def __init__(self):
""" Initialize the street sign reocgnizer """
rospy.init_node('street_sign_recognizer')
self.cv_image = None # the latest image from the camera
# self.grid_cell = None
self.binary_image = None
self.image_info_window = None
self.bridge = CvBridge() # used to convert ROS messages to OpenCV
# self.hsv_lb = np.array([23, 175, 133]) # hsv lower bound
# self.hsv_ub = np.array([40, 255, 255]) # hsv upper bound
self.hsv_lb = np.array([0, 0, 0]) # hsv lower bound
self.hsv_ub = np.array([255, 255, 255]) # hsv upper bound
# self.grid_cell_w = 64*3
# self.grid_cell_h = 48*3
self.TM = TemplateMatcher()
self.grid = GridImage()
cv2.namedWindow('video_window')
cv2.setMouseCallback('video_window', self.process_mouse_event)
cv2.namedWindow('threshold_image')
cv2.createTrackbar('H lb', 'threshold_image', 0, 255, self.set_h_lb)
cv2.createTrackbar('S lb', 'threshold_image', 0, 255, self.set_s_lb)
cv2.createTrackbar('V lb', 'threshold_image', 0, 255, self.set_v_lb)
cv2.createTrackbar('H ub', 'threshold_image', 0, 255, self.set_h_ub)
cv2.createTrackbar('S ub', 'threshold_image', 0, 255, self.set_s_ub)
cv2.createTrackbar('V ub', 'threshold_image', 0, 255, self.set_v_ub)
rospy.Subscriber("/camera/image_raw", Image, self.process_image)
def __init__(self):
""" Initialize the street sign reocgnizer """
rospy.init_node('street_sign_recognizer')
self.cv_image = None # the latest image from the camera
self.cv_image_res = None
self.grayscale_sign = None
self.bridge = CvBridge() # used to convert ROS messages to OpenCV
cv2.namedWindow('video_window')
cv2.namedWindow('grayscale_sign_window')
rospy.Subscriber("/camera/image_raw", Image, self.process_image)
cv2.namedWindow('threshold_image')
self.hsv_lb = np.array([30, 75, 75]) # hsv lower bound
cv2.createTrackbar('H lb', 'threshold_image', 0, 360, self.set_h_lb)
cv2.createTrackbar('S lb', 'threshold_image', 0, 100, self.set_s_lb)
cv2.createTrackbar('V lb', 'threshold_image', 0, 100, self.set_v_lb)
self.hsv_ub = np.array([90, 100, 100]) # hsv upper bound
cv2.createTrackbar('H ub', 'threshold_image', 0, 360, self.set_h_ub)
cv2.createTrackbar('S ub', 'threshold_image', 0, 100, self.set_s_ub)
cv2.createTrackbar('V ub', 'threshold_image', 0, 100, self.set_v_ub)
self.tm = TemplateMatcher({
"left":
'/home/hdavidzhu/catkin_ws/src/sign_follower/images/leftturn_box_small.png',
"right":
'/home/hdavidzhu/catkin_ws/src/sign_follower/images/rightturn_box_small.png',
"uturn":
'/home/hdavidzhu/catkin_ws/src/sign_follower/images/uturn_box_small.png'
})
def __init__(self):
"""Initialize the street sign recognizer """
rospy.init_node('street_sign_recognizer')
rospy.Subscriber("sign_follower/cropped_sign", Image, self.recognize_sign)
images = {
"left": '../images/leftturn_box_small.png',
"right": '../images/rightturn_box_small.png',
"uturn": '../images/uturn_box_small.png'
}
self.tm = TemplateMatcher(images)
def __init__(self):
#init ROS node
rospy.init_node('street_sign_recognizer')
self.bridge = CvBridge() # used to convert ROS messages to OpenCV
self.image = None # the latest image from the camera
self.cv_image = None # gaussian blurred image
self.hsv_image = None # HSV form of image
self.binary_image = None # Binary form of image
self.grid_cell = None # portion of an image
self.density = 0 # amount of white in a grid cell
self.threshold = .001 # amount of white needed in a grid cell to be part of sign
#the thresholds to find the yellow color of the sign
self.hsv_lb = np.array([17, 161, 160]) # hsv lower bound
self.hsv_ub = np.array([75, 255, 255]) # hsv upper bound
# the various windows for visualization
cv2.namedWindow('HSV_window')
