def _msg_cb(self, msg):
rects, count = self.non_max_suppression_handler(msg.rects, self.thre)
rects_msg = RectArray()
rects_msg.header = msg.header
rects_msg.rects = rects
self.pub_rects.publish(rects_msg)
count_msg = Int64()
count_msg.data = count
self.pub_count.publish(count_msg)
def _apply(self, img_msg):
bridge = cv_bridge.CvBridge()
img = bridge.imgmsg_to_cv2(img_msg, desired_encoding='bgr8')
rects = []
dlib.find_candidate_object_locations(img, rects, min_size=self.min_size)
ros_rect_array = RectArray()
ros_rect_array.header = img_msg.header
for d in rects:
if (d.right() - d.left()) * (d.bottom() - d.top()) > self.max_size:
continue
cv2.rectangle(img, (d.left(), d.top()), (d.right(), d.bottom()), (255, 0, 0), 3)
ros_rect_array.rects.append(Rect(x=d.left(), y=d.top(), width=d.right() - d.left(), height=d.bottom() - d.top()))
imgmsg = bridge.cv2_to_imgmsg(img, encoding='bgr8')
self.debug_pub_.publish(imgmsg)
self.pub_.publish(ros_rect_array)
def _apply(self, img_msg):
bridge = cv_bridge.CvBridge()
img_bgr = bridge.imgmsg_to_cv2(img_msg, desired_encoding='bgr8')
img_rgb = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB)
rects = []
dlib.find_candidate_object_locations(img_rgb, rects,
min_size=self.min_size)
ros_rect_array = RectArray()
ros_rect_array.header = img_msg.header
for d in rects:
if (d.right() - d.left()) * (d.bottom() - d.top()) > self.max_size:
continue
cv2.rectangle(img_bgr, (d.left(), d.top()), (d.right(), d.bottom()), (255, 0, 0), 3)
ros_rect_array.rects.append(Rect(x=d.left(), y=d.top(), width=d.right() - d.left(), height=d.bottom() - d.top()))
imgmsg = bridge.cv2_to_imgmsg(img_bgr, encoding='bgr8')
self.debug_pub_.publish(imgmsg)
self.pub_.publish(ros_rect_array)
def callback(self, imgmsg):
raw_image = None
self.image_width = imgmsg.width
self.image_height = imgmsg.height
try:
raw_image = self.bridge.imgmsg_to_cv2(imgmsg,
desired_encoding='bgr8')
except:
rospy.logerr('failed transform image')
return
dataset = ImageDataset(pkg_dir,
raw_image,
self.templates_dir,
thresh=self.thresh,
image_name=str(imgmsg.header.stamp))
scores, w_array, h_array, label_list = calculate_scores(
self.model, dataset)
boxes, indices = nms(scores, w_array, h_array, dataset.thresh,
label_list)
output_image = plot_results(dataset.image_raw,
boxes,
label_list,
indices,
show=False,
save_name=None)
labels_msg = LabelArray()
rects_msg = RectArray()
original_size_rects_msg = RectArray()
for i in range(len(indices)):
rect_msg = Rect()
label_msg = Label()
original_size_rect_msg = Rect()
box = boxes[i][None, :, :][0]
x, y, width, height = self.check_out_of_image(box)
rect_msg.x = x
rect_msg.y = y
rect_msg.width = width
rect_msg.height = height
original_size_rect_msg.x = x * 1 / self.resize_scale
original_size_rect_msg.y = y * 1 / self.resize_scale
original_size_rect_msg.width = width * 1 / self.resize_scale
original_size_rect_msg.height = height * 1 / self.resize_scale
# rect_msg.x = box[0][0]
# rect_msg.y = box[0][1]
# rect_msg.width = box[1][0] - box[0][0]
# rect_msg.height = box[1][1] - box[0][1]
label_msg.name = label_list[indices[i]]
rects_msg.rects.append(rect_msg)
labels_msg.labels.append(label_msg)
original_size_rects_msg.rects.append(original_size_rect_msg)
rects_msg.header = imgmsg.header
labels_msg.header = imgmsg.header
original_size_rects_msg.header = imgmsg.header
self.labels_pub.publish(labels_msg)
self.rects_pub.publish(rects_msg)
self.original_size_rects_pub.publish(original_size_rects_msg)
msg_viz = cv_bridge.CvBridge().cv2_to_imgmsg(output_image,
encoding='bgr8')
msg_viz.header = imgmsg.header
self.pub_viz.publish(msg_viz)