OpenCV with Python in 4 Hours-course-master（一）

编程语言 2022-08-11 04:27:28 阅读次数: 0

OpenCV with Python in 4 Hours-course-master（一）

编译环境：Jupyter Notebook (Anaconda3)

调用的包：matplotlib，cv2

文章目录

一、资料地址

https://github.com/Wattson1128/OpenCV教程&Demos

Demos中不能理解得英文单词我直接贴得原文。

二、Section_1

1. basic_functions.py

读取图片：

import cv2 as cv

# Read in an image
img = cv.imread('D:/IDE/Python38_Files/OpenCV Demos/opencv-course-master/Resources/Photos/park.jpg')
#D:\IDE\Python38_Files\OpenCV Demos\opencv-course-master\Resources
cv.imshow('Park', img)

image-20211223140322058

读取灰度图片：

# Converting to grayscale
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
cv.imshow('Gray', gray)

image-20211223140331165

模糊图片：

# Blur 
blur = cv.GaussianBlur(img, (7,7), cv.BORDER_DEFAULT)
cv.imshow('Blur', blur)

边缘图片：

# Edge Cascade
canny = cv.Canny(blur, 125, 175)
cv.imshow('Canny Edges', canny)

image-20211223140313024

稀释边缘？：

# Dilating the image
dilated = cv.dilate(canny, (7,7), iterations=3)
cv.imshow('Dilated', dilated)

image-20211223140308651

Eroding：

# Eroding
eroded = cv.erode(dilated, (7,7), iterations=3)
cv.imshow('Eroded', eroded)

image-20211223140503787

缩放图片：

# Resize
resized = cv.resize(img, (500,500), interpolation=cv.INTER_CUBIC)
cv.imshow('Resized', resized)

image-20211223140704216

裁剪图片：

# Cropping
cropped = img[50:200, 200:400]
cv.imshow('Cropped', cropped)

image-20211223140719866

关闭窗口：

cv.waitKey(0)

2. contours.py

读取图片：

import cv2 as cv
import numpy as np

img = cv.imread('D:/IDE/Python38_Files/OpenCV Demos/opencv-course-master/Resources/Photos/cats.jpg')
cv.imshow('Cats', img)

image-20211223141041650

blank：

blank = np.zeros(img.shape, dtype='uint8')
cv.imshow('Blank', blank)

image-20211223141058355

读取灰度图片：

gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
cv.imshow('Gray', gray)

image-20211223141112800

读取模糊图片：

blur = cv.GaussianBlur(gray, (5,5), cv.BORDER_DEFAULT)
cv.imshow('Blur', blur)

image-20211223141119705

边缘化：

canny = cv.Canny(blur, 125, 175)
cv.imshow('Canny Edges', canny)

image-20211223141127448

找出轮廓点：

contours, hierarchies = cv.findContours(canny, cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE)
print(f'{
      
      len(contours)} contour(s) found!')

image-20211223141200122

绘出轮廓：

cv.drawContours(blank, contours, -1, (0,0,255), 1)
cv.imshow('Contours Drawn', blank)

image-20211223141152188

3. draw.py

Blank：

import cv2 as cv
import numpy as np

blank = np.zeros((500,500,3), dtype='uint8')
cv.imshow('Blank', blank)

image-20211223141624317

绘制第一个矩形：

# 1. Paint the image a certain colour
blank[200:300, 300:400] = 0,0,255
cv.imshow('Green', blank)

image-20211223141629621

绘制第二个矩形：

# 2. Draw a Rectangle
cv.rectangle(blank, (0,0), (blank.shape[1]//2, blank.shape[0]//2), (0,255,0), thickness=-1)
cv.imshow('Rectangle', blank)

image-20211223141637861

绘制圆形：

# 3. Draw A circle
cv.circle(blank, (blank.shape[1]//2, blank.shape[0]//2), 40, (0,0,255), thickness=-1)
cv.imshow('Circle', blank)

image-20211223141641759

绘制线：

# 4. Draw a line
cv.line(blank, (100,250), (300,400), (255,255,255), thickness=3)
cv.imshow('Line', blank)

image-20211223141648159

绘制文本：

# 5. Write text
cv.putText(blank, 'Hello, my name is Jason!!!', (0,225), cv.FONT_HERSHEY_TRIPLEX, 1.0, (0,255,0), 2)
cv.imshow('Text', blank)

image-20211223141657919

4. read.py

读取图片后按0播放视频：

#pylint:disable=no-member

import cv2 as cv

img = cv.imread('D:/IDE/Python38_Files/OpenCV Demos/opencv-course-master/Resources/Photos/cats.jpg')
cv.imshow('Cats', img)

cv.waitKey(0)