cv2.namedWindow('Binary_window')
cv2.namedWindow('RGB_window')
#set of template images for the Template Matcher
images = {
"left": '../images/leftturn_box_small.png',
"right": '../images/rightturn_box_small.png',
"uturn": '../images/uturn_box_small.png'
}
#variables for Template Matcher
self.matcher = TemplateMatcher(
images) # initialize Template Matcher class
self.matched_threshold = 40 # threshold to determine which sign the input is
self.total_confidence = {
'uturn': 0.0,
'left': 0.0,
'right': 0.0
} # dictionary that holds cumulative confidence of each sign
self.recognized = False #boolean to ensure only one run of the recognition
#init ROS Subscriber to camera image
rospy.Subscriber("/camera/image_raw", Image, self.process_image)
def __init__(self):
""" Initialize the street sign reocgnizer """
rospy.init_node('street_sign_recognizer')
self.cv_image = None # the latest image from the camera
self.hsv_image = None
self.res_image = None
self.mask = None
self.cropped_sign = None
self.bridge = CvBridge() # used to convert ROS messages to OpenCV
cv2.namedWindow('video_window')
rospy.Subscriber("/camera/image_raw", Image, self.process_image)
self.signpub = rospy.Publisher('/predicted_sign',
String,
queue_size=10)
self.prediction = ""
#sets up slider bars for hue isolation
#cv2.namedWindow('threshold_image')
# current values work well for uturn and right, but poorly for left
# values for left (20, 166, 139) increase error for uturn and right
self.hsv_lb = np.array(
[25, 202, 186]
) # hsv lower bound 20, 166, 139 25, 202, 186 26, 214, 167 [15, 225, 139
# cv2.createTrackbar('H lb', 'threshold_image', 0, 255, self.set_h_lb)
# cv2.createTrackbar('S lb', 'threshold_image', 0, 255, self.set_s_lb)
# cv2.createTrackbar('V lb', 'threshold_image', 0, 255, self.set_v_lb)
self.hsv_ub = np.array(
[204, 255, 255]) # hsv upper bound 204, 255, 255 204, 255, 230
# cv2.createTrackbar('H ub', 'threshold_image', 0, 255, self.set_h_ub)
# cv2.createTrackbar('S ub', 'threshold_image', 0, 255, self.set_s_ub)
# cv2.createTrackbar('V ub', 'threshold_image', 0, 255, self.set_v_ub)
# initialize template_matcher
images = {
"left": '../images/leftturn_box_small.png',
"right": '../images/rightturn_box_small.png',
"uturn": '../images/uturn_box_small.png'
}
self.tm = TemplateMatcher(images)
cv2.waitKey(5)
# cv2.imshow('image_info', self.image_info_window)
# cv2.waitKey(5)
r.sleep()
if __name__ == '__main__':
images = {
"left": '../images/leftturn_box_small.png',
"right": '../images/rightturn_box_small.png',
"uturn": '../images/uturn_box_small.png'
}
scenes = [
"../images/uturn_scene.jpg", "../images/leftturn_scene.jpg",
"../images/rightturn_scene.jpg"
]
node = StreetSignRecognizer()
node.run()
tm = TemplateMatcher(images)
for filename in scenes:
scene_img = cv2.imread(filename, 0)
pred = tm.predict(scene_img)
print filename.split('/')[-1]
print pred
def __init__(self, image_topic, sleep_topic):
""" Initialize the street sign reocgnizer """
rospy.init_node('street_sign_recognizer')
self.cv_image = None # the latest image from the camera
self.bridge = CvBridge() # used to convert ROS messages to OpenCV
self.saveCounter = 0 # how many images we've saved to disk
print "Loading TemplateMatcher"
self.template_matcher = TemplateMatcher(self.template_images)
self.pub = rospy.Publisher('predicted_sign', String, queue_size=1)
cv2.namedWindow('video_window')
self.sleeping = False
self.running_predictions = {"lturn": 0, "rturn": 0, "uturn": 0}
self.sign_pub_mappings = {
"uturn": 1,
"lturn": 2,
"rturn": 3
}
# 'use' parameters for quick changes in node functionality
self.use_slider = False
