def test_drive():
images = glob.glob("bgr_data/2019-05-09_04-48-50/" + "*.jpg")
image_num = len(images)
print(image_num)
hostname = socket.gethostname()
run_time = datetime.datetime.now().strftime('%Y%m%d%H%M%S')
folder_name = "set_" + hostname + "_" + run_time
set_path = Constant.DATA_SET_PATH + folder_name
os.makedirs(set_path)
sys.stdout = Logger(set_path + "/log.txt", sys.stdout)
de = Detector()
d = Driver()
# server = Server()
# client = Client()
# d.client = client
is_upload = True
# video_stream_thread = threading.Thread(target=server.get_video_stream)
# video_stream_thread.setDaemon(True)
# video_stream_thread.start()
# tl_state_thread = threading.Thread(target=client.get_tl_state)
# tl_state_thread.setDaemon(True)
# tl_state_thread.start()
objects_info_dict = {}
start = time.time()
# i = 0
for image in images:
print(image.split('/')[-1])
objects_info, objects_num, image_array = de.detect(cv2.imread(image))
d.objects_info = objects_info
d.objects_num = objects_num
d.image_array = image_array
cmd = d.drive()
# server.send_msg(cmd)
print("commond sent to pi: ", cmd)
# server.send_msg(cmd.encode(encoding="utf-8"))
objects_info_dict[ObjInfoKey(image_array)] = objects_info
print("* " * 50)
cv2.waitKey(1)
end = time.time()
local_path = object_dict_to_csv(objects_info_dict, folder_name)
print("local_path: ", local_path)
print(end - start)
Uploader("server_conf.conf", local_path,
Constant.SERVER_DATA_PATH).upload()
cv2.destroyAllWindows()
cv2.setTrackbarPos('UpperS', 'result', us)
cv2.createTrackbar('LowerV', 'result', 0, 255, nothing)
cv2.setTrackbarPos('LowerV', 'result', lv)
cv2.createTrackbar('UpperV', 'result', 0, 255, nothing)
cv2.setTrackbarPos('UpperV', 'result', uv)
font = cv2.FONT_HERSHEY_SIMPLEX
while 1:
# Threshold the HSV image
frame, hsv = get_frame()
mask = cv2.inRange(hsv, lower_hsv, upper_hsv)
if mode in ['ball', 'basket']:
result, _, cy, _, _, h = detector.detect(frame, hsv, lower_hsv,
upper_hsv)
# print("Lower border: " + str(int(round(cy + h/2))))
else:
result = cv2.bitwise_and(frame, frame, mask=mask)
if mode == 'hough':
# result = frame
circles = cv2.HoughCircles(mask,
cv2.HOUGH_GRADIENT,
1,
20,
param1=30,
param2=14,
minRadius=0,
maxRadius=0)
if circles is not None:
circles = np.uint16(np.around(circles))
self.image_idx += 1
if __name__ == '__main__':
try:
cam_proc = RealsenseProcessing()
cam_proc.run()
rate = rospy.Rate(RATE)
i = 0
while not rospy.is_shutdown():
cam_proc.get_frame()
ball_detector = Detector(
osp.join(COLOR_CONFIG_PATH, "ball_green.txt"), "BallDetector",
"ball")
ball_res, cx, cy, contour_area, w, h = ball_detector.detect(
cam_proc.regular_image, cam_proc.hsv)
cam_proc.pub_ball.publish(Point(cx, cy, 0))
basket_detector = Detector(
osp.join(COLOR_CONFIG_PATH,
"basket_{}.txt".format(BASKET_COLOR)),
"BasketDetector", "basket")
basket_res, basket_cx, basket_cy, basket_contour_area, basket_w, basket_h = basket_detector.detect(
cam_proc.regular_image, cam_proc.hsv)
cam_proc.pub_basket.publish(
Point(basket_cx, int(round(basket_cy + basket_h / 2)), 0))
# print("Lower border: " + str(int(round(basket_cy + basket_h/2))))
if i % int(RATE * SAVE_FREQUENCY
) == 0 and i != 0: # for debugging/analysis purposes
squareness = round((float(min(w, h)) / max(w, h)) *