# Reading Videos
capture = cv.VideoCapture('D:/IDE/Python38_Files/OpenCV Demos/opencv-course-master/Resources/Videos/dog.mp4')

while True:
    isTrue, frame = capture.read()
    
    # if cv.waitKey(20) & 0xFF==ord('d'):
    # This is the preferred way - if `isTrue` is false (the frame could 
    # not be read, or we're at the end of the video), we immediately
    # break from the loop. 
    if isTrue:    
        cv.imshow('Video', frame)
        if cv.waitKey(20) & 0xFF==ord('d'):
            break            
    else:
        break

capture.release()
cv.destroyAllWindows()

image-20211223141946960

image-20211223141951294

5. thresh.py

读取BGR灰度图片：

import cv2 as cv

img = cv.imread('D:/IDE/Python38_Files/OpenCV Demos/opencv-course-master/Resources/Photos/cats.jpg')

gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
cv.imshow('Gray', gray)

image-20211223142244277

Simple Thresholded：

# Simple Thresholding
threshold, thresh = cv.threshold(gray, 150, 255, cv.THRESH_BINARY )
cv.imshow('Simple Thresholded', thresh)

image-20211223142250028

Simple Thresholded Inverse：

threshold, thresh_inv = cv.threshold(gray, 150, 255, cv.THRESH_BINARY_INV )
cv.imshow('Simple Thresholded Inverse', thresh_inv)

image-20211223142257552

Adaptive Thresholding：

# Adaptive Thresholding
adaptive_thresh = cv.adaptiveThreshold(gray, 255, cv.ADAPTIVE_THRESH_GAUSSIAN_C, cv.THRESH_BINARY_INV, 11, 9)
cv.imshow('Adaptive Thresholding', adaptive_thresh)

image-20211223142309015

6. transformations.py

读取图片：

#pylint:disable=no-member

import cv2 as cv
import numpy as np

img = cv.imread('D:/IDE/Python38_Files/OpenCV Demos/opencv-course-master/Resources/Photos/park.jpg')
cv.imshow('Park', img)

image-20211223142610844

移动图片：

def translate(img, x, y):
    transMat = np.float32([[1,0,x],[0,1,y]])
    dimensions = (img.shape[1], img.shape[0])
    return cv.warpAffine(img, transMat, dimensions)

# -x --> Left
# -y --> Up
# x --> Right
# y --> Down

translated = translate(img, -100, 100)
cv.imshow('Translated', translated)

image-20211223142617843

旋转图片：

translated = translate(img, -100, 100)
cv.imshow('Translated', translated)

# Rotation
def rotate(img, angle, rotPoint=None):
    (height,width) = img.shape[:2]

    if rotPoint is None:
        rotPoint = (width//2,height//2)
    
    rotMat = cv.getRotationMatrix2D(rotPoint, angle, 1.0)
    dimensions = (width,height)

    return cv.warpAffine(img, rotMat, dimensions)

rotated = rotate(img, -45)
cv.imshow('Rotated', rotated)

rotated_rotated = rotate(img, -90)
cv.imshow('Rotated Rotated', rotated_rotated)

image-20211223142635223

缩放图片：

# Resizing
resized = cv.resize(img, (500,500), interpolation=cv.INTER_CUBIC)
cv.imshow('Resized', resized)

image-20211223142648158

倒转图片：

# Flipping
flip = cv.flip(img, -1)
cv.imshow('Flip', flip)

image-20211223142657642

裁剪图片：

# Cropping
cropped = img[200:400, 300:400]
cv.imshow('Cropped', cropped)

image-20211223142710207

三、Section_2

1. bitwise.py

绘制底层图片：

#pylint:disable=no-member

import cv2 as cv
import numpy as np

blank = np.zeros((400,400), dtype='uint8')

绘制矩形与原型：

rectangle = cv.rectangle(blank.copy(), (30,30), (370,370), 255, -1)
circle = cv.circle(blank.copy(), (200,200), 200, 255, -1)

cv.imshow('Rectangle', rectangle)
cv.imshow('Circle', circle)

image-20211223143559869

image-20211223143606527

绘制圆角矩形（融合矩形与圆形）：

# bitwise AND --> intersecting regions
bitwise_and = cv.bitwise_and(rectangle, circle)
cv.imshow('Bitwise AND', bitwise_and)

image-20211223143611961

重叠矩形与圆形：

# bitwise OR --> non-intersecting and intersecting regions
bitwise_or = cv.bitwise_or(rectangle, circle)
cv.imshow('Bitwise OR', bitwise_or)

