# This file is MACHINE GENERATED! Do not edit. # Generated by: tensorflow/python/tools/api/generator/create_python_api.py script. """Image ops. The `tf.image` module contains various functions for image processing and decoding-encoding Ops. Many of the encoding/decoding functions are also available in the core `tf.io` module. ## Image processing ### Resizing The resizing Ops accept input images as tensors of several types. They always output resized images as float32 tensors. The convenience function `tf.image.resize` supports both 4-D and 3-D tensors as input and output. 4-D tensors are for batches of images, 3-D tensors for individual images. Resized images will be distorted if their original aspect ratio is not the same as size. To avoid distortions see tf.image.resize_with_pad. * `tf.image.resize` * `tf.image.resize_with_pad` * `tf.image.resize_with_crop_or_pad` The Class `tf.image.ResizeMethod` provides various resize methods like `bilinear`, `nearest_neighbor`. ### Converting Between Colorspaces Image ops work either on individual images or on batches of images, depending on the shape of their input Tensor. If 3-D, the shape is `[height, width, channels]`, and the Tensor represents one image. If 4-D, the shape is `[batch_size, height, width, channels]`, and the Tensor represents `batch_size` images. Currently, `channels` can usefully be 1, 2, 3, or 4. Single-channel images are grayscale, images with 3 channels are encoded as either RGB or HSV. Images with 2 or 4 channels include an alpha channel, which has to be stripped from the image before passing the image to most image processing functions (and can be re-attached later). Internally, images are either stored in as one `float32` per channel per pixel (implicitly, values are assumed to lie in `[0,1)`) or one `uint8` per channel per pixel (values are assumed to lie in `[0,255]`). TensorFlow can convert between images in RGB or HSV or YIQ. * `tf.image.rgb_to_grayscale`, `tf.image.grayscale_to_rgb` * `tf.image.rgb_to_hsv`, `tf.image.hsv_to_rgb` * `tf.image.rgb_to_yiq`, `tf.image.yiq_to_rgb` * `tf.image.rgb_to_yuv`, `tf.image.yuv_to_rgb` * `tf.image.image_gradients` * `tf.image.convert_image_dtype` ### Image Adjustments TensorFlow provides functions to adjust images in various ways: brightness, contrast, hue, and saturation. Each adjustment can be done with predefined parameters or with random parameters picked from predefined intervals. Random adjustments are often useful to expand a training set and reduce overfitting. If several adjustments are chained it is advisable to minimize the number of redundant conversions by first converting the images to the most natural data type and representation. * `tf.image.adjust_brightness` * `tf.image.adjust_contrast` * `tf.image.adjust_gamma` * `tf.image.adjust_hue` * `tf.image.adjust_jpeg_quality` * `tf.image.adjust_saturation` * `tf.image.random_brightness` * `tf.image.random_contrast` * `tf.image.random_hue` * `tf.image.random_saturation` * `tf.image.per_image_standardization` ### Working with Bounding Boxes * `tf.image.draw_bounding_boxes` * `tf.image.combined_non_max_suppression` * `tf.image.generate_bounding_box_proposals` * `tf.image.non_max_suppression` * `tf.image.non_max_suppression_overlaps` * `tf.image.non_max_suppression_padded` * `tf.image.non_max_suppression_with_scores` * `tf.image.pad_to_bounding_box` * `tf.image.sample_distorted_bounding_box` ### Cropping * `tf.image.central_crop` * `tf.image.crop_and_resize` * `tf.image.crop_to_bounding_box` * `tf.io.decode_and_crop_jpeg` * `tf.image.extract_glimpse` * `tf.image.random_crop` * `tf.image.resize_with_crop_or_pad` ### Flipping, Rotating and Transposing * `tf.image.flip_left_right` * `tf.image.flip_up_down` * `tf.image.random_flip_left_right` * `tf.image.random_flip_up_down` * `tf.image.rot90` * `tf.image.transpose` ## Image decoding and encoding TensorFlow provides Ops to decode and encode JPEG and PNG formats. Encoded images are represented by scalar string Tensors, decoded images by 3-D uint8 tensors of shape `[height, width, channels]`. (PNG also supports uint16.) Note: `decode_gif` returns a 4-D array `[num_frames, height, width, 3]` The encode and decode Ops apply to one image at a time. Their input and output are all of variable size. If you need fixed size images, pass the output of the decode Ops to one of the cropping and resizing Ops. * `tf.io.decode_bmp` * `tf.io.decode_gif` * `tf.io.decode_image` * `tf.io.decode_jpeg` * `tf.io.decode_and_crop_jpeg` * `tf.io.decode_png` * `tf.io.encode_jpeg` * `tf.io.encode_png` """ from __future__ import print_function as _print_function import sys as _sys from tensorflow.python.ops.array_ops import extract_image_patches