python opencv Intel Realsense 使用滑动条调整图片的曝光率

python opencv Intel Realsense 使用滑动条调整图片的曝光率_第1张图片

# -*- coding: utf-8 -*-
"""
@File    : 200113:测试跟踪条tracebackbar().py
@Time    : 2020/1/13 9:11
@Author  : Dontla
@Email   : [email protected]
@Software: PyCharm
"""
import cv2
import numpy as np


# 等比例调整图像分辨率大小
def img_resize(image):
    height, width = image.shape[0], image.shape[1]
    width_new = 1280
    height_new = 720
    # 判断图片的长宽比率
    if width / height >= width_new / height_new:
        img_new = cv2.resize(image, (width_new, int(height * width_new / width)))
    else:
        img_new = cv2.resize(image, (int(width * height_new / height), height_new))
    return img_new


def nothing(x):
    pass


# gamma函数处理
def gamma_trans(img, gamma):
    gamma_table = [np.power(x / 255.0, gamma) * 255.0 for x in range(256)]  # 建立映射表
    gamma_table = np.round(np.array(gamma_table)).astype(np.uint8)  # 颜色值为整数
    return cv2.LUT(img, gamma_table)  # 图片颜色查表。另外可以根据光强(颜色)均匀化原则设计自适应算法。


img = cv2.imread('lena_test.jpg')
# img = cv2.imread('mianhua.jpg')
img_new = img_resize(img)
print(img_new.shape)
cv2.namedWindow('win')

cv2.createTrackbar('Value of Gamma', 'win', 100, 1000, nothing)
#  创建滑块,注册回调函数 lambda x: None没有滑动时
# cv2.createTrackbar('Value of Gamma', 'win', 100, 1000, lambda x: None)

while True:
    s = cv2.getTrackbarPos('Value of Gamma', 'win')
    value_of_gamma = s * 0.01  # 压缩gamma范围,以进行精细调整
    img_gamma = gamma_trans(img_new, value_of_gamma)
    cv2.imshow('win', img_gamma)
    cv2.waitKey(1)

运行结果:
python opencv Intel Realsense 使用滑动条调整图片的曝光率_第2张图片
python opencv Intel Realsense 使用滑动条调整图片的曝光率_第3张图片
参考文章1:python opencv-批量调整图片的曝光率

参考文章2:python opencv cv2.createTrackbar()方法 getTrackbarPos()方法 (创建窗口滑动条和获取滑动条当前值)

参考文章3:opencv cv2.LUT()(使用查找表中的值填充输出数组)

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