openCV API

下面列出的是api,單純線性執行以下代碼可能會跑不通

環境安裝

• conda create -n XXX（新建一個conda環境）
• Activate XXX （打開conda的某一個環境）
• pip install opencv-python （安裝opencv-python）

基本操作

import cv2
pic= cv2.imread('filename.png',0)  # 0爲只讀灰度，1爲讀BGR圖像
cv2.imshow('xxx',pic) # 在xxx窗口顯示pic圖片
cv2.watKey(0)
cv2.destoryAllWindows()
cv2.imwrite('filename.png',pic)

視頻

cap = cv2.VideoCapture('vtest.avi') 
while(cap.isOpened()):
    ret, frame = cap.read() # 讀一幀
    if ret:
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)        
        cv2.imshow('frame',gray)
    if cv2.waitKey(1) & 0xFF == ord('q')  :
         break
cap.release()
cv2.destroyAllWindows()

# 獲取攝像頭
cap = cv2.VideoCapture(-1) #攝像頭編號。
# Define the codec and create VideoWriter object
fourcc = cv2.VideoWriter_fourcc(*'XVID')#  注意編碼器
out = cv2.VideoWriter('output.avi',fourcc, 20.0, (640,480))

繪圖

# Draw a diagonal blue line with thickness of 5 px
cv2.line(img,(0,0),(511,511),(255,0,0),5)
cv2.rectangle(img,(384,0),(510,128),(0,255,0),3)
cv2.circle(img,(447,63), 63, (0,0,255), -1)
cv2.ellipse(img,(256,256),(100,50),0,0,180,255,-1)

# 多邊形
pts=np.array([[10,5],[20,30],[70,20],[50,10]], np.int32)
pts=pts.reshape((-1,1,2))
cv2.polylines(img,[pts],True,(0,255,255))

# 文字
font=cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img,'OpenCV',(10,500), font, 4,(255,255,255),6) 

鼠標

# 對某個窗口應用鼠標事件函數
cv2.namedWindow('image')
cv2.setMouseCallback('image',draw_circle)

圖像代數運算

cv2.add()
cv2.subtract(img,80)
cv2.multiply(img,1.5)
cv2.addWeighted(img1,0.7,img2,0.3,0)

img2gray = cv2.cvtColor(img2,cv2.COLOR_BGR2GRAY) # 圖片img2轉換爲灰度值
ret, mask_front = cv2.threshold(img2gray, 175, 255, cv2.THRESH_BINARY) # 門限 灰度值大於175爲1（白） 小於175爲0
mask_inv = cv2.bitwise_not(mask_front) # 取反
img1_bg = cv2.bitwise_and(img1,img1,mask = mask_front) # 圖片1扣背景
img2_fg = cv2.bitwise_and(img2,img2,mask = mask_inv) # 圖片2扣內容（背景爲白色，內容灰度值較低）
result = cv2.add(img1_bg,img2_fg) # 合併

幾何變換

res=cv2.resize(img,None,fx=2,fy=2,interpolation=cv2.INTER_CUBIC)

M=cv2.getRotationMatrix2D((cols/2,rows/2),45,0.6) # 獲得對應的旋轉矩陣
dst=cv2.warpAffine(img,M,(cols,rows)) # 仿射

# 仿射
pts1=np.float32([[50,50],[200,50],[50,200]])
pts2=np.float32([[10,100],[200,50],[100,250]])
M=cv2.getAffineTransform(pts1,pts2)

# 透視
pts1 = np.float32([[56,65],[368,52],[28,387],[389,390]])
pts2 = np.float32([[0,0],[300,0],[0,300],[300,300]])
M=cv2.getPerspectiveTransform(pts1,pts2)

直方圖

cv2:calcHist(images; channels; mask; histSize; ranges[; hist[; accumulate]])
hist = cv2.calcHist([img],[0],None,[256],[0,256])
hist,bins = np.histogram(img.ravel(),256,[0,256])

# 均衡化灰度圖
equ = cv2.equalizeHist(img)

卷積

# 計算卷積
dst = cv2.filter2D(img,-1,kernel)

blur3 = cv2.blur(img,(3,3)) # 均值
median = cv2.medianBlur(img,5) # 中值
blur = cv2.GaussianBlur(img,(5,5),0) # 高斯
laplacian=cv2.Laplacian(img,-1) # 拉普拉斯
sobelx=cv2.Sobel(img,-1,1,0,ksize=5) #sobel x方向1 y方向0

復變

f = np.fft.fft2(img)
fshift = np.fft.fftshift(f)

magnitude_spectrum = 20*np.log(np.abs(fshift)) # 進行對數處理，可視化

f_ishift = np.fft.ifftshift(fshift)
img_back = np.fft.ifft2(f_ishift)

形態學

kernel = np.ones((5,5),np.uint8) 
#kernel  = cv2.getStructuringElement(cv2.MORPH_RECT,(3, 3))
erosion = cv2.erode(img,kernel,iterations = 1) # 腐蝕
dilation = cv2.dilate(img,kernel,iterations = 1) # 膨脹
opening = cv2.morphologyEx(img, cv2.MORPH_OPEN, kernel) # 開
closing = cv2.morphologyEx(img, cv2.MORPH_CLOSE, kernel) # 閉
gradient = cv2.morphologyEx(img, cv2.MORPH_GRADIENT, kernel) # 膨脹-腐蝕 result = cv2.absdiff(dilate,erode)

形態學-閾值

ret,thresh1 = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
# 自適應閾值
th2 = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY,11,2)
th3 = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,11,2)

cv2.cvtColor(input_image，flag) # 色彩轉換
mask=cv2.inRange(hsv,lower_blue,upper_blue)  #構建掩模