import cv2
import cv2 as cv

img = cv.imread("img/lena.jpg")
tony = cv.imread("img/tony.jpg", )

# 修改lena圖片的寬高  融合圖像之前兩個(gè)圖片的寬高要保持一樣
height, width = img.shape[0:2]
new_height = int(height * 1.5)
new_width = int(width * 2)
new_img = cv2.resize(img, (new_width, new_height))

# 進(jìn)行疊加時(shí)的插值
dst = cv.addWeighted(new_img, 0.5, tony, 0.5, 0)
cv.imshow("dst", dst)

cv.waitKey(0)
cv.destroyAllWindows()

import cv2
img = cv2.imread("img/lena.jpg", cv.IMREAD_GRAYSCALE)

import cv2

img = cv2.imread("img/lena.jpg", cv.IMREAD_COLOR)
# 將原圖的所有顏色轉(zhuǎn)成灰色
dstImg = cv2.cvtColor(img, cv.COLOR_BGR2GRAY)
cv.imshow("dstImg", dstImg)
cv.waitKey(0)

import cv2 as cv

img = cv.imread("img/lena.jpg", cv.IMREAD_COLOR)
# 將原圖的所有顏色轉(zhuǎn)成灰色
dstImg = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
# 獲取高度和寬度
height, width = dstImg.shape[0:2]
# 遍歷每一個(gè)像素點(diǎn)
for row in range(height):
    for col in range(width):
        # 255 - 每一個(gè)像素點(diǎn) = 反轉(zhuǎn)后的顏色
        dstImg[row, col] = 255 - dstImg[row, col]

cv.imshow("dstImg", dstImg)
cv.waitKey(0)

import cv2 as cv

img = cv.imread("img/lena.jpg", cv.IMREAD_COLOR)
# 將原圖的所有顏色轉(zhuǎn)成灰色
dstImg = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
# 獲取高度和寬度
height, width = dstImg.shape[0:2]
# 遍歷每一個(gè)像素點(diǎn)
for row in range(height):
    for col in range(width):
        # 255 - 每一個(gè)像素點(diǎn) = 反轉(zhuǎn)后的顏色
        dstImg[row, col] = 255 - dstImg[row, col]

cv.imshow("dstImg", dstImg)
cv.waitKey(0)

import cv2

# 讀取圖片  cv2讀取出的圖片都是一個(gè)二維矩陣
img = cv2.imread('./img/lena.jpg', cv2.IMREAD_COLOR)
# 切片 兩個(gè)點(diǎn)的坐標(biāo)可以截取圖片
# x1:x2,y1:y2  截取眼睛部分
img1 = img[180:250, 180:310]
# 獲取到高度和寬度
height, width = img1.shape[0:2]
# 遍歷每一個(gè)像素點(diǎn)
for row in range(height):
    for col in range(width):
        # 如果正好為10的倍數(shù)的行并且是10的倍數(shù)的列
        if row % 10 == 0 and col % 10 == 0:
            # 獲取到這個(gè)像素點(diǎn)的bgr三原色
            b, g, r = img1[row, col]
            # 遍歷這個(gè)像素點(diǎn)旁邊的100個(gè)像素點(diǎn) 都等于中間這個(gè)像素點(diǎn)
            for i in range(10):
                for j in range(10):
                    img1[row + i, col + j] = b, g, r

cv2.imshow('img', img)

cv2.imwrite('msk_lena.jpg', img)
cv2.waitKey()

import random

import cv2
import numpy as np

img = cv2.imread('./lena.jpg')
height, width = img.shape[0:2]
new_img = np.zeros_like(img, np.uint8)
# 定義偏移量
offset = 6
# 遍歷每一個(gè)像素點(diǎn)
for row in range(height):
    for col in range(width):
        # 定義不超過1的隨機(jī)值與offset相乘
        index = int(random.random() * offset)
        # 獲取到隨機(jī)完的行號和列號   如果不超過總高度就使用隨機(jī)的行  如果超過就使用高度-1
        random_row = row + index if row + index < height else height - 1
        random_col = col + index if col + index < width else width - 1
        # 賦值顏色
        b, g, r = img[random_row, random_col]
        new_img[row, col] = b, g, r

cv2.imshow('img', img)
cv2.imshow('new_img', new_img)

cv2.waitKey()

import cv2
import numpy as np

img = cv2.imread('./lena.jpg')
# 獲取高度寬度
height, width = img.shape[0:2]
# 轉(zhuǎn)為灰度圖
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

new_img = np.zeros_like(gray_img, np.uint8)
# 遍歷每一個(gè)像素點(diǎn)
for row in range(height):
    # 因?yàn)橐@取相鄰的像素點(diǎn) 防止下標(biāo)越界提前遍歷的時(shí)候?qū)挾?1
    for col in range(width - 1):
        # 獲取像素點(diǎn)的像素值
        gray0 = gray_img[row, col]
        # 獲取相鄰像素點(diǎn)的像素值
        gray1 = gray_img[row, col + 1]
        # 使用浮雕效果的公式
        new_gray = int(gray0) - int(gray1) + 120
        # 判斷新的灰度值是否越界
        if new_gray > 255:
            new_gray = 255
        elif new_gray < 0:
            new_gray = 0
        # 賦值
        new_img[row, col] = new_gray

cv2.imshow('img', img)
cv2.imshow('new_img', new_img)

cv2.waitKey()