python 實(shí)時(shí)調(diào)取攝像頭的示例代碼

第python實(shí)時(shí)調(diào)取攝像頭的示例代碼ret,thresh=cv2.threshold(img,127,255,0)

contours,hierarchy=cv2.findContours(thresh,1,2)

cnt=contours[0]

#近似輪廓

epsilon=0.1*cv2.arcLength(cnt,True)

approx=cv2.approxPolyDP(cnt,epsilon,True)

img=cv2.drawContours(img,approx,-1,(0,255,0),3)

cv2.imwrite("4.jpg",img)

frommatplotlibimportpyplotasplt

#圖像識(shí)別/匹配

img_rgb=cv2.imread('why174.png')

img_gray=cv2.cvtColor(img_rgb,cv2.COLOR_BGR2GRAY)

img2=img_gray.copy()

template=cv2.imread('0temp.png',0)

w,h=template.shape[::-1]

#共有六種識(shí)別方法

methods=['cv2.TM_CCOEFF','cv2.TM_CCOEFF_NORMED','cv2.TM_CCORR','cv2.TM_CCORR_NORMED','cv2.TM_SQDIFF','cv2.TM_SQDIFF_NORMED']

formethinmethods:

img=img2.copy()

#eval返回某個(gè)式子的計(jì)算結(jié)果

method=eval(meth)

#下面使用匹配方法

res=cv2.matchTemplate(img,template,method)

min_val,max_val,min_loc,max_loc=cv2.minMaxLoc(res)

ifmethodin[cv2.TM_SQDIFF,cv2.TM_SQDIFF_NORMED]:

top_left=min_loc

else:

top_left=max_loc

bottom_right=(top_left[0]+w,top_left[1]+h)

#畫(huà)矩形把他框出來(lái)

cv2.rectangle(img,top_left,bottom_right,255,2)

plt.subplot(121),plt.imshow(res,cmap='gray')

plt.title('MatchingResult'),plt.xticks([]),plt.yticks([])

plt.subplot(122),plt.imshow(img,cmap='gray')

plt.title('DetectedPoint'),plt.xticks([]),plt.yticks([])

plt.suptitle(meth)

plt.show()

#這個(gè)匹配結(jié)果太差

#選取3，5，6的匹配方式會(huì)稍微好點(diǎn)：cv2.TM_CCORR；cv2.TM_SQDIFF，cv2.TM_SQDIFF_NORMED

#視頻人臉識(shí)別

#/wsywb111/article/details/79152425

importcv2

fromPILimportImage

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

#告訴Opencv使用人臉識(shí)別分類(lèi)器

classfier=cv2.CascadeClassifier("E:\\0yfl\\opencv-master\\data\\haarcascades\\haarcascade_frontalface_alt2.xml")

count=0

whilecap.isOpened():

ret,frame=cap.read()

ifnotret:

break

grey=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)

faceRect=classfier.detectMultiScale(grey,scaleFac