OpenCV 简单入门| Python

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Install

pip3 install --upgrade setuptools
pip3 install numpy Matplotlib
pip3 install opencv-python

Img Read and Show

Load an color image in grayscale

import numpy as np
import cv2
img = cv2.imread('messi5.jpg',0)

img read from Camera

cap = cv2.VideoCapture(0)
ret, frame = cap.read()
cap.release()
cap = cv2.VideoCapture(0)
while(True):
   ret, frame = cap.read()
   cv2.imshow('image',frame)
   if cv2.waitKey(1) & 0xFF == ord('q'):
       cv2.destroyAllWindows()
       break

Resolution of the img

cap.set(cv2.CAP_PROP_FRAME_WIDTH,1280)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT,720)

img show and close

cv2.imshow('image',img)
if cv2.waitKey(0) & 0xFF == ord('q'):
    cv2.destroyAllWindows()

resize

 cv2.resize(img, (10,10), interpolation = cv2.INTER_AREA)

img wirte

cv2.imwrite('messigray.png',img)

img to gif

Original Webpage:

• PHILOS_THU, 2017
• 执笔论英雄, 2018

import cv2
import imageio
List = ['./yang1.jpg', './yang2.jpg', './yang3.jpg']
frames = []
for img in List:
  img = cv2.imread(img, 1)
  img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
  img = cv2.resize(img, (460,360))
  frames.append(img)
gif=imageio.mimsave('yang.gif',frames,'GIF',duration=0.4)

Screen shot

import cv2
import numpy as np
from mss import mss
cords = {'top':40 , 'left': 0 , 'width': 800, 'height': 640 }
while(True):
   with mss() as sct :
       img = np.array(sct.grab(cords)) #sct.grab(cords/monitor)
   #cimg = cv2.cvtColor(img , cv2.COLOR_BGRA2GRAY)
   cv2.imshow('image',img)
   if cv2.waitKey(1) & 0xFF == ord('q'):
       cv2.destroyAllWindows()
       break
cv2.destroyAllWindows()

Draw on Img

Draw a Rectangle

reference: AlanWang4523 2018

## 绘制一个红色矩形
ptLeftTop = (120, 100)
ptRightBottom = (200, 150)
point_color = (0, 0, 255) # BGR
thickness = 1
lineType = 8
cv.rectangle(img, ptLeftTop, ptRightBottom, point_color, thickness, lineType)

Write on the image

img = cv2.imread('messi5.jpg',0)
cv2.putText(img, "Hello World" ,(200, 100), cv2.FONT_HERSHEY_COMPLEX, 2.0, (100, 200, 200), 5)

Other Tricks for image

## Blur
img = cv2.medianBlur(img,5)
## Grey
cv2.cvtColor(img,cv2.COLOR_RGB2GRAY)

Video

Video read

cap=cv2.VideoCapture("test")
while (True):
   ret,frame=cap.read()
   cv2.imshow("video",frame)
   # 在播放每一帧时，使用cv2.waitKey()设置适当的持续时间。如果设置的太低视频就会播放的非常快，如果设置的太高就会播放的很慢。通常情况下25ms就ok
   if cv2.waitKey(25)&0xFF==ord('q'):
       cv2.destroyAllWindows()
       break

Reading Video information

## fps of this Video
fps_c = cap.get(cv2.CAP_PROP_FPS)
frame _total = cap.get(cv2.CAP_PROP_FRAME_COUNT)
Video_h = cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
Video_w = cap.get(cv2.CAP_PROP_FRAME_WIDTH)

play Video and audio

##https://stackoverflow.com/questions/46864915/python-add-audio-to-video-opencv
import cv2
import numpy as np
##ffpyplayer for playing audio
from ffpyplayer.player import MediaPlayer
video_path="../L1/images/Godwin.mp4"
def PlayVideo(video_path):
    video=cv2.VideoCapture(video_path)
    player = MediaPlayer(video_path)
    while True:
        grabbed, frame=video.read()
        audio_frame, val = player.get_frame()
        if not grabbed:
            print("End of video")
            break
        if cv2.waitKey(28) & 0xFF == ord("q"):
            break
        cv2.imshow("Video", frame)
        if val != 'eof' and audio_frame is not None:
            #audio
            img, t = audio_frame
    video.release()
    cv2.destroyAllWindows()
PlayVideo(video_path)

Video write

## for normal output
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('output.avi',fourcc, 20.0, (640,480))
while true:
 out.write(frame)
## For Gray outpu
fourcc = cv2.VideoWriter_fourcc('M','J','P','G')
out = cv2.VideoWriter("outfilename.mp4", fourcc, 15, (640,480), 0)

Img to Video

import cv2, os
File = "Up"
OUTPUT = "Egg_Day1.avi"
List = os.popen('ls '+File).read().split('\n')[:-1]
img = cv2.imread(File +"/"+List[0])
fps = 24
size = (len(img[0]),len(img))
fourcc = cv2.VideoWriter_fourcc('M','J','P','G')
videowriter = cv2.VideoWriter(OUTPUT,fourcc,fps,size)
for i in List:
    img = cv2.imread(File +"/"+i)
    videowriter.write(img)
videowriter.release()

vedio to gif

from cv2 import cv2
import imageio
import numpy
# Collection of the imgs
frames_list = []
# Tossed frames per FPS. When FPS = 1, all frame are saved.
FPS = 1
cap=cv2.VideoCapture("test_1.mp4")
while (True):
  ret,frame=cap.read()
  #img = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
  img = cv2.resize(frame, (460,360))
  frames_list.append(img)
frames = []
Num =0
for img in frames_list:
  Num +=1
  if Num %3 == 0:
    frames.append(img)
gif=imageio.mimsave('test_3.gif',frames,'GIF',duration=1/8)

