def main():
rospy.init_node('capsen_benchmark', anonymous=True)
basefolder = os.getenv('APCDATA_BASE') + '/bagfiles/vision_dataset/Bin0/'
pc_topic = '/realsense/depth_registered/points'
bin_num = 0
mode = 1 # 0 for kinect, 1 for realsense
item_names = get_immediate_subdirectories(basefolder)
pubTf = rospy.Publisher('tf', TFMessage, queue_size=10)
pubPointCloud = rospy.Publisher(pc_topic, PointCloud2, queue_size=10)
capsen.init()
for item_name in item_names:
object_folder = os.path.join(basefolder, item_name)
pose_types = get_immediate_subdirectories(object_folder)
for pose_type in pose_types:
posefolder = os.path.join(object_folder, pose_type)
bagFilenames = get_immediate_files(posefolder)
while True:
#for bagFilename in bagFilenames:
bagFilename = bagFilenames[0]
bagpath = os.path.join(posefolder, bagFilename)
bag = rosbag.Bag(bagpath)
#print bagpath
for topic, msg, t in bag.read_messages(topics=['/tf']):
if topic == '/tf':
rospy.sleep(0.003)
for i in range(len(msg.transforms)):
msg.transforms[i].header.stamp = rospy.Time.now()
pubTf.publish(msg)
def main():
rospy.init_node('capsen_benchmark', anonymous=True)
basefolder = os.getenv('APCDATA_BASE') + '/bagfiles/vision_dataset/Bin0/'
pc_topic = '/realsense/depth_registered/points'
bin_num = 0
mode = 1 # 0 for kinect, 1 for realsense
item_names = get_immediate_subdirectories(basefolder)
pubTf = rospy.Publisher('tf', TFMessage, queue_size=10)
pubPointCloud = rospy.Publisher(pc_topic, PointCloud2, queue_size=10)
capsen.init()
for item_name in item_names:
object_folder = os.path.join(basefolder, item_name)
pose_types = get_immediate_subdirectories(object_folder)
for pose_type in pose_types:
posefolder = os.path.join(object_folder, pose_type)
bagFilenames = get_immediate_files(posefolder)
while True:
#for bagFilename in bagFilenames:
bagFilename = bagFilenames[0]
bagpath = os.path.join(posefolder, bagFilename)
bag = rosbag.Bag(bagpath)
#print bagpath
for topic, msg, t in bag.read_messages(topics=['/tf']):
if topic == '/tf':
rospy.sleep(0.003)
for i in range(len(msg.transforms)):
msg.transforms[i].header.stamp = rospy.Time.now()
pubTf.publish(msg)
def main():
rospy.init_node('capsen_benchmark', anonymous=True)
basefolder = os.getenv('APCDATA_BASE') + '/bagfiles/vision_dataset/Bin0/'
outputfile = os.getenv('APCDATA_BASE') + '/bagfiles/vision_dataset/Bin0/result.json'
pc_topic = '/realsense/depth_registered/points'
bin_num = 0
mode = 1 # 0 for kinect, 1 for realsense
item_names = get_immediate_subdirectories(basefolder)
pubTf = rospy.Publisher('tf', TFMessage, queue_size=10)
pubPointCloud = rospy.Publisher(pc_topic, PointCloud2, queue_size=1)
capsen.init()
listener = tf.TransformListener()
rospy.sleep(0.1)
result = []
for item_name in item_names:
#os.system("echo '%s' > %s/capsen_vision/models/models.txt" % (item_name, os.getenv('APCDATA_BASE')) ) # hack
object_folder = os.path.join(basefolder, item_name)
pose_types = get_immediate_subdirectories(object_folder)
for pose_type in pose_types:
posefolder = os.path.join(object_folder, pose_type)
bagFilenames = get_immediate_files(posefolder)
for bagFilename in bagFilenames:
bagpath = os.path.join(posefolder, bagFilename)
bag = rosbag.Bag(bagpath)
print bagpath
cnt = 0
for topic, msg, t in bag.read_messages(topics=[pc_topic]):
for i in range(3):
msg.header.stamp = rospy.Time.now()
pubPointCloud.publish(msg)
rospy.sleep(0.1)
rospy.sleep(0.5)
pose = detectOneObject(item_name, [item_name], bin_num, mode)
if pose is not None:
print item_name, find_object_pose_type(item_name, pose), pose_type, bagFilename, cnt
result.append([item_name, pose, find_object_pose_type(item_name, pose), pose_type, bagFilename, cnt])
else:
print item_name, 'None', pose_type, bagFilename, cnt
result.append([item_name, None, None, pose_type, bagFilename, cnt])
cnt += 1
#raw_input('press enter to continue')
with open(outputfile, 'w') as outfile:
json.dump(result, outfile)
os.system("cp %s/capsen_vision/models/models_full.txt %s/capsen_vision/models/models.txt" % (os.getenv('APCDATA_BASE'), os.getenv('APCDATA_BASE'))) # hack
def main():
