def main():
args = get_arguments()
state = True
if args['webcam'] != -1:
camera = cv2.VideoCapture(0)
elif args['picamera'] != -1:
camera = VideoStream(usePiCamera=args['picamera'] > 0).start()
camera.resolution = (640, 480)
camera.brightness = 25
camera.framerate = 30
time.sleep(2.0)
elif args['query']:
# load the query image, compute the ratio of the old height to the new height, clone it, and resize it
image = cv2.imread(args['query'])
#image = imutils.resize(image, height=300)
# kernel to filter noise
kernel = np.ones((5, 5), np.uint8)
while state:
if args['webcam'] != -1:
ret, image = camera.read()
if not ret:
break
elif args['picamera'] != -1:
image = camera.read()
elif args['query']:
state = False
# show original image
#originale = image.copy()
#cv2.imshow("Originale", originale)
# convert the image to grayscale, blur it, and find edges
# in the image
image = cv2.convertScaleAbs(image, beta=-255)
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
thresh = cv2.inRange(hsv, (30, 100, 70), (150, 255, 255))
opening = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)
opening = cv2.morphologyEx(opening, cv2.MORPH_OPEN, kernel)
hsv = cv2.bilateralFilter(opening, 15, 17,
17) # bilateral filter to keep edges
cv2.imshow("HSV", hsv)
edged = cv2.Canny(hsv, 30, 200)
# find contours in the edged image, keep only the largest
# ones, and initialize our screen contour
im2, cnts, hierarchy = cv2.findContours(edged.copy(), cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
cnts.sort(key=cv2.contourArea, reverse=True)
# loop over our contours to find number of bottles in image
nb_bottles = 0
for c in cnts:
# approximate the contour
peri = cv2.arcLength(c, True)
area = cv2.contourArea(c, True)
approx = cv2.approxPolyDP(c, 0.03 * peri, True)
# if our approximated contour has four points, then we can assume that we have found our screen
print(cv2.isContourConvex(approx))
print(area)
if 20 <= abs(area) <= 5000 and 4 <= len(
approx) <= 8 and cv2.isContourConvex(approx):
nb_bottles += 1
cv2.drawContours(image, [approx], -1, (0, 255, 0), 3)
cv2.imshow("Edges", edged)
cv2.imshow("Image with rectangle", image)
print("Number of bottles: {}".format(nb_bottles))
if args['query']:
cv2.waitKey(0)
if cv2.waitKey(1) & 0xFF is ord('q'):
break
