00001
00002
00003 import sys
00004
00005 import cv2
00006 import matplotlib
00007 matplotlib.use('Agg')
00008 import matplotlib.cm
00009 import numpy as np
00010 import scipy.ndimage
00011
00012 import cv_bridge
00013 import dynamic_reconfigure.server
00014 from jsk_recognition_utils import bounding_rect_of_mask
00015 from jsk_recognition_utils import get_tile_image
00016 from jsk_recognition_utils.color import labelcolormap
00017 from jsk_topic_tools import ConnectionBasedTransport
00018 from jsk_topic_tools import warn_no_remap
00019 import message_filters
00020 import rospy
00021 from sensor_msgs.msg import Image
00022
00023 from jsk_perception.cfg import LabelImageDecomposerConfig
00024
00025
00026 def get_text_color(color):
00027 if color[0] * 0.299 + color[1] * 0.587 + color[2] * 0.114 > 170:
00028 return (0, 0, 0)
00029 return (255, 255, 255)
00030
00031
00032 def label2rgb(lbl, img=None, label_names=None, alpha=0.3, bg_label=0):
00033 if label_names is None:
00034 n_labels = lbl.max() + 1
00035 else:
00036 n_labels = len(label_names)
00037 cmap = labelcolormap(256)
00038 cmap = (cmap * 255).astype(np.uint8)
00039 bg_color, cmap = cmap[0], cmap[1:]
00040
00041 lbl_viz = np.zeros((lbl.shape[0], lbl.shape[1], 3), dtype=np.uint8)
00042 fg_mask = lbl != bg_label
00043 lbl_viz[fg_mask] = cmap[lbl[fg_mask] % 256]
00044 lbl_viz[~fg_mask] = bg_color
00045
00046 if img is not None:
00047 if img.ndim == 3:
00048 img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
00049 else:
00050 assert img.ndim == 2
00051 img_gray = img
00052 img_gray = cv2.cvtColor(img_gray, cv2.COLOR_GRAY2RGB)
00053 lbl_viz = alpha * lbl_viz + (1 - alpha) * img_gray
00054 lbl_viz = lbl_viz.astype(np.uint8)
00055
00056 if label_names is None:
00057 return lbl_viz
00058
00059 np.random.seed(1234)
00060 labels = np.unique(lbl)
00061 labels = labels[labels != 0]
00062 for label in labels:
00063 mask = lbl == label
00064 mask = (mask * 255).astype(np.uint8)
00065 y, x = scipy.ndimage.center_of_mass(mask)
00066 y, x = map(int, [y, x])
00067
00068 if lbl[y, x] != label:
00069 Y, X = np.where(mask)
00070 point_index = np.random.randint(0, len(Y))
00071 y, x = Y[point_index], X[point_index]
00072
00073 text = label_names[label]
00074 font_face = cv2.FONT_HERSHEY_SIMPLEX
00075 font_scale = 0.7
00076 thickness = 2
00077 text_size, baseline = cv2.getTextSize(
00078 text, font_face, font_scale, thickness)
00079
00080 color = get_text_color(lbl_viz[y, x])
00081 cv2.putText(lbl_viz, text,
00082 (x - text_size[0] // 2, y),
00083 font_face, font_scale, color, thickness)
00084 return lbl_viz
00085
00086
00087 class LabelImageDecomposer(ConnectionBasedTransport):
00088
00089 def __init__(self):
00090 super(LabelImageDecomposer, self).__init__()
00091
00092 self._srv_dynparam = dynamic_reconfigure.server.Server(
00093 LabelImageDecomposerConfig, self._config_callback)
00094
00095 self.pub_img = self.advertise('~output', Image, queue_size=5)
00096 self.pub_label_viz = self.advertise('~output/label_viz', Image,
00097 queue_size=5)
00098 self._bg_label = rospy.get_param('~bg_label', 0)
00099 self._only_label = rospy.get_param('~only_label', False)
00100 self._label_names = rospy.get_param('~label_names', None)
00101
00102 self._publish_mask = rospy.get_param('~publish_mask', False)
00103 if self._publish_mask:
00104 self.pub_fg_mask = self.advertise('~output/fg_mask', Image,
00105 queue_size=5)
00106 self.pub_bg_mask = self.advertise('~output/bg_mask', Image,
00107 queue_size=5)
00108
00109 self._publish_tile = rospy.get_param('~publish_tile', False)
00110 rospy.loginfo('~publish_tile: {}'.format(self._publish_tile))
00111 if self._only_label and self._publish_tile:
00112 rospy.logerr('Can not publish tile image when ~only_label is true,'
00113 ' so forcely set ~publish_tile to false.')
