File image_ops_impl.py has 4819 lines of code (exceeds 250 allowed). Consider refactoring.

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# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at

Function central_crop has a Cognitive Complexity of 31 (exceeds 5 allowed). Consider refactoring.

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def central_crop(image, central_fraction):
  """Crop the central region of the image(s).

  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

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Function convert_image_dtype has a Cognitive Complexity of 26 (exceeds 5 allowed). Consider refactoring.

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def convert_image_dtype(image, dtype, saturate=False, name=None):
  """Convert `image` to `dtype`, scaling its values if needed.

  The operation supports data types (for `image` and `dtype`) of
  `uint8`, `uint16`, `uint32`, `uint64`, `int8`, `int16`, `int32`, `int64`,

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Function resize_image_with_crop_or_pad has a Cognitive Complexity of 17 (exceeds 5 allowed). Consider refactoring.

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def resize_image_with_crop_or_pad(image, target_height, target_width):
  """Crops and/or pads an image to a target width and height.

  Resizes an image to a target width and height by either centrally
  cropping the image or padding it evenly with zeros.

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Function resize_images_v2 has a Cognitive Complexity of 15 (exceeds 5 allowed). Consider refactoring.

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def resize_images_v2(images,
                     size,
                     method=ResizeMethod.BILINEAR,
                     preserve_aspect_ratio=False,
                     antialias=False,

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Function _resize_images_common has a Cognitive Complexity of 12 (exceeds 5 allowed). Consider refactoring.

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def _resize_images_common(images, resizer_fn, size, preserve_aspect_ratio, name,
                          skip_resize_if_same):
  """Core functionality for v1 and v2 resize functions."""
  with ops.name_scope(name, 'resize', [images, size]):
    images = ops.convert_to_tensor(images, name='images')

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Function sample_distorted_bounding_box has 10 arguments (exceeds 4 allowed). Consider refactoring.

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def sample_distorted_bounding_box(image_size,

Function non_max_suppression_padded has 10 arguments (exceeds 4 allowed). Consider refactoring.

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def non_max_suppression_padded(boxes,

Function stateless_sample_distorted_bounding_box has 9 arguments (exceeds 4 allowed). Consider refactoring.

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def stateless_sample_distorted_bounding_box(image_size,

Function sample_distorted_bounding_box_v2 has 9 arguments (exceeds 4 allowed). Consider refactoring.

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def sample_distorted_bounding_box_v2(image_size,

Function combined_non_max_suppression has 9 arguments (exceeds 4 allowed). Consider refactoring.

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def combined_non_max_suppression(boxes,

Function generate_bounding_box_proposals has 9 arguments (exceeds 4 allowed). Consider refactoring.

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def generate_bounding_box_proposals(scores,

Function crop_and_resize_v1 has 9 arguments (exceeds 4 allowed). Consider refactoring.

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def crop_and_resize_v1(  # pylint: disable=missing-docstring

Function ssim has 8 arguments (exceeds 4 allowed). Consider refactoring.

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def ssim(img1,

Function ssim_multiscale has 8 arguments (exceeds 4 allowed). Consider refactoring.

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def ssim_multiscale(img1,

Function _ssim_per_channel has 8 arguments (exceeds 4 allowed). Consider refactoring.

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def _ssim_per_channel(img1,

Function extract_glimpse_v2 has 8 arguments (exceeds 4 allowed). Consider refactoring.

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def extract_glimpse_v2(

Function extract_glimpse has 8 arguments (exceeds 4 allowed). Consider refactoring.

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def extract_glimpse(

Function non_max_suppression_padded_v2 has 8 arguments (exceeds 4 allowed). Consider refactoring.

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def non_max_suppression_padded_v2(boxes,

Function _CheckGrayscaleImage has a Cognitive Complexity of 9 (exceeds 5 allowed). Consider refactoring.

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def _CheckGrayscaleImage(image, require_static=True):
  """Assert that we are working with properly shaped grayscale image.

  Args:
    image: >= 2-D Tensor of size [*, 1]

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Function _resize_image_with_pad_common has a Cognitive Complexity of 9 (exceeds 5 allowed). Consider refactoring.

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def _resize_image_with_pad_common(image, target_height, target_width,
                                  resize_fn):
  """Core functionality for v1 and v2 resize_image_with_pad functions."""
  with ops.name_scope(None, 'resize_image_with_pad', [image]):
    image = ops.convert_to_tensor(image, name='image')

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Function non_max_suppression_with_scores has 7 arguments (exceeds 4 allowed). Consider refactoring.

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def non_max_suppression_with_scores(boxes,

Function crop_and_resize_v2 has 7 arguments (exceeds 4 allowed). Consider refactoring.

