def main():
#Define flags for face detection and background detection
face_flag = 0
bg_flag = 1
start_flag = 0
stop_flag = 0
#Set arbitrary limits
wait_limit = 45 # number of frames before ending action
area_limit = 0 # pixels squared
#About a delay with a threshold of 50 (intensity)
fgbg = cv2.createBackgroundSubtractorMOG2(500,50)
bgLim = 10000
#Parse all of the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video",
help = "path to the (optional) video file")
args = vars(ap.parse_args())
# if no video, use webcam
if not args.get("video", False):
nome = 0
else:
nome = args["video"]
# Capture first frame
cap = cv2.VideoCapture(nome)
ret, frame = cap.read()
if cap.isOpened():
print "Success\n"
else:
print "Unable to open file/webcam"
return
# Create some random colors
color = np.random.randint(0,255,(100,3))
#Find face if flagged
if face_flag == 1:
minSkin,maxSkin = findMinMaxHand(frame)#findMinMaxSkin(frame)
#print minSkin
#print maxSkin
#Initialize arrays, counters, masks, etc
objectx_old = []
objecty_old = []
bg_cnt = 0
ct1 = 0
ct2 = 0
start_cnt = 0
stop_cnt = 0
sz = np.shape(frame)
mask = np.zeros(shape=(sz[0],sz[1],3,20), dtype = np.uint8)
mask_old = np.copy(mask)
tim = np.zeros(20)
#Loop through each frame
while(cap.isOpened()):
#If background subtraction is on, do that
if bg_flag == 1:
#if bg_cnt <= bgLim:
fgmask = fgbg.apply(frame)
#bg_cnt = bg_cnt+1;
#print "Apply BG Sub"
masked_frame = cv2.bitwise_and(frame,frame,mask = fgmask)
else:
masked_frame = frame
#If face detection is on, use personalized skin hue for binary conversion
if face_flag == 1:
binary_frame = personalSkin2BW(masked_frame,minSkin,maxSkin)
#else:
# binary_frame = skin2BW(masked_frame)
frame = cv2.line(frame,(40,200),(600,200),(0,255,0),2)
#crop_img = frame[200:600, 40:600]
binary_frame = skin2BW(frame)
binary_frame[0:199][:] = 0
cv2.imshow('BW Frame',binary_frame)
#Find blobs in binary image
__ , contours, contoursOut, defects = blob2(binary_frame,frame,area_limit)
if not defects == []:
#print "Defects Exist\n"
#Check flags to see what text should be displayed...
if start_flag == 0 and stop_flag == 0:
#print "Looking for start"
start_flag = startGest(frame,contoursOut,defects)
if start_flag == 1 and start_cnt < 10:
start_cnt = start_cnt+1
start_flag = 0
else:
start_cnt = 0
stop_flag = 0
elif start_flag == 1 and ct1<10:
cv2.putText(frame,"Start", (50,50), cv2.FONT_HERSHEY_SIMPLEX, 2, 2)
print "Start"
ct1 = ct1+1
ct2 = 0
elif start_flag == 1 and ct1>=10:
#print "Looking for stop"
stop_flag = stopGest(frame,contoursOut,defects)
if stop_flag == 1 and stop_cnt < 10:
stop_cnt = stop_cnt+1
stop_flag = 0
else:
stop_cnt = 0
(frame,objectx_old,objecty_old,mask,mask_old) = trackObj2(frame,contours,objectx_old,objecty_old,mask,mask_old,area_limit)
if stop_flag == 1 and ct2 < 10:
cv2.putText(frame,"Stop", (50,50), cv2.FONT_HERSHEY_SIMPLEX, 2, 2)
print "Stop"
start_flag = 0
#Increment frame counter
ct1 = 0
ct2 = ct2+1
elif stop_flag == 1 and ct2 >= 10:
start_flag = 0
stop_flag = 0
ct1 = 0
ct2 = 0
#Clear out all flags after being stopped for X amount of time
start_flag = 0
stop_flag = 0
ct1 = 0
ct2 = 0
print "Output mask created. \n"
mask_output = mask_old
#print mask_output
objectx_old = []
objecty_old = []
else:
print "Defects do not exist\n"
#Show frame with magic applied
cv2.imshow('frame',frame)
#Check for break code
if cv2.waitKey(1) & 0xFF == ord('q'):
break
ret, frame = cap.read()
cap.release()
cv2.destroyAllWindows()
def main():
#Define flags for face detection and background detection
face_flag = 0
bg_flag = 1
gest_flag = 1
#Flags used for collection of data
start_flag = 0
stop_flag = 0
#Set arbitrary limits
wait_limit = 45 # number of frames before ending action
area_limit = 500 # pixels squared
#About a delay with a threshold of 50 (intensity)
