Python-Opencv 基本操作

下面完整代码在github仓库：传送门

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一、在图片上画线

import cv2

img = cv2.imread("1.jpg", 0)  # 默认1为真彩色，0为灰色

# opencv的图像模式是BGR
cv2.line(img, (10, 10), (100, 100), [0, 0, 255], 3)
cv2.imshow("", img)
cv2.waitKey(10000)
cv2.destroyAllWindows()

二、图像通道BGR转换RGB

import cv2
from PIL import Image

img = cv2.imread("1.jpg")

cv2.line(img, (10, 10), (100, 100), [0, 0, 255], 3)
cv2.rectangle(img, (10, 10), (100, 100), [0, 0, 255], 3)

# h, w, c
# img = img[:, :, ::-1]  # ::-1表示将RGB倒序输出
# BGR通道的图像转换成RGB的图像
img = img[..., ::-1]
img = Image.fromarray(img)
img.show()

三、画矩形框

import cv2
from PIL import Image

img = cv2.imread("1.jpg")
cv2.line(img, (10, 10), (100, 100), [0, 0, 255], 3)
cv2.rectangle(img, (10, 10), (100, 100), [0, 0, 255], 3)

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

四、图片变形

import cv2

img = cv2.imread("1.jpg")
# print(type(img))
# print(img)

img_size = img.shape
print(img_size)
img = cv2.resize(img, (img_size[1]//2, img_size[0]//2))

cv2.imshow("img", img)
cv2.waitKey(10000)
cv2.destroyAllWindows()
cv2.imwrite("2.jpg", img)

五、opencv转换到PIL

import cv2
from PIL import Image
import numpy as np

# 从opencv转换到PIL
img_arr = cv2.imread("3.jpeg")
img_arr = cv2.cvtColor(img_arr, cv2.COLOR_BGR2RGB)  # 改变通道
img = Image.fromarray(img_arr)  # 改变图像数据类型
img.show()

六、利用opencv播放视频

import cv2

path = "1.mp4"  # 本地视频路径
# path = r"http://vfx.mtime.cn/Video/2019/03/19/mp4/190319125415785691.mp4"  # 在线视频路径

# cap = cv2.VideoCapture(0)  # 调取内置摄像头
cap = cv2.VideoCapture(path)  # 获取视频对象

fps = cap.get(cv2.CAP_PROP_FPS)  # 从视频对象中获取帧数
print(fps)

w = int(cap.get(3))  # 获取图片的宽度
h = int(cap.get(4))  # 获取图片的高度
# print(w)
# print(h)


fourc = cv2.VideoWriter_fourcc(*"DVIX")  # 视频格式
out = cv2.VideoWriter("2.mp4", fourc, fps, (w, h))  # 写入视频格式

font = cv2.FONT_HERSHEY_COMPLEX
# frame表示读出的每一张图片, ret表示这一张图片是否存在
while True:
    ret, frame = cap.read()
    # 将十六进制数据转成 二进制数据
    if cv2.waitKey(int(1000 / fps)) & 0xFF == ord("q"):  # 视频在播放的过程中按键，循环会中断）。
        break
    elif ret == False:  # 视频播放完了，循环自动中断。
        break
    cv2.rectangle(frame, (200, 50), (300, 150), [0, 0, 255], 3)
    out.write(frame)

    # 前面的1表示字体大小，后面的1表示字体厚度, lineType抗锯齿
    cv2.putText(frame, "beautiful girl 啊", (100, 100), font, 1, (0, 0, 255), 1, lineType=cv2.LINE_AA)
    cv2.imshow("", frame)

cap.release()  # 将视频关了
cv2.destroyAllWindows()

七、PIL转换到Opencv

import cv2
from PIL import Image
import numpy as np

# 从PIL转换到opencv
img = Image.open("3.jpeg")
img_arr = np.array(img)  # 从图像数据转成numpy数据类型

img_arr = cv2.cvtColor(img_arr, cv2.COLOR_RGB2BGR)  # 转通道
cv2.imshow("", img_arr)
cv2.waitKey(0)

img_arr = img_arr[..., ::-1]

