while (cap.isOpened()):
t = time.time()
l = []
press_count = 0
#grabbing a frame
_, img = cap.read()
#preprocessing
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, th1 = cv2.threshold(gray, thresh, 255, cv2.THRESH_TOZERO)
cv2.imshow('threshold', th1)
# contour detection and getting the contours with minArea and maxArea
_, contours, hierarchy = cv2.findContours(th1.copy(), cv2.RETR_EXTERNAL, 2)
cnts = ut.getContourBiggerThan(contours, minArea=3000, maxArea=40000)
if len(cnts) == 1:
mouse_enable = True
else:
mouse_enable = False
#processing the contrours
for cnt in cnts:
x, y, w, h = cv2.boundingRect(cnt)
#predicting the hand pose
_, resp = ut.getGestureImg(cnt, img, th1, model)
#calculating the centroid of the hand
M = cv2.moments(cnt)
cx = int(M['m10'] / M['m00'])
if frame_count==80:
color=(0,255,0)
if frame_count==100:
thresh=cv2.mean(gray[165:315,270:370])
thresh=thresh[0]-15
break
while(cap.isOpened()):
t=time.time()
_,img=cap.read()
gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
ret,th1 =cv2.threshold(gray,thresh,255,cv2.THRESH_TOZERO)
cv2.imshow('threshold',th1)
_,contours,hierarchy = cv2.findContours(th1.copy(),cv2.RETR_EXTERNAL, 2)
cnts=ut.getContourBiggerThan(contours,minArea=3000,maxArea=40000)
line=[]
for cnt in cnts:
x,y,w,h = cv2.boundingRect(cnt)
_,resp=ut.getGestureImg(cnt,img,th1,model)
M = cv2.moments(cnt)
cx = int(M['m10']/M['m00'])
cy = int(M['m01']/M['m00'])
line.append((cx,cy))
cv2.circle(img,(cx,cy),5,[0,255,0],-1)
cv2.putText(img,resp,(x,y), font,1,(255,255,255),2,cv2.LINE_AA)
if len(line)==2:
pt1=line[0]
pt2=line[1]
ang=int(ut.getSlope(pt1,pt2))
cv2.putText(img,'Angle-> '+str(ang),(400,50), font,1,(255,255,255),2,cv2.LINE_AA)