self.use_mouse_hover = False
self.use_saver = False
self.use_predict = True
# threshold by which the running confidence summation must achieve to publish a predicted_sign
# hand tuned
self.decision_threshold = 35
# # # # # # # # # # # # #
# color params, in HSV #
# # # # # # # # # # # # #
self.COLOR = "yellow" # which default color we binarize based on
self.color_bounds = {}
# tuned from the green hand ball
self.color_bounds["green"] = (
np.array([60,76,2]) # min
, np.array([80,255,255]) # max
)
# tuned from yellow lturn sign
self.color_bounds["yellow"] = (
np.array([23,175,130]) # min
, np.array([32,255,255]) # max
)
if self.use_mouse_hover:
# when mouse hovers over video window
cv2.setMouseCallback('video_window', self.process_mouse_event)
if self.use_slider:
cv2.namedWindow('threshold_image')
self.hsv_lb = np.array([0, 0, 0])
cv2.createTrackbar('H lb', 'threshold_image', 0, 255, self.set_h_lb)
cv2.createTrackbar('S lb', 'threshold_image', 0, 255, self.set_s_lb)
cv2.createTrackbar('V lb', 'threshold_image', 0, 255, self.set_v_lb)
self.hsv_ub = np.array([255, 255, 255])
cv2.createTrackbar('H ub', 'threshold_image', 0, 255, self.set_h_ub)
cv2.createTrackbar('S ub', 'threshold_image', 0, 255, self.set_s_ub)
cv2.createTrackbar('V ub', 'threshold_image', 0, 255, self.set_v_ub)
rospy.Subscriber(image_topic, Image, self.process_image)
rospy.Subscriber(sleep_topic, Bool, self.process_sleep)
def __init__(self):
""" Initialize the street sign reocgnizer """
rospy.init_node('street_sign_recognizer')
# Create TemplateMatcher object with template images
self.template_matcher = TemplateMatcher({
"left":
'../images/leftturn_box_small.png',
"right":
'../images/rightturn_box_small.png',
"uturn":
'../images/uturn_box_small.png'
})
self.bgr_image = None # the latest image from the camera
self.hsv_image = None
self.filt_image = None
self.cropped_sign_grayscale = None
self.bridge = CvBridge() # used to convert ROS messages to OpenCV
# Create windows to view video streams
cv2.namedWindow('video_window')
cv2.namedWindow('filt_window')
cv2.namedWindow('cropped_grayscale_window')
cv2.namedWindow('img_T_window')
# Create sliders to control image color filtering
cv2.namedWindow('threshold_image')
self.h_lower_bound = 25
self.h_upper_bound = 38
self.s_lower_bound = 199
self.s_upper_bound = 255
self.v_lower_bound = 203
self.v_upper_bound = 237
self.blur_amount = 3
cv2.createTrackbar('H lower bound', 'threshold_image', 0, 255,
self.set_h_lower_bound)
cv2.createTrackbar('H upper bound', 'threshold_image', 0, 255,
self.set_h_upper_bound)
cv2.createTrackbar('S lower bound', 'threshold_image', 0, 255,
self.set_s_lower_bound)
cv2.createTrackbar('S upper bound', 'threshold_image', 0, 255,
self.set_s_upper_bound)
cv2.createTrackbar('V lower bound', 'threshold_image', 0, 255,
self.set_v_lower_bound)
cv2.createTrackbar('V upper bound', 'threshold_image', 0, 255,
self.set_v_upper_bound)
cv2.createTrackbar('Blur amount', 'threshold_image', 0, 20,
self.set_blur_amount)
cv2.setTrackbarPos('H lower bound', 'threshold_image',
self.h_lower_bound)
cv2.setTrackbarPos('H upper bound', 'threshold_image',
self.h_upper_bound)
cv2.setTrackbarPos('S lower bound', 'threshold_image',
self.s_lower_bound)
cv2.setTrackbarPos('S upper bound', 'threshold_image',
self.s_upper_bound)
cv2.setTrackbarPos('V lower bound', 'threshold_image',
self.v_lower_bound)
cv2.setTrackbarPos('V upper bound', 'threshold_image',
self.v_upper_bound)
cv2.setTrackbarPos('Blur amount', 'threshold_image', self.blur_amount)
# Subscribe to ROS image stream
rospy.Subscriber("/camera/image_raw", Image, self.process_image)
