first_frame = gray
continue
delta_frame = cv2.absdiff(first_frame, gray)
thresh_frame = cv2.threshold(delta_frame, 30, 255, cv2.THRESH_BINARY)[1]
thresh_frame = cv2.dilate(thresh_frame, None, iterations=2)
(cnts, _) = cv2.findContours(thresh_frame.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
for contour in cnts:
if cv2.contourArea(contour) < 10000:
continue
status = 1
(x, y, w, h) = cv2.boundRect(contour)
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 3)
status_list.append(status)
if status_list[-1] == 1 and status_list[-2] == 0:
times.append(datetime.now())
if status_list[-1] == 0 and status_list[-2] == 1:
times.append(datetime.now())
cv2.imshow("Gray Frame", gray)
cv2.imshow("Delta Frame", delta_frame)
cv2.imshow("Threshold Frame", thresh_frame)
cv2.imshow("Color Frame", frame)
key = cv2.waitKey(1)
# compute the bounding box of the contour
(x, y, w, h) = cv2.boundingRect(c)
# if the contour is sufficiently large, it must be a digit
if w >= 15 and (h >= 30 and h <= 40):
digitCnts.append(c)
# sort the contours from left-to-right, then initialize the
# actual digits themselves
digitCnts = contours.sort_contours(digitCnts, method="left-to-right")[0]
digits = []
# loop over each of the digits
for c in digitCnts:
# extract the digit ROI
(x, y, w, h) = cv2.boundRect(c)
roi = thresh[y:y + h, x:x + w]
# compute the width and height of each of the 7 segments
# we are gong to examine
(roiH, roiW) = roi.shape
(dW, dH) = (int(roiW * 0.25), int(roiH * 0.15))
dHC = int(roiH * 0.05)
# define the set of 7 segments
segments = [
((0, 0), (w, dH)), # top
((0, 0), (dW, h // 2)), # top-left
((w - dW, 0), (w, h // 2)), # top-right
((0, (h // 2) - dHC), (w, (h // 2) + dHC)), # center
((0, h // 2), (dW, h)), # bottom-left