tensorflow 图像数据处理（二）

____tz_zs

图像片段截取，图像大小调整，图像翻转以及色彩调整的整个图像预处理过程

案例来源《TensorFlow实战Google深度学习框架》

原图

处理后的图片

"""

@author: tz_zs

的图片预处理样例

"""

import tensorflow as tf

import numpy as np

import matplotlib.pyplot as plt

def distort_color(image, color_ordering=0):

if color_ordering == 0:

image = tf.image.random_brightness(image, max_delta=32. / 255.)

image = tf.image.random_saturation(image, lower=0.5, upper=1.5)

image = tf.image.random_hue(image, max_delta=0.2)

image = tf.image.random_contrast(image, lower=0.5, upper=1.5)

elif color_ordering == 1:

image = tf.image.random_saturation(image, lower=0.5, upper=1.5)

image = tf.image.random_brightness(image, max_delta=32. / 255.)

image = tf.image.random_contrast(image, lower=0.5, upper=1.5)

image = tf.image.random_hue(image, max_delta=0.2)

return tf.clip_by_value(image, 0.0, 1.0)

def preprocess_for_train(image, height, width, bbox):

if bbox is None:

bbox = tf.constant([0.0, 0.0, 1.0, 1.0], dtype=tf.float32, shape=[1, 1, 4])

if image.dtype != tf.float32:

image = tf.image.convert_image_dtype(image, dtype=tf.float32)

bbox_begin, bbox_size, _ = tf.image.sample_distorted_bounding_box(tf.shape(image), bounding_boxes=bbox)

distorted_image = tf.slice(image, bbox_begin, bbox_size)

distorted_image = tf.image.resize_images(distorted_image, [height, width], method=np.random.randint(4))

distorted_image = tf.image.random_flip_left_right(distorted_image)

distorted_image = distort_color(distorted_image, np.random.randint(2))

return distorted_image

image_raw_data = tf.gfile.FastGFile("picture.jpg", "rb").read()

with tf.Session() as sess:

img_data = tf.image.decode_jpeg(image_raw_data)

boxes = tf.constant([[[0.05, 0.05, 0.9, 0.7], [0.35, 0.47, 0.5, 0.56]]])

for i in range(6):

result = preprocess_for_train(img_data, 299, 299, boxes)

plt.imshow(result.eval())

plt.show()

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