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def crop_and_resize_v2(image,

Function _ssim_helper has 7 arguments (exceeds 4 allowed). Consider refactoring.

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def _ssim_helper(x, y, reducer, max_val, compensation=1.0, k1=0.01, k2=0.03):

Function non_max_suppression_padded_v1 has 7 arguments (exceeds 4 allowed). Consider refactoring.

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def non_max_suppression_padded_v1(boxes,

Function _resize_images_common has 6 arguments (exceeds 4 allowed). Consider refactoring.

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def _resize_images_common(images, resizer_fn, size, preserve_aspect_ratio, name,

Function resize_images has 6 arguments (exceeds 4 allowed). Consider refactoring.

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def resize_images(images,

Function resize_images_v2 has 6 arguments (exceeds 4 allowed). Consider refactoring.

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def resize_images_v2(images,

Function non_max_suppression_with_overlaps has 6 arguments (exceeds 4 allowed). Consider refactoring.

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def non_max_suppression_with_overlaps(overlaps,

Function pad_to_bounding_box_internal has 6 arguments (exceeds 4 allowed). Consider refactoring.

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def pad_to_bounding_box_internal(image, offset_height, offset_width,

Function non_max_suppression has 6 arguments (exceeds 4 allowed). Consider refactoring.

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def non_max_suppression(boxes,

Function resize_images has a Cognitive Complexity of 8 (exceeds 5 allowed). Consider refactoring.

Open

def resize_images(images,
                  size,
                  method=ResizeMethodV1.BILINEAR,
                  align_corners=False,
                  preserve_aspect_ratio=False,

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Function crop_to_bounding_box has 5 arguments (exceeds 4 allowed). Consider refactoring.

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def crop_to_bounding_box(image, offset_height, offset_width, target_height,

Function resize_bilinear has 5 arguments (exceeds 4 allowed). Consider refactoring.

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def resize_bilinear(images,

Function resize_image_with_pad_v1 has 5 arguments (exceeds 4 allowed). Consider refactoring.

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def resize_image_with_pad_v1(image,

Function resize_image_with_pad_v2 has 5 arguments (exceeds 4 allowed). Consider refactoring.

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def resize_image_with_pad_v2(image,

Function decode_image has 5 arguments (exceeds 4 allowed). Consider refactoring.

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def decode_image(contents,

Function resize_nearest_neighbor has 5 arguments (exceeds 4 allowed). Consider refactoring.

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def resize_nearest_neighbor(images,

Function pad_to_bounding_box has 5 arguments (exceeds 4 allowed). Consider refactoring.

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def pad_to_bounding_box(image, offset_height, offset_width, target_height,

Function resize_bicubic has 5 arguments (exceeds 4 allowed). Consider refactoring.

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def resize_bicubic(images,

Function _suppression_loop_body has 5 arguments (exceeds 4 allowed). Consider refactoring.

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def _suppression_loop_body(boxes, iou_threshold, output_size, idx, tile_size):

Function _cross_suppression has 5 arguments (exceeds 4 allowed). Consider refactoring.

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def _cross_suppression(boxes, box_slice, iou_threshold, inner_idx, tile_size):

Function _CheckAtLeast3DImage has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

def _CheckAtLeast3DImage(image, require_static=True):
  """Assert that we are working with a properly shaped image.

  Args:
    image: >= 3-D Tensor of size [*, height, width, depth]

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Avoid too many return statements within this function.

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      return gen_image_ops.resize_area(images_t, new_size)

Avoid too many return statements within this function.

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      return resize_with_scale_and_translate(method)

Avoid too many return statements within this function.

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      return math_ops.cast(image, dtype, name=name)

Avoid too many return statements within this function.

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        return math_ops.multiply(cast, scale, name=name)

Avoid too many return statements within this function.

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          return math_ops.saturate_cast(scaled, dtype, name=name)

Avoid too many return statements within this function.

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          return math_ops.cast(scaled, dtype, name=name)

Avoid too many return statements within this function.

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        return gen_image_ops.resize_bicubic(

Function adjust_hue has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

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def adjust_hue(image, delta, name=None):
  """Adjust hue of RGB images.

  This is a convenience method that converts an RGB image to float
  representation, converts it to HSV, adds an offset to the

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Function pad_to_bounding_box_internal has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

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def pad_to_bounding_box_internal(image, offset_height, offset_width,
                                 target_height, target_width, check_dims):
  """Pad `image` with zeros to the specified `height` and `width`.

  Adds `offset_height` rows of zeros on top, `offset_width` columns of

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Function _Check3DImage has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

def _Check3DImage(image, require_static=True):
  """Assert that we are working with a properly shaped image.

  Args:
    image: 3-D Tensor of shape [height, width, channels]

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