fgbg = cv2.createBackgroundSubtractorMOG2(50000,100)
#Parse all of the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video",
help = "path to the (optional) video file")
args = vars(ap.parse_args())
# if no video, use webcam
if not args.get("video", False):
nome = 0
else:
nome = args["video"]
# Capture first frame
cap = cv2.VideoCapture(nome)
ret, frame = cap.read()
if cap.isOpened():
print "Success\n"
else:
print "Unable to open file/webcam"
return
# Create some random colors
color = np.random.randint(0,255,(100,3))
#Find face if flagged
if face_flag == 1:
minSkin,maxSkin = findMinMaxHand(frame)#findMinMaxSkin(frame)
#print minSkin
#print maxSkin
#Initialize arrays, counters, masks, etc
objectx_old = []
objecty_old = []
#Starting all of the counters
ct = 0
ct1 = 0
ct2 = 0
start_cnt = 0
stop_cnt = 0
#Creating mask arrays
sz = np.shape(frame)
mask = np.zeros(shape=(sz[0],sz[1],3,20), dtype = np.uint8)
mask_old = np.copy(mask)
tim = np.zeros(20)
#Loop through each frame
while(cap.isOpened()):
#If background subtraction is on, do that
if bg_flag == 1:
fgmask = fgbg.apply(frame)
masked_frame = cv2.bitwise_and(frame,frame,mask = fgmask)
else:
masked_frame = frame
#If face detection is on, use personalized skin hue for binary conversion
if face_flag == 1:
binary_frame = personalSkin2BW(masked_frame,minSkin,maxSkin)
#elif gest_flag == 1:
# frame = cv2.line(frame,(40,200),(600,200),(0,255,0),2)
# crop_img = frame[200:600, 40:600]
# binary_frame = skin2BW(crop_img)
else:
binary_frame = skin2BW(masked_frame)
#Find blobs in binary image
if gest_flag == 1:
__ , contours, contoursOut, defects = blob2(binary_frame,frame,area_limit)
else:
frame, contours = blob(binary_frame,frame,area_limit)
#Show binary image
cv2.imshow('frame',binary_frame)
#Check if a frame was found
if not ret == False:
if gest_flag == 1:
if not defects == []:
if start_flag == 0 and stop_flag == 0:
print "Looking for start..."
#cv2.waitKey(10)
#os.system("pause")
start_flag = startGest(frame,contoursOut,defects)
(start_flag,start_cnt,ct2) = testGest(start_flag,start_cnt,ct2)
stop_flag = 0
img = frame
elif start_flag == 1 and ct1<10:
cv2.putText(frame,"Start",(50,50),cv2.FONT_HERSHEY_SIMPLEX,2,2)
print "Start"
ct1 = ct1+1
ct2 = 0
stop_flag = 0
#print "ct1"
#print ct1
#cv2.waitKey(27)
(img,objectx_old,objecty_old,mask,mask_old) = trackObj2(frame,contours,objectx_old,objecty_old,mask,mask_old, area_limit)
elif start_flag == 1 and ct1 >= 10:
#Looking for stop...
#print "Looking for stop ..."
stop_flag = stopGest(frame,contoursOut,defects)
(stop_flag,stop_cnt,ct1) = testGest(stop_flag,stop_cnt,ct1)
#print stop_cnt
if stop_flag == 1:
start_flag = 0
(img,objectx_old,objecty_old,mask,mask_old) = trackObj2(frame,contours,objectx_old,objecty_old,mask,mask_old,area_limit)
elif stop_flag == 1 and ct2 < 1:
#Stop Gesture collection
cv2.putText(frame,"Stop",(50,50),cv2.FONT_HERSHEY_SIMPLEX,2,2)
print "Stop"
#start_flag = 0
ct1 = 0
ct2 = ct2+1
img = frame
elif stop_flag == 1 and ct2 >= 10:
#Clear out all flags after being stopped for X amount of time
start_flag = 0
stop_flag = 0
ct1 = 0
ct2 = 0
print "Output mask created. \n"
mask_output = mask_old
objectx_old = []
objecty_old = []
img = frame
else: #If the defects aren't found, do nothing
#print "Defects do not exist. \n"
img = frame
else: #If not using the gestures to start and stop the function...
#Initialize variable which change with each frame
(img,objectx_old,objecty_old,mask,mask_old,tim) = trackObj(frame,contours,objectx_old,objecty_old,mask,mask_old,area_limit,tim)
#If the frame was not found o' so long ago...
else:
break
#Increment frame counter
ct = ct+1
#Show frame with magic applied
cv2.imshow('frame',img)
#Check for break code
if cv2.waitKey(1) & 0xFF == ord('q'):
break
ret, frame = cap.read()
cap.release()
cv2.destroyAllWindows()