00114 self._publish_tile = False
00115 if self._publish_tile:
00116 self.pub_tile = self.advertise('~output/tile', Image, queue_size=5)
00117
00118 def _config_callback(self, config, level):
00119 self._alpha = config.alpha
00120 return config
00121
00122 def subscribe(self):
00123 self.sub_label = message_filters.Subscriber('~input/label', Image)
00124 if self._only_label:
00125 self.sub_label.registerCallback(self._apply)
00126 return
00127 self.sub_img = message_filters.Subscriber('~input', Image)
00128 warn_no_remap('~input', '~input/label')
00129 use_async = rospy.get_param('~approximate_sync', False)
00130 queue_size = rospy.get_param('~queue_size', 10)
00131 rospy.loginfo('~approximate_sync: {}, queue_size: {}'
00132 .format(use_async, queue_size))
00133 if use_async:
00134 slop = rospy.get_param('~slop', 0.1)
00135 rospy.loginfo('~slop: {}'.format(slop))
00136 async = message_filters.ApproximateTimeSynchronizer(
00137 [self.sub_label, self.sub_img],
00138 queue_size=queue_size, slop=slop)
00139 async.registerCallback(self._apply)
00140 if self._publish_tile:
00141 async.registerCallback(self._apply_tile)
00142 else:
00143 sync = message_filters.TimeSynchronizer(
00144 [self.sub_label, self.sub_img], queue_size=queue_size)
00145 sync.registerCallback(self._apply)
00146 if self._publish_tile:
00147 sync.registerCallback(self._apply_tile)
00148
00149 def unsubscribe(self):
00150 self.sub_img.sub.unregister()
00151 self.sub_label.sub.unregister()
00152
00153 def _apply(self, label_msg, img_msg=None):
00154 bridge = cv_bridge.CvBridge()
00155 label_img = bridge.imgmsg_to_cv2(label_msg)
00156 if img_msg:
00157 img = bridge.imgmsg_to_cv2(img_msg)
00158
00159 applied = img.copy()
00160 applied[label_img == self._bg_label] = 0
00161 applied_msg = bridge.cv2_to_imgmsg(applied, encoding=img_msg.encoding)
00162 applied_msg.header = img_msg.header
00163 self.pub_img.publish(applied_msg)
00164
00165 if img_msg.encoding in {'16UC1', '32SC1'}:
00166
00167 min_value, max_value = img.min(), img.max()
00168 img = (img - min_value) / (max_value - min_value) * 255
00169 img = img.astype(np.uint8)
00170 img = cv2.cvtColor(img, cv2.COLOR_GRAY2RGB)
00171 else:
00172 img = None
00173
00174 label_viz = label2rgb(label_img, img, label_names=self._label_names,
00175 alpha=self._alpha, bg_label=self._bg_label)
00176 label_viz_msg = bridge.cv2_to_imgmsg(label_viz, encoding='rgb8')
00177 label_viz_msg.header = label_msg.header
00178 self.pub_label_viz.publish(label_viz_msg)
00179
00180
00181 if self._publish_mask:
00182 bg_mask = (label_img == 0)
00183 fg_mask = ~bg_mask
00184 bg_mask = (bg_mask * 255).astype(np.uint8)
00185 fg_mask = (fg_mask * 255).astype(np.uint8)
00186 fg_mask_msg = bridge.cv2_to_imgmsg(fg_mask, encoding='mono8')
00187 fg_mask_msg.header = label_msg.header
00188 bg_mask_msg = bridge.cv2_to_imgmsg(bg_mask, encoding='mono8')
00189 bg_mask_msg.header = label_msg.header
00190 self.pub_fg_mask.publish(fg_mask_msg)
00191 self.pub_bg_mask.publish(bg_mask_msg)
00192
00193 def _apply_tile(self, label_msg, img_msg):
00194 bridge = cv_bridge.CvBridge()
00195 img = bridge.imgmsg_to_cv2(img_msg)
00196 label_img = bridge.imgmsg_to_cv2(label_msg)
00197
00198 imgs = []
00199 labels = np.unique(label_img)
00200 for label in labels:
00201 if label == 0:
00202
00203
00204 continue
00205 img_tmp = img.copy()
00206 mask = label_img == label
00207 img_tmp[~mask] = 0
00208 img_tmp = bounding_rect_of_mask(img_tmp, mask)
00209 imgs.append(img_tmp)
00210 tile_img = get_tile_image(imgs)
00211 tile_msg = bridge.cv2_to_imgmsg(tile_img, encoding='bgr8')
00212 tile_msg.header = img_msg.header
00213 self.pub_tile.publish(tile_msg)
00214
00215
00216 if __name__ == '__main__':
00217 rospy.init_node('label_image_decomposer')
00218 label_image_decomposer = LabelImageDecomposer()
00219 rospy.spin()