def main():
"""Programme principal"""
try:
while True:
camera.capture(stream, format='bgr')
stream.truncate(0)
data = stream.array # Image capturée
imgHoughLines = data.copy() # Création d'une copie de l'image
# Reconnaissance lignes
imgGray = cv2.cvtColor(data, cv2.COLOR_BGR2GRAY) # Conversion en niveau de gris
imgEdges = cv2.Canny(imgGray, 70, 70, apertureSize=3) # Binarisation de l'image
houghLines = cv2.HoughLines(imgEdges, 3, 3*numpy.pi/180, 100) # Transformée de Hough Lines
middleLine = libRI.getMiddleLine(houghLines) # Acquisition ligne de la route
if middleLine is not None:
print("Deviation : " + str(-1*libRI.lineToAngle((middleLine[0], middleLine[1]))))
arduino.Send("#deviation;" + str(-1*libRI.lineToAngle((middleLine[0], middleLine[1]))) + ";")
except Exception as e:
print(str(e))
finally:
arduino.Send("#stop;#kp;0;#kd;0;#ki;0;")
camera.close()
stream.close()
arduino.close()
def main():
"""Fonction main"""
sock = socket.socket()
sock.connect((TCP_IP, TCP_PORT))
print("Socket ouvert")
# Création des barres de réglages
cv2.namedWindow('Reglages')
cv2.resizeWindow('Reglages', 400, 400)
cv2.createTrackbar("t1", "Reglages", 70, 255, nothing) # Seuil houghlines t1
cv2.createTrackbar("t2", "Reglages", 70, 255, nothing) # Seuil houghlines t2
cv2.createTrackbar("Threshold", "Reglages", 100, 500, nothing) # Longueur minimale admissible d'un segment
cv2.createTrackbar("minDist", "Reglages", 110, 255, nothing) # distance minimale entre chaque cercles de houghcircles
cv2.createTrackbar("param1", "Reglages", 70, 255, nothing)
cv2.createTrackbar("param2", "Reglages", 70, 255, nothing)
cv2.createTrackbar("minRadius", "Reglages", 70, 255, nothing) # rayon cercle minimum
cv2.createTrackbar("maxRadius", "Reglages", 85, 255, nothing) # rayon cercle maximum
while(True):
length = recvall(sock, 16)
if(length):
stringData = recvall(sock, int(length))
data = numpy.fromstring(stringData, dtype='uint8').reshape(resolution[1], resolution[0], -1) #Image reçue
imgHoughLines = data.copy() # Création d'une copie de l'image
imgHoughCircle = data.copy() # Création d'une copie de l'image
#----------------------------------------------------------------------
# Actualisation paramètres
t1 = cv2.getTrackbarPos("t1", "Reglages")
t2 = cv2.getTrackbarPos("t2", "Reglages")
HoughLinesThreshold = cv2.getTrackbarPos("Threshold", "Reglages")
mindist = cv2.getTrackbarPos("minDist", "Reglages")
p1 = cv2.getTrackbarPos("param1", "Reglages")
p2 = cv2.getTrackbarPos("param2", "Reglages")
minR = cv2.getTrackbarPos("minRadius", "Reglages")
maxR = cv2.getTrackbarPos("maxRadius", "Reglages")
# Reconnaissance lignes
imgGray = cv2.cvtColor(data, cv2.COLOR_BGR2GRAY) # Conversion en niveau de gris
imgEdges = cv2.Canny(imgGray, t1, t2, apertureSize=3) # Binarisation de l'image
houghLines = cv2.HoughLines(imgEdges, 3, 3*numpy.pi/180, HoughLinesThreshold) # Transformée de Hough Lines
imgHoughLines = libRI.drawLines(imgHoughLines, libRI.keepHorizontalLines(houghLines)) # Tracée lignes horizontales
imgHoughLines = libRI.drawLines(imgHoughLines, libRI.keepVerticalLines(houghLines), color=(0,255,0)) # Tracée lignes verticales
middleLine = libRI.getMiddleLine(houghLines) # Acquisition ligne de la route
if middleLine is not None:
imgHoughLines = libRI.drawLine(imgHoughLines, middleLine[0], middleLine[1], color=(0,255,255)) # Trace la ligne à suivre par le robot
print("Deviation : " + str(libRI.lineToAngle((middleLine[0], middleLine[1])))) # Affichage de l'erreur angulaire
# Reconnaissance cercle et couleur
imgBlurred = cv2.medianBlur(imgGray, 5)
houghCircles = cv2.HoughCircles(imgBlurred, cv2.HOUGH_GRADIENT, 3, mindist, param1=p1, param2=p2, minRadius=minR, maxRadius=maxR) # Transformée de HoughCircle
if houghCircles is not None:
houghCircles = numpy.uint16(numpy.around(houghCircles))
for i in houghCircles[0,:]:
cv2.circle(imgHoughCircle, (i[0], i[1]), i[2], (0, 255, 0), 2) # Affichage cercles
cv2.circle(imgHoughCircle, (i[0], i[1]), 2, (0, 0, 255), 3) # Affichage centres des cercles
color = libRI.getPixelColor(data, (i[0], i[1])) # Affichage couleur pixel
