Namespaces |
namespace | random_forest_client_sample |
Variables |
int | random_forest_client_sample.answer = 1 |
tuple | random_forest_client_sample.ax = fig.add_subplot(1, 1, 1) |
tuple | random_forest_client_sample.br = cv_bridge.CvBridge() |
tuple | random_forest_client_sample.circle = patches.Circle(xy=(0, 0), radius=1.0, fill=False, ec='g') |
string | random_forest_client_sample.ENDC = '\033[0m' |
string | random_forest_client_sample.FAIL = '\033[91m' |
tuple | random_forest_client_sample.fig = plt.figure() |
string | random_forest_client_sample.HEADER = '\033[95m' |
tuple | random_forest_client_sample.img = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8) |
tuple | random_forest_client_sample.img_msg = br.cv2_to_imgmsg(img, 'rgb8') |
string | random_forest_client_sample.OKBLUE = '\033[94m' |
string | random_forest_client_sample.OKGREEN = '\033[92m' |
list | random_forest_client_sample.old_targets_fail = [] |
tuple | random_forest_client_sample.old_targets_fail_nparr = np.array(old_targets_fail) |
list | random_forest_client_sample.old_targets_ok = [] |
tuple | random_forest_client_sample.old_targets_ok_nparr = np.array(old_targets_ok) |
tuple | random_forest_client_sample.predict_data = rospy.ServiceProxy('predict', ClassifyData) |
tuple | random_forest_client_sample.pub_img = rospy.Publisher('~output/debug_image', Image, queue_size=1) |
tuple | random_forest_client_sample.req = ClassifyDataRequest() |
tuple | random_forest_client_sample.req_point = ClassDataPoint() |
tuple | random_forest_client_sample.response = predict_data(req) |
tuple | random_forest_client_sample.succeed = int(float(response.classifications[0])) |
list | random_forest_client_sample.target = [random.random(), random.random()] |
string | random_forest_client_sample.WARNING = '\033[93m' |