def;
if rayon>SEILLE_RAYON:
fps=cv2.getTickFrequency()/(cv2.getTickCount()-tickmark)
cv2.putText(frame, "FPS: {:05.2f} Seuil: {:d}".format(fps, seuil), (10, 30), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, color_infos, 1)
calcule_matricule(frame)
i=0
else :
fps=cv2.getTickFrequency()/(cv2.getTickCount()-tickmark)
cv2.putText(frame, "FPS: {:05.2f} Seuil: {:d}".format(fps, seuil), (10, 30), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, color_infos, 1)
cv2.imshow('frame', frame)
i+=1
if (i==50):
image_back=meth.moyenne_images(tab_image)
i=0
if (i>=40):
tab_image[i-40]=frame
ymax = 360
SEILLE_RAYON = 20
seuil = 10
i = 0
tab_image = []
color_infos = (0, 0, 255)
video = 'voiture.mp4'
cap = cv2.VideoCapture(video)
while i < 10:
ret, frame = cap.read()
tab_image.append(frame)
i += 1
image_back = meth.moyenne_images(tab_image)
image_back = image_back[ymin:ymax, xmin:xmax]
i = 0
while True:
ret, frame = cap.read()
tickmark = cv2.getTickCount()
mask = meth.calcul_mask(frame, image_back, seuil)
elements = cv2.findContours(mask, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)[-2]
for e in elements:
## contour_area = cv2.contourArea(e)
## if (contour_area > MIN_CONTOUR_AREA) :
((x, y), rayon) = cv2.minEnclosingCircle(e)
if rayon > SEILLE_RAYON:
cv2.circle(frame, (int(x) + xmin, int(y) + ymin), 5, color_infos,