Created
April 20, 2020 09:44
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# kernel for image dilation | |
kernel = np.ones((4,4),np.uint8) | |
# font style | |
font = cv2.FONT_HERSHEY_SIMPLEX | |
# directory to save the ouput frames | |
pathIn = "contour_frames_3/" | |
for i in range(len(col_images)-1): | |
# frame differencing | |
grayA = cv2.cvtColor(col_images[i], cv2.COLOR_BGR2GRAY) | |
grayB = cv2.cvtColor(col_images[i+1], cv2.COLOR_BGR2GRAY) | |
diff_image = cv2.absdiff(grayB, grayA) | |
# image thresholding | |
ret, thresh = cv2.threshold(diff_image, 30, 255, cv2.THRESH_BINARY) | |
# image dilation | |
dilated = cv2.dilate(thresh,kernel,iterations = 1) | |
# find contours | |
contours, hierarchy = cv2.findContours(dilated.copy(), cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE) | |
# shortlist contours appearing in the detection zone | |
valid_cntrs = [] | |
for cntr in contours: | |
x,y,w,h = cv2.boundingRect(cntr) | |
if (x <= 200) & (y >= 80) & (cv2.contourArea(cntr) >= 25): | |
if (y >= 90) & (cv2.contourArea(cntr) < 40): | |
break | |
valid_cntrs.append(cntr) | |
# add contours to original frames | |
dmy = col_images[i].copy() | |
cv2.drawContours(dmy, valid_cntrs, -1, (127,200,0), 2) | |
cv2.putText(dmy, "vehicles detected: " + str(len(valid_cntrs)), (55, 15), font, 0.6, (0, 180, 0), 2) | |
cv2.line(dmy, (0, 80),(256,80),(100, 255, 255)) | |
cv2.imwrite(pathIn+str(i)+'.png',dmy) |
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