def req_channel_type():
hfl_chnl_proto_obj.required_devicesData = True
payload = hfl_chnl_proto_obj.SerializeToString()
# print "payload :: ", payload
hfl_publ_obj.send(payload)
ecal.finalize()
def req_image_data():
hfl_chnl_proto_obj.isReady = True
payload = hfl_chnl_proto_obj.SerializeToString()
# print "payload :: ", payload
hfl_publ_obj.send(payload)
ecal.finalize()
def req_timestamp():
dvc_data_proto_obj = common_pb2.DevicesDataRequest()
dvc_data_proto_obj.requiredDevicesData = True
payload = dvc_data_proto_obj.SerializeToString()
# print "payload :: ", payload
tmstamp_publ_obj.send(payload)
ecal.finalize()
def req_image_data():
hfl_req_proto_obj.required_timestamp = 1524659296562401
hfl_req_proto_obj.request_channel_name = 'svu32x_rear'
hfl_req_proto_obj.request_device_name = 'svu32'
payload = hfl_req_proto_obj.SerializeToString()
# print "payload :: ", payload
hfl_publ_obj.send(payload)
ecal.finalize()
def request_hfl_data():
# while ecal.ok():
# hfl_req_proto_obj.required_timestamp = 1504816617728550
hfl_req_proto_obj.image_index = 8 #1504816617788522
# hfl_req_proto_obj.hfl_file_name = "D:\\Work\\2018\\code\\LT5G\\HDF5_reader\\2017.09.07_at_20.37.57_camera-mi_1449.h5"
hfl_publ_obj.send(hfl_req_proto_obj.SerializeToString())
ecal.finalize()
def req_pcl_points():
pcl_data_proto_obj = common_pb2.DataRequest()
pcl_data_proto_obj.requiredTimestamp = 1521225338975243 #1521225351544589
pcl_data_proto_obj.requestDeviceName = "HFL"
pcl_data_proto_obj.requestChannelName = "Valodyne"
pcl_data_proto_obj.uniqueId = 1
payload = pcl_data_proto_obj.SerializeToString()
# print "payload :: ", payload
pcl_publ_obj.send(payload)
ecal.finalize()
r = results[0]
ed_time = datetime.now()
duration = ed_time - st_time
print("detection done in ... ", duration)
# If visualization flag is set to True in topics.json file it would pop an
# image with masks, object classes
if vis_flag:
show_detected_img(re_img_np_ary, r['rois'], r['class_ids'],
r['masks'])
# Arrange the detected output in a dictionary
# key: tuple having co-ordinates of BBox
# value: tuple, 1st value is class id, 2nd value is a mask of numpy array
rois_tupl_conv_lst = [tuple(ech_roi) for ech_roi in r['rois'].tolist()]
N = r['rois'].shape[0]
# print("N :: ", N)
mask_obj_lst = []
for i in range(N):
mask = r['masks'][:, :, i]
# print("mask >> ", type(mask))
mask_obj_lst.append(mask)
# detected_dict = dict(zip(rois_tupl_conv_lst, r['class_ids'].tolist()))
clsid_mask_tupl = zip(r['class_ids'].tolist(), mask_obj_lst)
detected_dict = dict(zip(rois_tupl_conv_lst, clsid_mask_tupl))
# Publish the class name, bounding box coordinates and the mask numpy array
# over prototobuf layer
publish_rois(detected_dict)
print("published response", datetime.now())
ecal.finalize()