OAK相机：自动或手动设置相机参数
硬件
使用硬件如下：
- 4✖️ov9782相机
- OAK-FFC-4P驱动板
硬件接线参考博主的一篇博客：OAK相机：多相机硬件同步拍摄
软件
博主使用的是Ubuntu18.04系统，首先配置所需的python环境：
1、下载SDK软件包：
bash
git clone https://gitee.com/oakchina/depthai.git2、安装依赖：
bash
python3 -m pip install -r depthai/requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple3、注意：在Linux平台并且第一次使用OAK需要配置udev规则
bash
echo 'SUBSYSTEM=="usb", ATTRS{idVendor}=="03e7", MODE="0666"' | sudo tee /etc/udev/rules.d/80-movidius.rules
sudo udevadm control --reload-rules && sudo udevadm trigger相关python API可参考官方文档：https://docs.luxonis.com/projects/api/en/latest/references/python/#
在此博主提供一个示例：四个相机通过硬件触发同步，使用ROS发布图像消息，并可以自动或手动设置相机参数，更多设置可参考官方文档的API加以修改，完整程序如下：
python
# -*- coding: utf-8 -*-
#!/usr/bin/env python3
import depthai as dai
import yaml
import cv2
assert cv2.__version__[0] == '4', 'The fisheye module requires opencv version >= 3.0.0'
import numpy as np
import glob
NAME_LIST = ['cama', 'camb', 'camc', 'camd']
FPS = 20
AUTOSET = True
def clamp(num, v0, v1):
return max(v0, min(num, v1))
class CameraArray:
def __init__(self,fps=20):
self.FPS = fps
self.RESOLUTION = dai.ColorCameraProperties.SensorResolution.THE_800_P
self.cam_list = ['cam_a', 'cam_b', 'cam_c', 'cam_d']
self.cam_socket_opts = {
'cam_a': dai.CameraBoardSocket.CAM_A,
'cam_b': dai.CameraBoardSocket.CAM_B,
'cam_c': dai.CameraBoardSocket.CAM_C,
'cam_d': dai.CameraBoardSocket.CAM_D,
}
self.pipeline = dai.Pipeline()
self.cam = {}
self.xout = {}
# color
self.controlIn = self.pipeline.create(dai.node.XLinkIn)
self.controlIn.setStreamName('control')
for camera_name in self.cam_list:
self.cam[camera_name] = self.pipeline.createColorCamera()
self.cam[camera_name].setResolution(self.RESOLUTION)
if camera_name == 'cam_a': # ref trigger
self.cam[camera_name].initialControl.setFrameSyncMode(dai.CameraControl.FrameSyncMode.OUTPUT)
else: # other trigger
self.cam[camera_name].initialControl.setFrameSyncMode(dai.CameraControl.FrameSyncMode.INPUT)
self.cam[camera_name].setBoardSocket(self.cam_socket_opts[camera_name])
self.xout[camera_name] = self.pipeline.createXLinkOut()
self.xout[camera_name].setStreamName(camera_name)
self.cam[camera_name].isp.link(self.xout[camera_name].input)
self.cam[camera_name].setFps(self.FPS)
self.config = dai.Device.Config()
self.config.board.gpio[6] = dai.BoardConfig.GPIO(dai.BoardConfig.GPIO.OUTPUT, dai.BoardConfig.GPIO.Level.HIGH)
self.device = dai.Device(self.config)
def start(self):
self.device.startPipeline(self.pipeline)
self.output_queue_dict = {}
for camera_name in self.cam_list:
self.output_queue_dict[camera_name] = self.device.getOutputQueue(name=camera_name, maxSize=1, blocking=False)
def read_data(self):
output_img = {}
output_ts = {}
for camera_name in self.cam_list:
output_data = self.output_queue_dict[camera_name].tryGet()
if output_data is not None:
timestamp = output_data.getTimestampDevice()
img = output_data.getCvFrame()
# img = cv2.rotate(img, cv2.ROTATE_180)
output_img[camera_name] = img
output_ts[camera_name] = timestamp.total_seconds()
