ToF depth¶
This is a sample code that showcases how to use the ToF sensor. The ToF node converts raw data from the ToF sensor into a depth map.
Demo¶
This demo was recorded using the OAK-D SR PoE, that’s why we selected CAM_A port on the ToF sensor.
Setup¶
Please run the install script to download all required dependencies. Please note that this script must be ran from git context, so you have to download the depthai-python repository first and then run the script
git clone https://github.com/luxonis/depthai-python.git
cd depthai-python/examples
python3 install_requirements.py
For additional information, please follow installation guide
Source code¶
Also available on GitHub
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | #!/usr/bin/env python3 import cv2 import depthai as dai import numpy as np pipeline = dai.Pipeline() cam_a = pipeline.create(dai.node.Camera) # We assume the ToF camera sensor is on port CAM_A cam_a.setBoardSocket(dai.CameraBoardSocket.CAM_A) tof = pipeline.create(dai.node.ToF) # Configure the ToF node tofConfig = tof.initialConfig.get() # tofConfig.depthParams.freqModUsed = dai.RawToFConfig.DepthParams.TypeFMod.MIN tofConfig.depthParams.freqModUsed = dai.RawToFConfig.DepthParams.TypeFMod.MAX tofConfig.depthParams.avgPhaseShuffle = False tofConfig.depthParams.minimumAmplitude = 3.0 tof.initialConfig.set(tofConfig) # Link the ToF sensor to the ToF node cam_a.raw.link(tof.input) xout = pipeline.create(dai.node.XLinkOut) xout.setStreamName("depth") tof.depth.link(xout.input) # Connect to device and start pipeline with dai.Device(pipeline) as device: print('Connected cameras:', device.getConnectedCameraFeatures()) q = device.getOutputQueue(name="depth") while True: imgFrame = q.get() # blocking call, will wait until a new data has arrived depth_map = imgFrame.getFrame() # Colorize the depth frame to jet colormap depth_downscaled = depth_map[::4] non_zero_depth = depth_downscaled[depth_downscaled != 0] # Remove invalid depth values if len(non_zero_depth) == 0: min_depth, max_depth = 0, 0 else: min_depth = np.percentile(non_zero_depth, 3) max_depth = np.percentile(non_zero_depth, 97) depth_colorized = np.interp(depth_map, (min_depth, max_depth), (0, 255)).astype(np.uint8) depth_colorized = cv2.applyColorMap(depth_colorized, cv2.COLORMAP_JET) cv2.imshow("Colorized depth", depth_colorized) if cv2.waitKey(1) == ord('q'): break |