def run_all_calibration(sweep_config_json, **kwargs):
'''
A Python based command line utility to run calibration for ADI TOF modules
SWEEP_CONFIG_JSON: Specify the default sweep config json file. The default options can be overriden by explictly specifying the options on the command line
'''
sweep_config_dict = {}
if (sweep_config_json is not None):
with open(sweep_config_json) as f:
sweep_config_dict = json.load(f)
for key, value in kwargs.items():
if value is not None:
sweep_config_dict[key] = kwargs[key]
if key in sweep_config_dict:
if sweep_config_dict[key] is None:
print(
'Need to specify %s either as a command line option or in the sweep config json file'
)
raise SystemExit
if sweep_config_dict['unique_id'] == None:
unique_id = generate_unique_id()
sweep_config_dict['unique_id'] = unique_id
sweep_config_dict['unique_id_list'] = split_unique_id(
sweep_config_dict['unique_id'], 4)
ipString = ''
if 'remote' in sweep_config_dict:
ip = ipaddress.ip_address(sweep_config_dict['remote'])
print('Running script for a camera connected over Ethernet at ip:', ip)
ipString = sweep_config_dict['remote']
#Initialize tof class
system = tof.System()
status = system.initialize()
logger.info("System Initialize: " + str(status))
# Get Camera and program firmware
cam_handle = device.open_device2(system, ipString)
firmware_path = sweep_config_dict['firmware_path']
device.program_firmware2(cam_handle, firmware_path)
logger.info("Running Calibration")
#Initialize Dataframes
depth_stats_calibrated_df = pd.DataFrame([], columns=['NO DATA'])
depth_stats_df = pd.DataFrame([], columns=['NO DATA'])
linear_offset_df = pd.DataFrame([], columns=['NO DATA'])
metrics_df = pd.DataFrame([], columns=['NO DATA'])
# If using rail create handle and store handle in cfg
rail_handle = None
if (sweep_config_dict['calib_type'] == 'Rail'
or sweep_config_dict['verification_type'] == 'Rail'):
rail_handle = calib.initialize_rail(sweep_config_dict)
latest, archive = save.make_results_dir(sweep_config_dict['results_path'],
sweep_config_dict['unique_id'],
mode=sweep_config_dict['mode'])
t = time.time()
d = 0
while d < sweep_config_dict['warmup_time']:
d = time.time() - t
if sweep_config_dict['calibrate']:
if sweep_config_dict['calib_type'] == 'Sweep':
linear_offset_df, depth_stats_df = calib.run_sweep_calibration(
cam_handle=cam_handle,
cfg=sweep_config_dict,
firmware_path=firmware_path)
elif sweep_config_dict['calib_type'] == 'Rail':
logger.info("Running Rail Calibration")
# Run Rail calibration and store lf files
linear_offset_df, depth_stats_df = calib.run_rail_calibration(
cam_handle=cam_handle,
rail_handle=rail_handle,
cfg=sweep_config_dict,
firmware_path=firmware_path)
save.save_lf_files(latest, archive, firmware_path)
write_lf.write_linear_offset_to_lf2(firmware_path,
os.path.join(latest, 'lf_files'),
sweep_config_dict,
linear_offset_df)
depth_stats_calibrated_df = pd.DataFrame()
if sweep_config_dict['verify_sweep']:
if sweep_config_dict['verification_type'] == 'Sweep':
logger.info("Verifying Sweep")
_, depth_stats_calibrated_df = calib.verify_sweep(
cam_handle, sweep_config_dict,
os.path.join(latest, 'lf_files'))
elif sweep_config_dict['verification_type'] == 'Rail':
logger.info("Verifying Sweeap")
device.program_firmware2(cam_handle,
os.path.join(latest, 'lf_files'))
#_, depth_stats_calibrated_df = calib.rail_verify(cam_handle, rail_handle, sweep_config_dict, os.path.join(latest, 'lf_files'))
cfg = sweep_config_dict
frame_count = cfg['frame_count']
window = {}
window['X'] = cfg['window_x']
window['Y'] = cfg['window_y']
frame = {}
frame['height'] = cfg['frame_height']
frame['width'] = cfg['frame_width']
raw_frame = {}
raw_frame['height'] = cfg['raw_frame_height']
raw_frame['width'] = cfg['raw_frame_width']
repeat_num_file = os.path.join(firmware_path,
cfg['repeat_num_filename'])
hpt_data_file = os.path.join(firmware_path,
cfg['hpt_data_filename'])
data_file = os.path.join(firmware_path, cfg['data_filename'])
seq_file = os.path.join(firmware_path, cfg['seq_info_filename'])
min_dist = cfg['rail_min_dist']
max_dist = cfg['rail_max_dist']
dist_step = cfg['rail_dist_step']
depth_conv_gain = cfg['depth_conv_gain']
sw_gain = cfg['sw_gain']
sw_offset = cfg['sw_offset']
depth_stats_calibrated_df = sc.rail_stats(
min_dist, max_dist, dist_step, raw_frame, frame, frame_count,
window, sw_gain, sw_offset, rail_handle, cam_handle)
logger.info("Calculating Metrics")
metrics_df = pd.DataFrame()
#if sweep_config_dict['verify_sweep'] and sweep_config_dict['calculate_metrics']:
# metrics_df = metcalc.calculate_metrics(depth_stats_df, depth_stats_calibrated_df)
logger.info("writing to calibration json files")
cal_json = os.path.join(firmware_path, 'linear_cal.json')
output_cal_dict = write_to_cal_json(cal_json, sweep_config_dict)
save.save_results(latest, archive, depth_stats_df,
depth_stats_calibrated_df, linear_offset_df,
sweep_config_dict, firmware_path, metrics_df,
output_cal_dict)
camera_results_path = save.get_results_path(sweep_config_json,
sweep_config_dict['unique_id'])
logger.info('camera results path %s', camera_results_path)
return linear_offset_df
elif station == 'warm1':
logger.info("warming up for far mode")
sweep_config_json = os.path.join(
'config/BM_Kit/Far/sweep_config_far.json')
warmup(sweep_config_json, dev_handle, 150)
elif station == 'far':
msg = "\nSelected: FAR\n"
sweep_config_json = os.path.join(
'config/BM_Kit/Far/sweep_config_far.json')
print(msg)
lin_offset_df, dev, cfg = run_all_calibration(
sweep_config_json, dev_handle, unique_id)
elif station == 'save':
sweep_config_json = os.path.join(
'config/BM_Kit/Far/sweep_config_far.json')
camera_results_path = save.get_results_path(
sweep_config_json, unique_id)
logger.info('camera results path %s', camera_results_path)
write_verify_eeprom(camera_results_path, dev_handle)
publish.push_to_host(camera_results_path)
logger.info("Results written to host: Camera Unique ID: %s",
unique_id)
else:
logger.error("UNIQUE ID INPUT REQUIRED FIRST")
if station == 'exit':
logger.info("Results written to host: Camera Unique ID: %s",
unique_id)
break
else:
print("Unsupported option... Aborting...\n")