# print(camera_name, timestamp, timestamp.microseconds, img.shape)
else:
# print(camera_name, 'No ouput')
output_img[camera_name] = None
output_ts[camera_name] = None
return output_img, output_ts
if __name__ == '__main__':
import rospy
from sensor_msgs.msg import Image
from std_msgs.msg import Header
class CvBridge():
def __init__(self):
self.numpy_type_to_cvtype = {'uint8': '8U', 'int8': '8S', 'uint16': '16U',
'int16': '16S', 'int32': '32S', 'float32': '32F',
'float64': '64F'}
self.numpy_type_to_cvtype.update(dict((v, k) for (k, v) in self.numpy_type_to_cvtype.items()))
def dtype_with_channels_to_cvtype2(self, dtype, n_channels):
return '%sC%d' % (self.numpy_type_to_cvtype[dtype.name], n_channels)
def cv2_to_imgmsg(self, cvim, encoding = "passthrough"):
img_msg = Image()
img_msg.height = cvim.shape[0]
img_msg.width = cvim.shape[1]
if len(cvim.shape) < 3:
cv_type = self.dtype_with_channels_to_cvtype2(cvim.dtype, 1)
else:
cv_type = self.dtype_with_channels_to_cvtype2(cvim.dtype, cvim.shape[2])
if encoding == "passthrough":
img_msg.encoding = cv_type
else:
img_msg.encoding = encoding
if cvim.dtype.byteorder == '>':
img_msg.is_bigendian = True
img_msg.data = cvim.tobytes()
img_msg.step = len(img_msg.data) // img_msg.height
return img_msg
bridge = CvBridge()
img_pub_dict = {}
rospy.init_node('camera_array', anonymous=True)
rate = rospy.Rate(20)
for camera_name in ['cam_a', 'cam_b', 'cam_c', 'cam_d']:
img_pub_dict[camera_name] = rospy.Publisher('/img/'+str(camera_name), Image, queue_size=0)
img_cnt_dict = {
'cam_a':0, 'cam_b':0, 'cam_c':0, 'cam_d':0
}
camera_array = CameraArray(FPS)
camera_array.start()
controlQueue = camera_array.device.getInputQueue(camera_array.controlIn.getStreamName())
if AUTOSET:
ctrl = dai.CameraControl()
ctrl.setAutoExposureEnable()
ctrl.setAutoWhiteBalanceMode(dai.CameraControl.AutoWhiteBalanceMode.AUTO)
controlQueue.send(ctrl)
else:
# Defaults and limits for manual focus/exposure controls
expTime = 10000
expMin = 1
expMax = 33000
sensIso = 100
sensMin = 100
sensMax = 1600
wbManual = 3500
expTime = clamp(expTime, expMin, expMax)
sensIso = clamp(sensIso, sensMin, sensMax)
print("Setting manual exposure, time:", expTime, "iso:", sensIso)
ctrl = dai.CameraControl()
ctrl.setManualExposure(expTime, sensIso)
ctrl.setManualWhiteBalance(wbManual)
controlQueue.send(ctrl)
first_time_cam = None
first_time_local = None
while not rospy.is_shutdown():
output_img, output_ts = camera_array.read_data()
if first_time_cam is None and output_ts['cam_a'] is not None:
first_time_cam = output_ts['cam_a']
first_time_local = rospy.Time.now().to_sec()
for key in output_img.keys():
if output_img[key] is None:
continue
frame = output_img[key]
# convert
img = bridge.cv2_to_imgmsg(undistorted_img, encoding="bgr8")
img.header = Header()
if first_time_cam is not None:
ts = output_ts[key] - first_time_cam + first_time_local
img.header.stamp = rospy.Time.from_sec(ts)
else:
img.header.stamp = rospy.Time.now()
img_pub_dict[key].publish(img)
rate.sleep()将程序拷贝到本地，运行程序python camera.py；输入rostopic list，查看话题名；打开Rviz查看图像输出。