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

八、合成图片通道

import cv2
from PIL import Image

img = cv2.imread("1.jpg")

b, g, r = cv2.split(img)

cv2.imshow("b", b)  # 显示灰度图
cv2.imshow("g", g)
cv2.imshow("r", r)

img = cv2.merge([g, r, b])  # 合成通道
cv2.imshow("", img)
cv2.waitKey(0)
cv2.destroyAllWindows()

九、给视频图像加滤波

import cv2
import numpy as np
from PIL import Image, ImageFilter

cap = cv2.VideoCapture("1.mp4")

fps = cap.get(cv2.CAP_PROP_FPS)
while True:
    ret, frame = cap.read()
    img_arrs = frame[..., ::-1]
    imgs = Image.fromarray(img_arrs)

    img = imgs.filter(ImageFilter.MinFilter(5))
    img_arr = np.array(img)[..., ::-1]
    cv2.imshow("", img_arr)

    if cv2.waitKey(int(1000/fps)) & 0xFF == ord("q"):
        break
    elif ret == False:
        break

cap.release()  # 关闭视频
cv2.destroyAllWindows()  # 关闭窗口

十、视频图像变灰度

import cv2
import numpy as np
from PIL import Image, ImageFilter

cap = cv2.VideoCapture("1.mp4")

fps = cap.get(cv2.CAP_PROP_FPS)
while True:
    ret, frame = cap.read()
    # img1 = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    img1 = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)  # HSV是连续的色彩空间

    cv2.imshow("", img1)

    if cv2.waitKey(int(1000/fps)) & 0xFF == ord("q"):
        break
    elif ret == False:
        break

cap.release()  # 关闭视频
cv2.destroyAllWindows()  # 关闭窗口

十一、找视频图像轮廓

import cv2
import numpy as np
from PIL import Image, ImageFilter

cap = cv2.VideoCapture("1.mp4")

fps = cap.get(cv2.CAP_PROP_FPS)
while True:
    ret, frame = cap.read()

    img_arr = frame[..., ::-1]
    img1 = Image.fromarray(img_arr)

    # img2 = img1.filter(ImageFilter.CONTOUR)  # 图像轮廓
    # img2 = img1.filter(ImageFilter.EMBOSS)
    img2 = cv2.cvtColor(img_arr, cv2.COLOR_RGB2GRAY)

    img3_arr = np.array(img2)[..., ::-1]  # 转数据类型和通道
    cv2.imshow("", img3_arr)

    if cv2.waitKey(int(1000/fps)) & 0xFF == ord("q"):
        break
    elif ret == False:
        break

cap.release()  # 关闭视频
cv2.destroyAllWindows()  # 关闭窗口

十二、通道分离

import cv2
import numpy as np

img_arr = np.empty([400, 400, 3], np.uint8)  # 生成空矩阵
print(img_arr)

# [0, 0, 255]
img_arr[..., 0] = 0
img_arr[..., 1] = 0
img_arr[..., 2] = 255  # 将第三个通道的像素值填为255

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

import cv2
from PIL import Image

# 将图像变为单通道
img = cv2.imread("1.jpg")

img[..., 1] = 0
img[..., 2] = 0

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

十三、通道填值

import cv2
import numpy as np

img_arr = np.zeros([400, 400, 3], np.uint8)
# img_arr = np.ones([400, 400, 3])

# img_arr = np.arange(400*400*3).reshape([400, 400, 3]) / (400*400*3)
# img_arr = np.random.rand(400, 400, 3)
# img_arr = np.random.randn(400, 400, 3)
# img_arr = np.random.normal(0, 0.5, (400, 400, 3))

cv2.imshow("", img_arr)  # opencv中 像素值填0-1之间的值
cv2.waitKey(0)
cv2.destroyAllWindows()

本文地址：https://blog.csdn.net/liu1073811240/article/details/109902964