from tensorflow.python.ops.array_ops import extract_image_patches_v2 as extract_patches from tensorflow.python.ops.gen_image_ops import decode_and_crop_jpeg from tensorflow.python.ops.gen_image_ops import decode_bmp from tensorflow.python.ops.gen_image_ops import decode_gif from tensorflow.python.ops.gen_image_ops import decode_jpeg from tensorflow.python.ops.gen_image_ops import decode_png from tensorflow.python.ops.gen_image_ops import encode_jpeg from tensorflow.python.ops.gen_image_ops import extract_jpeg_shape from tensorflow.python.ops.gen_image_ops import hsv_to_rgb from tensorflow.python.ops.gen_image_ops import resize_area from tensorflow.python.ops.gen_image_ops import rgb_to_hsv from tensorflow.python.ops.image_ops_impl import ResizeMethodV1 as ResizeMethod from tensorflow.python.ops.image_ops_impl import adjust_brightness from tensorflow.python.ops.image_ops_impl import adjust_contrast from tensorflow.python.ops.image_ops_impl import adjust_gamma from tensorflow.python.ops.image_ops_impl import adjust_hue from tensorflow.python.ops.image_ops_impl import adjust_jpeg_quality from tensorflow.python.ops.image_ops_impl import adjust_saturation from tensorflow.python.ops.image_ops_impl import central_crop from tensorflow.python.ops.image_ops_impl import combined_non_max_suppression from tensorflow.python.ops.image_ops_impl import convert_image_dtype from tensorflow.python.ops.image_ops_impl import crop_and_resize_v1 as crop_and_resize from tensorflow.python.ops.image_ops_impl import crop_to_bounding_box from tensorflow.python.ops.image_ops_impl import decode_image from tensorflow.python.ops.image_ops_impl import draw_bounding_boxes from tensorflow.python.ops.image_ops_impl import encode_png from tensorflow.python.ops.image_ops_impl import extract_glimpse from tensorflow.python.ops.image_ops_impl import flip_left_right from tensorflow.python.ops.image_ops_impl import flip_up_down from tensorflow.python.ops.image_ops_impl import generate_bounding_box_proposals from tensorflow.python.ops.image_ops_impl import grayscale_to_rgb from tensorflow.python.ops.image_ops_impl import image_gradients from tensorflow.python.ops.image_ops_impl import is_jpeg from tensorflow.python.ops.image_ops_impl import non_max_suppression from tensorflow.python.ops.image_ops_impl import non_max_suppression_padded from tensorflow.python.ops.image_ops_impl import non_max_suppression_with_overlaps as non_max_suppression_overlaps from tensorflow.python.ops.image_ops_impl import non_max_suppression_with_scores from tensorflow.python.ops.image_ops_impl import pad_to_bounding_box from tensorflow.python.ops.image_ops_impl import per_image_standardization from tensorflow.python.ops.image_ops_impl import psnr from tensorflow.python.ops.image_ops_impl import random_brightness from tensorflow.python.ops.image_ops_impl import random_contrast from tensorflow.python.ops.image_ops_impl import random_flip_left_right from tensorflow.python.ops.image_ops_impl import random_flip_up_down from tensorflow.python.ops.image_ops_impl import random_hue from tensorflow.python.ops.image_ops_impl import random_jpeg_quality from tensorflow.python.ops.image_ops_impl import random_saturation from tensorflow.python.ops.image_ops_impl import resize_bicubic from tensorflow.python.ops.image_ops_impl import resize_bilinear from tensorflow.python.ops.image_ops_impl import resize_image_with_crop_or_pad from tensorflow.python.ops.image_ops_impl import resize_image_with_crop_or_pad as resize_with_crop_or_pad from tensorflow.python.ops.image_ops_impl import resize_image_with_pad_v1 as resize_image_with_pad from tensorflow.python.ops.image_ops_impl import resize_images from tensorflow.python.ops.image_ops_impl import resize_images as resize from tensorflow.python.ops.image_ops_impl import resize_nearest_neighbor from tensorflow.python.ops.image_ops_impl import rgb_to_grayscale from tensorflow.python.ops.image_ops_impl import rgb_to_yiq from tensorflow.python.ops.image_ops_impl import rgb_to_yuv from tensorflow.python.ops.image_ops_impl import rot90 from tensorflow.python.ops.image_ops_impl import sample_distorted_bounding_box from tensorflow.python.ops.image_ops_impl import sobel_edges from tensorflow.python.ops.image_ops_impl import ssim from tensorflow.python.ops.image_ops_impl import ssim_multiscale from tensorflow.python.ops.image_ops_impl import total_variation from tensorflow.python.ops.image_ops_impl import transpose from tensorflow.python.ops.image_ops_impl import transpose as transpose_image from tensorflow.python.ops.image_ops_impl import yiq_to_rgb from tensorflow.python.ops.image_ops_impl import yuv_to_rgb from tensorflow.python.ops.random_ops import random_crop del _print_function