tf.image.adjust_saturation(image, saturation_factor, name=None) Adjust saturation of an RGB image. This is a convenience method that converts an RGB image to float representation, converts it to HSV, add an offset to the saturation channel, converts back to RGB and then back to the original data type. If several adjustments are chained it is advisable to minimize the number of redundant conversions. image is an RGB image. The image saturation is adjusted by converting the image to HSV and mult

tf.image.adjust_hue(image, delta, name=None) Adjust hue of an RGB image. This is a convenience method that converts an RGB image to float representation, converts it to HSV, add an offset to the hue channel, converts back to RGB and then back to the original data type. If several adjustments are chained it is advisable to minimize the number of redundant conversions. image is an RGB image. The image hue is adjusted by converting the image to HSV and rotating the hue channel (H) by delta. The i

tf.image.adjust_contrast(images, contrast_factor) Adjust contrast of RGB or grayscale images. This is a convenience method that converts an RGB image to float representation, adjusts its contrast, and then converts it back to the original data type. If several adjustments are chained it is advisable to minimize the number of redundant conversions. images is a tensor of at least 3 dimensions. The last 3 dimensions are interpreted as [height, width, channels]. The other dimensions only represent

tf.image.adjust_brightness(image, delta) Adjust the brightness of RGB or Grayscale images. This is a convenience method that converts an RGB image to float representation, adjusts its brightness, and then converts it back to the original data type. If several adjustments are chained it is advisable to minimize the number of redundant conversions. The value delta is added to all components of the tensor image. Both image and delta are converted to float before adding (and image is scaled approp

tf.imag(input, name=None) Returns the imaginary part of a complex number. Given a tensor input of complex numbers, this operation returns a tensor of type float32 or float64 that is the imaginary part of each element in input. All elements in input must be complex numbers of the form (a + bj), where a is the real part and b is the imaginary part returned by this operation. For example: # tensor 'input' is [-2.25 + 4.75j, 3.25 + 5.75j] tf.imag(input) ==> [4.75, 5.75] Args: input: A Tensor.

tf.igammac(a, x, name=None) Compute the upper regularized incomplete Gamma function Q(a, x). The upper regularized incomplete Gamma function is defined as: Q(a, x) = Gamma(a, x) / Gamma(a) = 1 - P(a, x) where Gamma(a, x) = int_{x}^{\infty} t^{a-1} exp(-t) dt is the upper incomplete Gama function. Note, above P(a, x) (Igamma) is the lower regularized complete Gamma function. Args: a: A Tensor. Must be one of the following types: float32, float64. x: A Tensor. Must have the same type as a. n

tf.igamma(a, x, name=None) Compute the lower regularized incomplete Gamma function Q(a, x). The lower regularized incomplete Gamma function is defined as: P(a, x) = gamma(a, x) / Gamma(a) = 1 - Q(a, x) where gamma(a, x) = int_{0}^{x} t^{a-1} exp(-t) dt is the lower incomplete Gamma function. Note, above Q(a, x) (Igammac) is the upper regularized complete Gamma function. Args: a: A Tensor. Must be one of the following types: float32, float64. x: A Tensor. Must have the same type as a. name:

tf.ifft3d(input, name=None) Compute the inverse 3-dimensional discrete Fourier Transform over the inner-most 3 dimensions of input. Args: input: A Tensor of type complex64. A complex64 tensor. name: A name for the operation (optional). Returns: A Tensor of type complex64. A complex64 tensor of the same shape as input. The inner-most 3 dimensions of input are replaced with their inverse 3D Fourier Transform.

tf.ifft2d(input, name=None) Compute the inverse 2-dimensional discrete Fourier Transform over the inner-most 2 dimensions of input. Args: input: A Tensor of type complex64. A complex64 tensor. name: A name for the operation (optional). Returns: A Tensor of type complex64. A complex64 tensor of the same shape as input. The inner-most 2 dimensions of input are replaced with their inverse 2D Fourier Transform.

tf.ifft(input, name=None) Compute the inverse 1-dimensional discrete Fourier Transform over the inner-most dimension of input. Args: input: A Tensor of type complex64. A complex64 tensor. name: A name for the operation (optional). Returns: A Tensor of type complex64. A complex64 tensor of the same shape as input. The inner-most dimension of input is replaced with its inverse 1D Fourier Transform.