tf.image.central_crop(image, central_fraction) Crop the central region of the image. Remove the outer parts of an image but retain the central region of the image along each dimension. If we specify central_fraction = 0.5, this function returns the region marked with "X" in the below diagram. -------- | | | XXXX | | XXXX | | | where "X" is the central 50% of the image. -------- Args: image: 3-D float Tensor of shape [height, width, depth] central_fraction: float (0, 1]

tf.image.convert_image_dtype(image, dtype, saturate=False, name=None) Convert image to dtype, scaling its values if needed. Images that are represented using floating point values are expected to have values in the range [0,1). Image data stored in integer data types are expected to have values in the range [0,MAX], where MAX is the largest positive representable number for the data type. This op converts between data types, scaling the values appropriately before casting. Note that converting

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.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.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.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.