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
def run_example(remote):
cam_ip = ''
if remote is not None:
ip = ipaddress.ip_address(remote)
print('Running script for a camera connected over Ethernet at ip:', ip)
cam_ip = remote
system = tof.System()
status = system.initialize()
#Specify if you want to load firmware from lf files, or from EEPROM
from_software = True
if (from_software):
#Choose firmware path from here
firmware_path = "config/BM_Kit/Near/"
logger.info("Programming firmware from : " + firmware_path)
cam_handle = device.open_device2(system, cam_ip)
device.program_firmware2(cam_handle, firmware_path)
# The following parameters must be specified if firmware is loaded from software
sw_gain = 1
sw_offset = 0
else:
#Specify which mode to load from EEPROM 'near', 'medium', 'far'
mode = 'near'
cameras = []
if not cam_ip:
status = system.getCameraList(cameras)
logger.info("system.getCameraList()" + str(status))
else:
status = system.getCameraListAtIp(cameras, cam_ip)
logger.info("system.getCameraListAtIp()" + str(status))
cam_handle = cameras[0]
modes = []
status = cam_handle.getAvailableModes(modes)
logger.info("system.getAvailableModes()" + str(status))
logger.info(str(modes))
types = []
status = cam_handle.getAvailableFrameTypes(types)
logger.info("system.getAvailableFrameTypes()" + str(status))
logger.info(str(types))
status = cam_handle.initialize()
logger.info("cam_handle.initialize()" + str(status))
status = cam_handle.setFrameType(types[0])
logger.info("cam_handle.setFrameType()" + str(status))
logger.info(types[0])
status = cam_handle.setMode(mode)
logger.info("cam_handle.setMode()" + str(status))
frame = tof.Frame()
logger.info("Device Programmed")
i = 0
# Specify frames to capture to output averaged data
avg_vals = 1
values_depth = np.zeros(avg_vals)
values_ir = np.zeros(avg_vals)
while (True):
if (from_software):
# Get depth and ir frames
depth_image, ir_image = device.get_depth_ir_image(cam_handle)
# Apply gain and offset
depth_image = (depth_image * sw_gain) + sw_offset
else:
status = cam_handle.requestFrame(frame)
depth_image = np.array(frame.getData(tof.FrameDataType.Depth),
dtype="uint16",
copy=False)
ir_image = np.array(frame.getData(tof.FrameDataType.IR),
dtype="uint16",
copy=False)
depth_image_size = (int(depth_image.shape[0] / 2),
depth_image.shape[1])
depth_image_2 = np.resize(depth_image, depth_image_size)
depth_image_2 = cv2.flip(depth_image_2, 1)
depth_image_2 = np.uint8(depth_image_2)
color_depth = cv2.applyColorMap(depth_image_2, cv2.COLORMAP_RAINBOW)
#Draw rectangle at the center of depth image
cv2.rectangle(color_depth, (315, 235), (325, 245), (0, 0, 0), 2)
ir_image_2 = np.uint8(255 * (ir_image / 4095))
ir_image_2.resize((480, 640))
ir_image_2 = cv2.flip(ir_image_2, 1)
ir_image_2 = cv2.applyColorMap(ir_image_2, cv2.COLORMAP_BONE)
#Output images as .png
cv2.imwrite('ir.png', ir_image_2)
cv2.imwrite('depth.png', color_depth)
#Uncomment if running example on 96/Arrow board with HDMI to show stream data on monitor
#cv2.namedWindow("Depth", cv2.WINDOW_AUTOSIZE)
#cv2.imshow( "Depth", color_depth)
#cv2.imshow( "IR", ir_image_2)
#if cv2.waitKey(1) >= 0:
# break
# values_depth[i] = depth_image[240,320]
# values_ir[i] = ir_image[240,320]
# i = i + 1
# # Generates stats for middle pixel
# if i == avg_vals:
# Depth = np.average(values_depth)
# ir = np.average(values_ir)
# Std = np.std(values_depth)
# Noise = (Std/Depth) * 100
# print('Depth:' + str(Depth))
# print('STD:' + str(Std))
# print('N%:' + str(Noise))
# print('IR:' + str(ir))
# i = 0
print(get_TAL_values(cam_handle))
def run_find_pc(config_json, **kwargs):
logger = logging.getLogger(__name__)
pc_config_dict = load_config_dict(config_json)
log_dict['pc_config_dict'] = pc_config_dict
sweep_config_dict = load_config_dict(
pc_config_dict['firmware_config_json_path'])
firmware_path = sweep_config_dict['firmware_path']
mode = pc_config_dict['firmware_config_json_path'].split('/')[2]
multiply_factor = 2 if mode == "M3W" else 1
log_dict['mode'] = mode
log_dict['results'] = []
# Initialize tof class
system = tof.System()
ipString = ''
# 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)
# Open Repeat Number file and load PC
lf_path = os.path.join(sweep_config_dict['firmware_path'],
sweep_config_dict['repeat_num_filename'])
file = open(lf_path)
text = file.read()
pc_dict = create_code_dict(text)
target_ir = pc_config_dict['target_ir']
start_pc = pc_config_dict['start_pc']
max_pc = pc_config_dict['max_pc']
pc, pc_dict = get_target_pc(cam_handle, pc_dict, start_pc, target_ir,
max_pc, sweep_config_dict, multiply_factor)
t = time.time()
d = 0
while d < sweep_config_dict['warmup_time']:
d = time.time() - t
pc, pc_dict = get_target_pc(cam_handle, pc_dict, pc, target_ir, max_pc,
sweep_config_dict, multiply_factor)
with open(pc_config_dict['out_file'], 'w') as outfile:
json.dump(log_dict, outfile)
# Create new lf file
repeat_folder = 'r_lfs'
files = glob.glob(
os.path.join(sweep_config_dict['firmware_path'], repeat_folder, '9_*'))
new_filename = '9_RepeatNumAddrList_' + str(len(files)) + '.lf'
os.rename(
lf_path,
os.path.join(sweep_config_dict['firmware_path'], repeat_folder,
new_filename))
# Write to new pulse count to file
file = open(lf_path, 'w')
file.writelines('/*Pulsecount :' + str(pc) + '*/ \n')
for key in pc_dict.keys():
file.writelines(
tohex(key, 16, '04x') + ' ' + tohex(pc_dict[key], 16, '04x') +
'\n')
file.close()