rospy.init_node('capsen_benchmark', anonymous=True)
basefolder = os.getenv('APCDATA_BASE') + '/bagfiles/vision_dataset/Bin0/'
outputfile = os.getenv(
'APCDATA_BASE') + '/bagfiles/vision_dataset/Bin0/result.json'
pc_topic = '/realsense/depth_registered/points'
bin_num = 0
mode = 1 # 0 for kinect, 1 for realsense
item_names = get_immediate_subdirectories(basefolder)
pubTf = rospy.Publisher('tf', TFMessage, queue_size=10)
pubPointCloud = rospy.Publisher(pc_topic, PointCloud2, queue_size=1)
capsen.init()
listener = tf.TransformListener()
rospy.sleep(0.1)
result = []
for item_name in item_names:
#os.system("echo '%s' > %s/capsen_vision/models/models.txt" % (item_name, os.getenv('APCDATA_BASE')) ) # hack
object_folder = os.path.join(basefolder, item_name)
pose_types = get_immediate_subdirectories(object_folder)
for pose_type in pose_types:
posefolder = os.path.join(object_folder, pose_type)
bagFilenames = get_immediate_files(posefolder)
for bagFilename in bagFilenames:
bagpath = os.path.join(posefolder, bagFilename)
bag = rosbag.Bag(bagpath)
print bagpath
cnt = 0
for topic, msg, t in bag.read_messages(topics=[pc_topic]):
for i in range(3):
msg.header.stamp = rospy.Time.now()
pubPointCloud.publish(msg)
rospy.sleep(0.1)
rospy.sleep(0.5)
pose = detectOneObject(item_name, [item_name], bin_num,
mode)
if pose is not None:
print item_name, find_object_pose_type(
item_name, pose), pose_type, bagFilename, cnt
result.append([
item_name, pose,
find_object_pose_type(item_name, pose), pose_type,
bagFilename, cnt
])
else:
print item_name, 'None', pose_type, bagFilename, cnt
result.append([
item_name, None, None, pose_type, bagFilename, cnt
])
cnt += 1
#raw_input('press enter to continue')
with open(outputfile, 'w') as outfile:
json.dump(result, outfile)
os.system(
"cp %s/capsen_vision/models/models_full.txt %s/capsen_vision/models/models.txt"
% (os.getenv('APCDATA_BASE'), os.getenv('APCDATA_BASE'))) # hack
def main():
rospy.init_node("capsen_benchmark", anonymous=True)
basefolder = os.getenv("APCDATA_BASE") + "/bagfiles/vision_dataset/Bin0_Kinect/"
outputfile = os.getenv("APCDATA_BASE") + "/bagfiles/vision_dataset/Bin0_Kinect/result.json"
pc_topics = ["/kinect2_1/depth_highres/points", "/kinect2_2/depth_highres/points"]
bin_num = 0
mode = 0 # 0 for kinect, 1 for realsense
item_names = get_immediate_subdirectories(basefolder)
pubTf = rospy.Publisher("tf", TFMessage, queue_size=10)
pubPointCloud = {}
pubPointCloud[pc_topics[0]] = rospy.Publisher(pc_topics[0], PointCloud2, queue_size=1)
pubPointCloud[pc_topics[1]] = rospy.Publisher(pc_topics[1], PointCloud2, queue_size=1)
capsen.init()
listener = tf.TransformListener()
rospy.sleep(0.1)
result = []
for item_name in item_names:
os.system("echo '%s' > /home/mcube/apcdata/capsen_vision/models/models.txt" % item_name) # hack
object_folder = os.path.join(basefolder, item_name)
pose_types = get_immediate_subdirectories(object_folder)
for pose_type in pose_types:
posefolder = os.path.join(object_folder, pose_type)
bagFilenames = get_immediate_files(posefolder)
for bagFilename in bagFilenames:
bagpath = os.path.join(posefolder, bagFilename)
bag = rosbag.Bag(bagpath)
print bagpath
cnt = 0
flags = {}
for topic, msg, t in bag.read_messages(topics=pc_topics):
for i in range(3):
msg.header.stamp = rospy.Time.now()
pubPointCloud[topic].publish(msg)
rospy.sleep(0.1)
rospy.sleep(0.5)
flags[topic] = True
if pc_topics[0] in flags and pc_topics[1] in flags:
pose = detectOneObject(item_name, [item_name], bin_num, mode)
if pose is not None:
print item_name, find_object_pose_type(item_name, pose), pose_type, bagFilename, cnt
result.append(
[item_name, pose, find_object_pose_type(item_name, pose), pose_type, bagFilename, cnt]
)
else:
print item_name, "None", pose_type, bagFilename, cnt
result.append([item_name, None, None, pose_type, bagFilename, cnt])
cnt += 1
# raw_input('press enter to continue')
with open(outputfile, "w") as outfile:
json.dump(result, outfile)
os.system(
"cp /home/mcube/apcdata/capsen_vision/models/models_full.txt /home/mcube/apcdata/capsen_vision/models/models.txt"
) # hack
