def get_ir_image(cam_handle):
logger = logging.getLogger(__name__)
frame = tof.Frame()
status = cam_handle.requestFrame(frame)
#logger.debug(status)
ir_image = np.array(frame.getData(tof.FrameDataType.IR), copy=True)
return ir_image
print("system.getAvailableFrameTypes()", status)
print(types)
status = camera1.initialize()
print("camera1.initialize()", status)
camDetails = tof.CameraDetails()
status = camera1.getDetails(camDetails)
print("system.getDetails()", status)
print("camera1 details:", "id:", camDetails.cameraId, "connection:",
camDetails.connection)
status = camera1.setFrameType(types[0])
print("camera1.setFrameType()", status)
status = camera1.setMode(modes[0])
print("camera1.setMode()", status)
frame = tof.Frame()
status = camera1.requestFrame(frame)
print("camera1.requestFrame()", status)
frameDetails = tof.FrameDetails()
status = frame.getDetails(frameDetails)
print("frame.getDetails()", status)
print("frame details:", "width:", frameDetails.width, "height:",
frameDetails.height, "type:", frameDetails.type)
image = np.array(frame.getData(tof.FrameDataType.Depth), copy=False)
print(image)
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))