if(i[0] > 320 and color[0] < 220 and color[0] > 90 and color[1] < 160 and color[1] > 110 and color[2] < 80 and color[2] > 35):
print("Panneau stop bleu detecte !\r\n")
# Affichage des images
cv2.imshow("imgEdges", imgEdges);
cv2.imshow("imgHoughLines", imgHoughLines);
cv2.imshow("imgHoughCircle", imgHoughCircle);
#----------------------------------------------------------------------
if(cv2.waitKey(1) & 0xFF == ord('q')):
break
sock.close()
print("Socket closed")
cv2.destroyAllWindows()
def main():
"""Fonction main"""
sock = socket.socket()
sock.connect((TCP_IP, TCP_PORT))
print("Socket ouvert")
# Création des barres de réglages
cv2.namedWindow('Reglages')
cv2.resizeWindow('Reglages', 400, 400)
cv2.createTrackbar("t1", "Reglages", 70, 255,
nothing) # Seuil houghlines t1
cv2.createTrackbar("t2", "Reglages", 70, 255,
nothing) # Seuil houghlines t2
cv2.createTrackbar("Threshold", "Reglages", 100, 500,
nothing) # Longueur minimale admissible d'un segment
cv2.createTrackbar(
"minDist", "Reglages", 110, 255,
nothing) # distance minimale entre chaque cercles de houghcircles
cv2.createTrackbar("param1", "Reglages", 70, 255, nothing)
cv2.createTrackbar("param2", "Reglages", 70, 255, nothing)
cv2.createTrackbar("minRadius", "Reglages", 70, 255,
nothing) # rayon cercle minimum
cv2.createTrackbar("maxRadius", "Reglages", 85, 255,
nothing) # rayon cercle maximum
while (True):
length = recvall(sock, 16)
if (length):
stringData = recvall(sock, int(length))
data = numpy.fromstring(stringData, dtype='uint8').reshape(
resolution[1], resolution[0], -1) #Image reçue
imgHoughLines = data.copy() # Création d'une copie de l'image
imgHoughCircle = data.copy() # Création d'une copie de l'image
#----------------------------------------------------------------------
# Actualisation paramètres
t1 = cv2.getTrackbarPos("t1", "Reglages")
t2 = cv2.getTrackbarPos("t2", "Reglages")
HoughLinesThreshold = cv2.getTrackbarPos("Threshold", "Reglages")
mindist = cv2.getTrackbarPos("minDist", "Reglages")
p1 = cv2.getTrackbarPos("param1", "Reglages")
p2 = cv2.getTrackbarPos("param2", "Reglages")
minR = cv2.getTrackbarPos("minRadius", "Reglages")
maxR = cv2.getTrackbarPos("maxRadius", "Reglages")
# Reconnaissance lignes
imgGray = cv2.cvtColor(
data, cv2.COLOR_BGR2GRAY) # Conversion en niveau de gris
imgEdges = cv2.Canny(imgGray, t1, t2,
apertureSize=3) # Binarisation de l'image
houghLines = cv2.HoughLines(
imgEdges, 3, 3 * numpy.pi / 180,
HoughLinesThreshold) # Transformée de Hough Lines
imgHoughLines = libRI.drawLines(
imgHoughLines, libRI.keepHorizontalLines(
houghLines)) # Tracée lignes horizontales
imgHoughLines = libRI.drawLines(
imgHoughLines,
libRI.keepVerticalLines(houghLines),
color=(0, 255, 0)) # Tracée lignes verticales
middleLine = libRI.getMiddleLine(
houghLines) # Acquisition ligne de la route
if middleLine is not None:
imgHoughLines = libRI.drawLine(
imgHoughLines,
middleLine[0],
middleLine[1],
color=(0, 255,
255)) # Trace la ligne à suivre par le robot
print("Deviation : " +
str(libRI.lineToAngle(
(middleLine[0],
middleLine[1])))) # Affichage de l'erreur angulaire
# Reconnaissance cercle et couleur
imgBlurred = cv2.medianBlur(imgGray, 5)
houghCircles = cv2.HoughCircles(
imgBlurred,
cv2.HOUGH_GRADIENT,
3,
mindist,
param1=p1,
param2=p2,
minRadius=minR,
maxRadius=maxR) # Transformée de HoughCircle
if houghCircles is not None:
houghCircles = numpy.uint16(numpy.around(houghCircles))
for i in houghCircles[0, :]:
cv2.circle(imgHoughCircle, (i[0], i[1]), i[2], (0, 255, 0),
2) # Affichage cercles
cv2.circle(imgHoughCircle, (i[0], i[1]), 2, (0, 0, 255),
3) # Affichage centres des cercles
color = libRI.getPixelColor(
data, (i[0], i[1])) # Affichage couleur pixel
if (i[0] > 320 and color[0] < 220 and color[0] > 90
and color[1] < 160 and color[1] > 110
and color[2] < 80 and color[2] > 35):
print("Panneau stop bleu detecte !\r\n")
# Affichage des images
cv2.imshow("imgEdges", imgEdges)
cv2.imshow("imgHoughLines", imgHoughLines)
cv2.imshow("imgHoughCircle", imgHoughCircle)
#----------------------------------------------------------------------
if (cv2.waitKey(1) & 0xFF == ord('q')):
break
sock.close()
print("Socket closed")
cv2.destroyAllWindows()