Python opencv操作深入详解

直接读取图片

def display_img(file="p.jpeg"):
  img = cv.imread(file)
  print (img.shape)
  cv.imshow('image',img)
  cv.waitkey(0)
  cv.destroyallwindows()

读取灰度图片

def display_gray_img(file="p.jpeg"):
  img = cv.imread(file,cv.imread_grayscale)
  print (img.shape)
  cv.imshow('image',img)
  cv.waitkey(0)
  cv.destroyallwindows()
  cv.imwrite("gray_img.png",img)

读取视频

def display_video(file="sj.mp4"):
  v = cv.videocapture(file)
  if v.isopened():
    open,frame = v.read()
  else:
    open=false

  while open:
    ret,frame = v.read()
    if frame is none:
      break
  
    if ret == true:
      gray = cv.cvtcolor(frame,cv.color_bgr2gray)
      cv.imshow("result",gray)
      if cv.waitkey(10) & 0xff == 27:
        break
  v.release()
  v.waitkey(0)
  v.destroyallwindows()

截取图片

def get_frame_img(file="p.jpeg"):
  img = cv.imread(file)
  print (img.shape)
  cat = img[0:200,0:200]
  cv.imshow('get_frame_img',cat)
  cv.waitkey(0)
  cv.destroyallwindows()

提取rgb通道

def extrats_rgb_img(file="p.jpeg"):
  img = cv.imread(file)
  b,g,r = cv.split(img)
  print (b.shape,g.shape,r.shape)
  new_img = cv.merge((b,g,r))
  print (new_img.shape)

  copy_img_r = img.copy()
  copy_img_r[:,:,0]=0
  copy_img_r[:,:,1]=0
  cv.imshow("r_img",copy_img_r)

  copy_img_g = img.copy()
  copy_img_g[:,:,0]=0
  copy_img_g[:,:,2]=0
  cv.imshow("g_img",copy_img_g)

  copy_img_b = img.copy()
  copy_img_b[:,:,1]=0
  copy_img_b[:,:,2]=0
  cv.imshow("b_img",copy_img_b)

边界填充

def border_fill_img(file="p.jpeg"):
  border_type = [
    cv.border_replicate,#复制法，复制边缘
    cv.border_reflect, #反射法，对感兴趣的图像中的像素在两边进行复制
    cv.border_reflect_101,#反射法，以边缘像素为轴，对称
    cv.border_wrap,#外包装法
    cv.border_constant#常量法，常量填充
    ]
  border_title = [
    "replicate",
    "reflect",
    "reflect_101",
    "wrap",
    "constant"
    ]
  img = cv.imread(file)
  top_size,bottom_size,left_size,right_size = (50,50,50,50)
  plt.subplot(231)
  plt.imshow(img,"gray")#原始图像
  plt.title("orignal")

  for i in range(len(border_type)):
    result = cv.copymakeborder(img,top_size,bottom_size,left_size,right_size,border_type[i])
    plt.subplot(232+i)
    plt.imshow(result,"gray")
    plt.title(border_title[i])

  plt.show()

图像融合，变换

def img_compose(file1="tu.jpeg",file2="gui.jpeg"):
  img_1 = cv.imread(file1)
  img_2 = cv.imread(file2)
  print (img_1.shape)
  print (img_2.shape)
  img_1= cv.resize(img_1,(500,500))
  img_2= cv.resize(img_2,(500,500))
  print (img_1.shape)
  print (img_2.shape)
  res = cv.addweighted(img_1,0.4,img_2,0.6,0)
  plt.imshow(res)
  plt.show()


  res = cv.resize(img_1,(0,0),fx=3,fy=1)
  plt.imshow(res)
  plt.show()

  res = cv.resize(img_2,(0,0),fx=1,fy=3)
  plt.imshow(res)
  plt.show()

二值化处理

def binarization(filepath):
  img = cv2.imread(filepath,0)
  limit = 120
  ret,thresh=cv2.threshold(img,limit,255,cv2.thresh_binary_inv)
  plt.imshow(thresh,'gray')
  plt.show()
  return thresh
binarization('t1.jpg')

到此这篇关于python opencv操作深入详解的文章就介绍到这了,更多相关python opencv操作内容请搜索www.887551.com以前的文章或继续浏览下面的相关文章希望大家以后多多支持www.887551.com！