Video capture

##!/usr/bin/env python
## -*- coding: utf-8 -*-
## @Time    : 2019/3/7 11:43
## @Author  : HaoWANG
## @Site    :
## @File    : VideoWrite.py
## @Software: PyCharm
## 加载包
import math
import sys
import cv2
def main():
  # 初始化摄像头
  keep_processing = True;
  camera_to_use = 0;  # 0 if you have one camera, 1 or > 1 otherwise
  cap = cv2.VideoCapture(0)  # 定义视频捕获类cap
  windowName = "Live Video Capture and Write"  # 窗口名
  # opencv中视频录制需要借助VideoWriter对象， 将从VideoCapture 中读入图片，不断地写入到VideoWrite的数据流中。
  # 指定视频编解码方式为MJPG
  codec = cv2.VideoWriter_fourcc(*'MJPG')
  fps = 25.0  # 指定写入帧率为25
  frameSize = (640, 480)  # 指定窗口大小
  # # 创建 VideoWriter对象
  output = cv2.VideoWriter('VideoRecord.avi', codec, fps, frameSize)
  # 摄像头开启检测
  # error detection #
  if not (((len(sys.argv) == 2) and (cap.open(str(sys.argv[1]))))
          or (cap.open(camera_to_use))):
    print("ERROR：No video file specified or camera connected.")
    return -1
  # Camera Is Open
  # create window by name (note flags for resizable or not)
  cv2.namedWindow(windowName, cv2.WINDOW_NORMAL)
  print("按键Q-结束视频录制")
  while (cap.isOpened()):
    # 00 if video file successfully open then read frame from video
    if (keep_processing):
      ret, frame = cap.read()  # 定义read对象ret和frame帧
      # start a timer (to see how long processing and display takes)
      start_t = cv2.getTickCount()
      # 不断的从VideoCapture 中读入图片，然后写入到VideoWrite的数据流中。
      output.write(frame)
      cv2.imshow(windowName, frame)  # display image
      # stop the timer and convert to ms. (to see how long processing and display takes)
      stop_t = ((cv2.getTickCount() - start_t) / cv2.getTickFrequency()) * 1000
      # 接收键盘停止指令
      # start the event loop - essential
      # wait 40ms or less depending on processing time taken (i.e. 1000ms / 25 fps = 40 ms)
      key = cv2.waitKey(max(2, 40 - int(math.ceil(stop_t)))) & 0xFF
      # It can also be set to detect specific key strokes by recording which key is pressed
      # e.g. if user presses "q" then exit
      if (key == ord('q')):
        print("Quit Process ")
        keep_processing = False
    else:
      break
  print("The display and video write tasks take {} ms".format(stop_t))
  # release the camera and close all windows
  # 资源释放,在录制结束后，我们要释放资源：
  # # 释放资源
  cap.release()
  output.release()
  cv2.destroyAllWindows()
## end main()
if __name__ == "__main__":
  main()

Training your personal model

'''
positive list:
Pics in Me director, 55*110
Background Pics are in BG file
'''
for i in $(ls Me/);do echo Me/$i 1 0 0 55 110;done > pos.list
for i in $(ls BG/);do echo BG/$i;done > bg.list
rm models/*
opencv_createsamples  -info pos.list -vec pos.vec -bg bg.list -num 12 -w 20 -h 40
opencv_traincascade -data models/ -vec pos.vec -bg bg.list -numPos 12 -numNeg 27 -numStages 2 -featureType HAAR -w 20 -h 40
'''
s
'''
import cv2
## 探测图片中的人脸
detector = cv2.CascadeClassifier("models/params.xml") # absolute !!!
faces = detector.detectMultiScale(img)
for(x,y,w,h) in faces:
    cv2.rectangle(image,(x,y),(x+w,y+w),(0,255,0),2)

Matlibplot

## -*- coding: utf-8 -*-
"""
## --------------------------------------------------------
## @Author : panjq
## @E-mail : pan_jinquan@163.com
## @Date   : 2020-02-05 11:01:49
## --------------------------------------------------------
"""
import matplotlib.pyplot as plt
import numpy as np
import cv2
def fig2data(fig):
    """
    fig = plt.figure()
    image = fig2data(fig)
    @brief Convert a Matplotlib figure to a 4D numpy array with RGBA channels and return it
    @param fig a matplotlib figure
    @return a numpy 3D array of RGBA values
    """
    import PIL.Image as Image
    # draw the renderer
    fig.canvas.draw()
    # Get the RGBA buffer from the figure
    w, h = fig.canvas.get_width_height()
    buf = np.fromstring(fig.canvas.tostring_argb(), dtype=np.uint8)
    buf.shape = (w, h, 4)
    # canvas.tostring_argb give pixmap in ARGB mode. Roll the ALPHA channel to have it in RGBA mode
    buf = np.roll(buf, 3, axis=2)
    image = Image.frombytes("RGBA", (w, h), buf.tostring())
    image = np.asarray(image)
    return image
if __name__ == "__main__":
    # Generate a figure with matplotlib</font>
    figure = plt.figure()
    plot = figure.add_subplot(111)
    # draw a cardinal sine plot
    x = np.arange(1, 100, 0.1)
    y = np.sin(x) / x
    plot.plot(x, y)
    plt.show()
    ##
    image = fig2data(figure)
    cv2.imshow("image", image)
    cv2.waitKey(0)

Enjoy~

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