RandomContrast class
keras.layers.RandomContrast(factor, value_range=(0, 255), seed=None, **kwargs)
A preprocessing layer which randomly adjusts contrast during training.
This layer will randomly adjust the contrast of an image or images by a random factor. Contrast is adjusted independently for each channel of each image during training.
For each channel, this layer computes the mean of the image pixels in the channel and then adjusts each component x of each pixel to (x - mean) * contrast_factor + mean.
Input pixel values can be of any range (e.g. [0., 1.) or [0, 255]) and in integer or floating point dtype. By default, the layer will output floats.
Note: This layer is safe to use inside a tf.data pipeline (independently of which backend you're using).
Input shape
3D (unbatched) or 4D (batched) tensor with shape: (..., height, width, channels), in "channels_last" format.
Output shape
3D (unbatched) or 4D (batched) tensor with shape: (..., height, width, channels), in "channels_last" format.
Arguments
[1.0 - lower, 1.0 + upper]. For any pixel x in the channel, the output will be (x - mean) * factor + mean where mean is the mean value of the channel.[low, high]. This is typically either [0, 1] or [0, 255] depending on how your preprocessing pipeline is set up.RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4