increasing robustness to incorrect channel ordering.
mosaic float 1.0 0.0 - 1.0 Combines four training images into one, simulating different scene compositions and object interactions. Highly effective for complex scene understanding.
mixup float 0.0 0.0 - 1.0 Blends two images and their labels, creating a composite image. Enhances the model's ability to generalize by introducing label noise and visual variability.
copy_paste float 0.0 0.0 - 1.0 Copies objects from one image and pastes them onto another, useful for increasing object instances and learning object occlusion.
auto_augment str randaugment - Automatically applies a predefined augmentation policy (randaugment, autoaugment, augmix), optimizing for classification tasks by diversifying the visual features.
erasing float 0.4 0.0 - 0.9 Randomly erases a portion of the image during classification training, encouraging the model to focus on less obvious features for recognition.
crop_fraction float 1.0 0.1 - 1.0 Crops the classification image to a fraction of its size to emphasize central features and adapt to object scales, reducing background distractions.