# encoding:utf-8
# 使用TensorFlow进行图片的放缩
import tensorflow as tf
import cv2
import numpy as np

# 读取图片
img = cv2.imread("1.jpg")
# 显示原始图片
cv2.imshow("resource", img)

h, w, depth = img.shape
img = np.expand_dims(img, 0)

# 临界点插值
nn_image = tf.image.resize_nearest_neighbor(img, size=[h+100, w+100])
nn_image = tf.squeeze(nn_image)
with tf.Session() as sess:
  # 运行 'init' op
  nn_image = sess.run(nn_image)
nn_image = np.uint8(nn_image)

# 双线性插值
bi_image = tf.image.resize_bilinear(img, size=[h+100, w+100])
bi_image = tf.squeeze(bi_image)
with tf.Session() as sess:
  # 运行 'init' op
  bi_image = sess.run(bi_image)
bi_image = np.uint8(bi_image)

# 双立方插值算法
bic_image = tf.image.resize_bicubic(img, size=[h+100, w+100])
bic_image = tf.squeeze(bic_image)
with tf.Session() as sess:
  # 运行 'init' op
  bic_image = sess.run(bic_image)
bic_image = np.uint8(bic_image)
# 显示结果图片
cv2.imshow("result_nn", nn_image)
cv2.imshow("result_bi", bi_image)
cv2.imshow("result_bic", bic_image)
cv2.waitKey(0)
cv2.destroyAllWindows()

# encoding:utf-8
# 使用TensorFlow调整图片的亮度
import tensorflow as tf
import cv2
import numpy as np

# 读取图片
img = cv2.imread("1.jpg")
# 显示原始图片
cv2.imshow("resource", img)

img = np.expand_dims(img, 0)
# adjust_brightness
bright_img = tf.image.adjust_brightness(img, delta=.5)
bright_img = tf.squeeze(bright_img)
with tf.Session() as sess:
  # 运行 'init' op
  result = sess.run(bright_img)
result = np.uint8(result)

rand_image = tf.image.random_brightness(img, max_delta=.5)
rand_image = tf.squeeze(rand_image)
with tf.Session() as sess:
  # 运行 'init' op
  result2 = sess.run(rand_image)
result2 = np.uint8(result2)

cv2.imshow("result", result)
cv2.imshow("result2", result2)
cv2.waitKey(0)
cv2.destroyAllWindows()

tf.image.adjust_saturation（） 

# encoding:utf-8
# 使用TensorFlow调整图片的亮度
import tensorflow as tf
import cv2
import numpy as np

# 读取图片
img = cv2.imread("1.jpg")
# 显示原始图片
cv2.imshow("resource", img)

# 图像的饱和度调整
stand_img = tf.image.adjust_saturation(img, saturation_factor=2.4)
with tf.Session() as sess:
  # 运行 'init' op
  result = sess.run(stand_img)
result = np.uint8(result)

cv2.imshow("result", result)
cv2.waitKey(0)
cv2.destroyAllWindows()

tf.image.per_image_standardization（） 

# encoding:utf-8
# 使用TensorFlow调整图片的亮度
import tensorflow as tf
import cv2
import numpy as np

# 读取图片
img = cv2.imread("1.jpg")
# 显示原始图片
cv2.imshow("resource", img)

# 图像标准化操作
stand_img = tf.image.per_image_standardization(img)
with tf.Session() as sess:
  # 运行 'init' op
  result = sess.run(stand_img)
result = np.uint8(result)

cv2.imshow("result", result)
cv2.waitKey(0)
cv2.destroyAllWindows()

tf.image.rgb_ to_hsv（） 
tf.image.rgb_ to_grayscale（） 
tf.image.hsv_ to_rgb（）