image-20211223143617546

重叠矩形与圆形（挖出重叠部分）：

# bitwise XOR --> non-intersecting regions
bitwise_xor = cv.bitwise_xor(rectangle, circle)
cv.imshow('Bitwise XOR', bitwise_xor)

image-20211223143623026

填充非圆形部分：

# bitwise NOT
bitwise_not = cv.bitwise_not(circle)
cv.imshow('Circle NOT', bitwise_not)

image-20211223143629189

2. blurring.py

平均模糊：

# Averaging
average = cv.blur(img, (3,3))
cv.imshow('Average Blur', average)

image-20211223143804934

高斯模糊：

# Gaussian Blur
gauss = cv.GaussianBlur(img, (3,3), 0)
cv.imshow('Gaussian Blur', gauss)

image-20211223143820277

中值模糊：

# Median Blur
median = cv.medianBlur(img, 3)
cv.imshow('Median Blur', median)

image-20211223143829883

Bilateral：

# Bilateral
bilateral = cv.bilateralFilter(img, 10, 35, 25)
cv.imshow('Bilateral', bilateral)

image-20211223143826422

3. colour_spaces.py

读取BGR灰度图片：

import cv2 as cv
import matplotlib.pyplot as plt

img = cv.imread('D:/IDE/Python38_Files/OpenCV Demos/opencv-course-master/Resources/Photos/park.jpg')
cv.imshow('Park', img)

# plt.imshow(img)
# plt.show()

# BGR to Grayscale
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
cv.imshow('Gray', gray)

image-20211223144302567

image-20211223144251341

BGR转HSV：

# BGR to HSV
hsv = cv.cvtColor(img, cv.COLOR_BGR2HSV)
cv.imshow('HSV', hsv)

image-20211223144312237

BGR转LAB：

# BGR to L*a*b
lab = cv.cvtColor(img, cv.COLOR_BGR2LAB)
cv.imshow('LAB', lab)

image-20211223144318290

BGR转RGB：

# BGR to RGB
rgb = cv.cvtColor(img, cv.COLOR_BGR2RGB)
cv.imshow('RGB', rgb)

image-20211223144323876

LAB转BGR：

# HSV to BGR
lab_bgr = cv.cvtColor(lab, cv.COLOR_LAB2BGR)
cv.imshow('LAB --> BGR', lab_bgr)

image-20211223144350746

image-20211223144338959

4. gradients.py

读取灰度图片并转为Laplacian：

#pylint:disable=no-member

import cv2 as cv
import numpy as np

img = cv.imread('D:/IDE/Python38_Files/OpenCV Demos/opencv-course-master/Resources/Photos/park.jpg')
cv.imshow('Park', img)

gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
cv.imshow('Gray', gray)

# Laplacian
lap = cv.Laplacian(gray, cv.CV_64F)
lap = np.uint8(np.absolute(lap))
cv.imshow('Laplacian', lap)

image-20211223144601475

image-20211223144609107

Sobel：

# Sobel 
sobelx = cv.Sobel(gray, cv.CV_64F, 1, 0)
sobely = cv.Sobel(gray, cv.CV_64F, 0, 1)
combined_sobel = cv.bitwise_or(sobelx, sobely)

cv.imshow('Sobel X', sobelx)
cv.imshow('Sobel Y', sobely)
cv.imshow('Combined Sobel', combined_sobel)

image-20211223144657451

image-20211223144704040

image-20211223144714486

描边灰度图片：

canny = cv.Canny(gray, 150, 175)
cv.imshow('Canny', canny)

image-20211223144725527

5. histogram.py

绘制圆框图片：

import cv2 as cv
import matplotlib.pyplot as plt
import numpy as np

img = cv.imread('D:/IDE/Python38_Files/OpenCV Demos/opencv-course-master/Resources/Photos/cats.jpg')
cv.imshow('Cats', img)

blank = np.zeros(img.shape[:2], dtype='uint8')

# gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
# cv.imshow('Gray', gray)

mask = cv.circle(blank, (img.shape[1]//2,img.shape[0]//2), 100, 255, -1)

masked = cv.bitwise_and(img,img,mask=mask)
cv.imshow('Mask', masked)

image-20211223154735696

绘制图片色彩分布：

# Colour Histogram

plt.figure()
plt.title('Colour Histogram')
plt.xlabel('Bins')
plt.ylabel('# of pixels')
colors = ('b', 'g', 'r')
for i,col in enumerate(colors):
    hist = cv.calcHist([img], [i], mask, [256], [0,256])
    plt.plot(hist, color=col)
    plt.xlim([0,256])

plt.show()

cv.waitKey(0)

image-20211223154746189

6. masking.py

读取图片并绘制底层：

#pylint:disable=no-member

import cv2 as cv
import numpy as np

img = cv.imread('D:/IDE/Python38_Files/OpenCV Demos/opencv-course-master/Resources/Photos/cats 2.jpg')
cv.imshow('Cats', img)

blank = np.zeros(img.shape[:2], dtype='uint8')
cv.imshow('Blank Image', blank)

