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count.py
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count.py
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# import the necessary packages
from imutils.video import VideoStream
from imutils.video import FPS
import argparse
import imutils
import time
import cv2
tracker = cv2.TrackerCSRT_create()
vs = cv2.VideoCapture("traffic_video.mp4")
initBB = None
detec = []
def pega_centro(x, y, w, h):
x1 = int(w / 2)
y1 = int(h / 2)
cx = x + x1
cy = y + y1
return cx,cy
roi = 380
counter = 0
offset = 6
# loop over frames from the video stream
while vs.isOpened():
ret,frame = vs.read()
cv2.line(frame, (69 , roi), (1298 , roi), (255,0,0), 3)
# check to see if we are currently tracking an object
if initBB is not None:
# grab the new bounding box coordinates of the object
(success, box) = tracker.update(frame)
# check to see if the tracking was a success
if success:
(x, y, w, h) = [int(v) for v in box]
cv2.rectangle(frame, (x, y), (x + w, y + h),
(0, 255, 0), 2)
cX = int((x + x+w) / 2.0)
cY = int((y + y+h) / 2.0)
cv2.circle(frame, (cX, cY), 3, (0, 0, 255), -1)
c=pega_centro(x, y, w, h)
detec.append(c)
for (x,y) in detec:
if y<(roi+offset) and y>(roi-offset):
counter+=1
print(counter)
cv2.line(frame, (769 , roi), (1298 , roi), (0,0,255), 3)
detec.remove((x,y))
# show the output frame
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
if key == ord("s"):
# select the bounding box of the object we want to track (make
# sure you press ENTER or SPACE after selecting the ROI)
initBB = cv2.selectROI("Frame", frame, fromCenter=False,
showCrosshair=True)
# start OpenCV object tracker using the supplied bounding box
# coordinates, then start the FPS throughput estimator as well
tracker.init(frame, initBB)
fps = FPS().start()
# if the `q` key was pressed, break from the loop
elif key == ord("q"):
break
else:
vs.release()
cv2.destroyAllWindows()