def contour_match(self, img):
'''
Returns 1. Image with bounding boxes added
2. an ObstacleImageDetectionList
'''
object_list = ObstacleImageDetectionList()
object_list.list = []
height,width = img.shape[:2]
object_list.imwidth = width
object_list.imheight = height
# get filtered contours
cone_contours = self.get_filtered_contours(img, "CONE")
duck_contours = self.get_filtered_contours(img, "DUCK_COLOR")
all_contours = [duck_contours, cone_contours]
for i, contours in enumerate(all_contours):
for (cnt, box, ds, aspect_ratio, mean_color) in contours:
# plot box around contour
x,y,w,h = box
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img,self.terms[i], (x,y), font, 0.5,mean_color,4)
cv2.rectangle(img,(x,y),(x+w,y+h), mean_color,2)
r = Rect()
r.x = x
r.y = y
r.w = w
r.h = h
t = ObstacleType()
t.type = i
d = ObstacleImageDetection()
d.bounding_box = r
d.type = t
object_list.list.append(d);
return img, object_list
def contour_match(self, img):
'''
Returns 1. Image with bounding boxes added
2. an ObstacleImageDetectionList
'''
object_list = ObstacleImageDetectionwithimageList()
object_list.list = []
height, width = img.shape[:2]
object_list.imwidth = width
object_list.imheight = height
# get filtered contours
x, y, w, h, img = self.get_filtered_contours(img)
object_list.im = self.bridge1.cv2_to_imgmsg(img, "bgr8")
r = Rect()
r.x = x
r.y = y
r.w = w
r.h = h
rospy.loginfo("the x,y,h,w is")
rospy.loginfo(str(x))
rospy.loginfo(str(y))
rospy.loginfo(str(w))
rospy.loginfo(str(h))
#t = ObstacleType()
#t.type =
d = ObstacleImageDetection()
d.bounding_box = r
#d.type = t
object_list.list.append(d)
return img, object_list
def contour_match(self, img):
#rospy.loginfo("[static_object_detector_node] [4.0] in contour_match.")
'''
Returns 1. Image with bounding boxes added
2. an ObstacleImageDetectionList
'''
object_list = ObstacleImageDetectionList()
object_list.list = []
height,width = img.shape[:2]
object_list.imwidth = width
object_list.imheight = height
# get filtered contours
#rospy.loginfo("[static_object_detector_node] [4.1] before get_filtered_contours.")
try:
cone_contours = self.get_filtered_contours(img, "CONE")
except Exception as e:
rospy.loginfo("[static_object_detector_node] [4.1.5] get_filtered_contours ERROR. %s" %(e))
#rospy.loginfo("[static_object_detector_node] [4.2] after get_filtered_contours.")
# disable duck detection
# duck_contours = self.get_filtered_contours(img, "DUCK_COLOR")
# disable duck detection
# all_contours = [duck_contours, cone_contours]
all_contours = [[], cone_contours]
for i, contours in enumerate(all_contours):
for (cnt, box, ds, aspect_ratio, mean_color) in contours:
# plot box around contour
x,y,w,h = box
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img,self.terms[i], (x,y), font, 0.5,mean_color,4)
cv2.rectangle(img,(x,y),(x+w,y+h), mean_color,2)
r = Rect()
r.x = x
r.y = y
r.w = w
r.h = h
t = ObstacleType()
t.type = i
d = ObstacleImageDetection()
d.bounding_box = r
d.type = t
object_list.list.append(d);
return img, object_list
def contour_match(self, img):
'''
Returns 1. Image with bounding boxes added
2. an ObstacleImageDetectionList
'''
object_list = ObstacleImageDetectionList()
object_list.list = []
height, width = img.shape[:2]
object_list.imwidth = width
object_list.imheight = height
# get filtered contours
cone_contours = self.get_filtered_contours(img, "CONE")
duck_contours = self.get_filtered_contours(img, "DUCK_COLOR")
all_contours = [duck_contours, cone_contours]
for i, contours in enumerate(all_contours):
for (cnt, box, ds, aspect_ratio, mean_color) in contours:
# plot box around contour
x, y, w, h = box
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img, self.terms[i], (x, y), font, 0.5, mean_color,
4)
cv2.rectangle(img, (x, y), (x + w, y + h), mean_color, 2)
r = Rect()
r.x = x
r.y = y
r.w = w
r.h = h
t = ObstacleType()
t.type = i
d = ObstacleImageDetection()
d.bounding_box = r
d.type = t
object_list.list.append(d)
return img, object_list
def contour_match(img):
# rospy.loginfo("contour_match")
object_list = ObstacleImageDetectionList()
object_list.list = []
height, width = img.shape[:2]
object_list.imwidth = width
object_list.imheight = height
# get filtered contours
# cone_contours = get_filtered_contours(img, "CONE")
duck_contours = get_filtered_contours(img, "DUCK_COLOR")
all_contours = [duck_contours]
for i, contours in enumerate(all_contours):
for (cnt, box, ds, aspect_ratio, mean_color) in contours:
# plot box around contour
x, y, w, h = box
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img, terms[i], (x, y), font, 0.5, mean_color, 4)
cv2.rectangle(img, (x, y), (x + w, y + h), mean_color, 2)
r = Rect()
r.x = x
r.y = y
r.w = w
r.h = h
t = ObstacleType()
t.type = i
d = ObstacleImageDetection()
d.bounding_box = r
d.type = t
object_list.list.append(d)
# rospy.loginfo("duck_contours" + str(len(duck_contours)))
# rospy.loginfo("object_list" + str(len(object_list.list)))
return img, object_list