绘制半圆：

circle = cv.circle(blank.copy(), (img.shape[1]//2 + 45,img.shape[0]//2), 100, 255, -1)

rectangle = cv.rectangle(blank.copy(), (30,30), (370,370), 255, -1)

weird_shape = cv.bitwise_and(circle,rectangle)
cv.imshow('Weird Shape', weird_shape)

image-20211223155105416

结合半圆与猫：

masked = cv.bitwise_and(img,img,mask=weird_shape)
cv.imshow('Weird Shaped Masked Image', masked)

image-20211223155113009

7. rescale_resize.py

读取视频：

capture = cv.VideoCapture('D:/IDE/Python38_Files/OpenCV Demos/opencv-course-master/Resources/Videos/dog.mp4')

绘制视频边框：

def rescaleFrame(frame, scale=0.75):
    # Images, Videos and Live Video
    width = int(frame.shape[1] * scale)
    height = int(frame.shape[0] * scale)

    dimensions = (width,height)

    return cv.resize(frame, dimensions, interpolation=cv.INTER_AREA)

播放视频：

while True:
    isTrue, frame = capture.read()

    frame_resized = rescaleFrame(frame, scale=.2)
    
    cv.imshow('Video', frame)
    cv.imshow('Video Resized', frame_resized)

    if cv.waitKey(20) & 0xFF==ord('d'):
        break

capture.release()
cv.destroyAllWindows()

image-20211223155452446

8. splitmerge.py

读取图片：

#pylint:disable=no-member

import cv2 as cv
import numpy as np

img = cv.imread('D:/IDE/Python38_Files/OpenCV Demos/opencv-course-master/Resources/Photos/park.jpg')
cv.imshow('Park', img)

分离blue green red：

blank = np.zeros(img.shape[:2], dtype='uint8')

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

blue = cv.merge([b,blank,blank])
green = cv.merge([blank,g,blank])
red = cv.merge([blank,blank,r])


cv.imshow('Blue', blue)
cv.imshow('Green', green)
cv.imshow('Red', red)

image-20211223155728425

image-20211223155735478

image-20211223155742948

合并BGR：

merged = cv.merge([b,g,r])
cv.imshow('Merged Image', merged)

image-20211223155749084

四、总结

通过学习本篇资料学习了OpenCV的基本函数与图形编程的基础知识。

五、参考文章

OpenCV with Python in 4 Hours-course-master

六、源代码

https://github.com/Wattson1128/Artificial-Intelligence-Machine-Learning

猜你喜欢

转载自blog.csdn.net/ChenJ_1012/article/details/122109906
今日推荐
开源日报 | Chrome内置Gemini的意义不在于Gemini；中国AI追随之路的五大误区；ECharts创始人“下海”养鱼；谷歌I/O开发者大会什么都有，只是没有惊喜
微软回应中国区AI团队“打包赴美”传闻
基于大语言模型的开源知识库问答系统 MaxKB GitHub Star 数量突破 5,000 个！
美国拟限制 AI 大模型出口中国和俄罗斯
苹果将与 OpenAI 达成协议，将 ChatGPT 应用于 iPhone
openKylin 社区生态委员会第六次会议圆满召开
阿里云正式发布通义千问 2.5
Python 3.13 发布首个 Beta：实验性自由线程模式和 JIT、改进交互式解释器
Stack Overflow 拿我的代码去训练 AI 大模型，还封了我的账号
Pop!_OS 的 COSMIC 桌面完成 App Store 上架工作
《2024 年一季度互联网投融资运行情况》研究报告
报告：Django 仍然是 74% 开发者的首选
周排行
laravle中orm简单的增删改查
文本分类 特征选取之CHI开方检验
Spark核心编程-WordCount
大数据开发实战系列之电信客服(1)
读书笔记 - 把时间当作朋友 by 李笑来
python 笔记--if else
SpringBoot/Mybatis/Druid, 多数据源MultiDataSource配置思路
排序三个整数
redis集群搭建【2】-Windows中Redis集群搭建
STM32F030驱动TM1650点亮4联数码管
每日归档
更多
2024-05-16(6)
2024-05-15(24)
2024-05-14(0)
2024-05-13(18)
2024-05-12(0)
2024-05-11(38)
2024-05-10(38)
2024-05-09(35)
2024-05-08(42)
2024-05-07(14)

代码天地 © 2018 codetd.com

境外服务器   最新电视剧2022