我正在运行openCV，以便在rasberry pi 4模型B上进行某些车辆检测。我购买了IDS相机：https://en.ids-imaging.com/download-ueye-emb-hardfloat.html但是将其集成到我的代码中被证明是太麻烦了，因为opencv.VideoCapture无法检测到任何设备，并且ueye python库无法即插即用，在线找到的任何示例代码都可以将其集成到opencv中，在我的Win PC上可以正常工作，但是会导致内存不足Pi上的泄漏和分段故障。
关于在rasberry pi 4上与opencv很好集成的相机的任何建议，而不必经历分配内存之类的麻烦？
添加集成尝试：
from pyueye import ueye
import numpy as np
import cv2
import sys
class Rect:
def __init__(self, x=0, y=0, width=0, height=0):
self.x = x
self.y = y
self.width = width
self.height = height
#---------------------------------------------------------------------------------------------------------------------------------------
class UeyeCamSetup():
#Variables
hCam = ueye.HIDS(0) #0: first available camera; 1-254: The camera with the specified camera ID
sInfo = ueye.SENSORINFO()
cInfo = ueye.CAMINFO()
pcImageMemory = ueye.c_mem_p()
MemID = ueye.int()
rectAOI = ueye.IS_RECT()
pitch = ueye.INT()
nBitsPerPixel = ueye.INT(24) #24: bits per pixel for color mode; take 8 bits per pixel for monochrome
channels = 3 #3: channels for color mode(RGB); take 1 channel for monochrome
m_nColorMode = ueye.INT() # Y8/RGB16/RGB24/REG32
bytes_per_pixel = int(nBitsPerPixel / 8)
nRet = None
width = None
height = None
#---------------------------------------------------------------------------------------------------------------------------------------
def startUeye(self):
# Starts the driver and establishes the connection to the camera
nRet = ueye.is_InitCamera(self.hCam, None)
if nRet != ueye.IS_SUCCESS:
print("is_InitCamera ERROR")
# Reads out the data hard-coded in the non-volatile camera memory and writes it to the data structure that cInfo points to
nRet = ueye.is_GetCameraInfo(self.hCam, self.cInfo)
if nRet != ueye.IS_SUCCESS:
print("is_GetCameraInfo ERROR")
# You can query additional information about the sensor type used in the camera
nRet = ueye.is_GetSensorInfo(self.hCam, self.sInfo)
if nRet != ueye.IS_SUCCESS:
print("is_GetSensorInfo ERROR")
nRet = ueye.is_ResetToDefault(self.hCam)
if nRet != ueye.IS_SUCCESS:
print("is_ResetToDefault ERROR")
# Set display mode to DIB
nRet = ueye.is_SetDisplayMode(self.hCam, ueye.IS_SET_DM_DIB)
# Set the right color mode
if int.from_bytes(self.sInfo.nColorMode.value, byteorder='big') == ueye.IS_COLORMODE_BAYER:
# setup the color depth to the current windows setting
ueye.is_GetColorDepth(self.hCam, self.nBitsPerPixel, self.m_nColorMode)
self.bytes_per_pixel = int(self.nBitsPerPixel / 8)
print("IS_COLORMODE_BAYER: ", )
print("\tm_nColorMode: \t\t", self.m_nColorMode)
print("\tnBitsPerPixel: \t\t", self.nBitsPerPixel)
print("\tbytes_per_pixel: \t", self.bytes_per_pixel)
print()
elif int.from_bytes(self.sInfo.nColorMode.value, byteorder='big') == ueye.IS_COLORMODE_CBYCRY:
# for color camera models use RGB32 mode
self.m_nColorMode = ueye.IS_CM_BGRA8_PACKED
self.nBitsPerPixel = ueye.INT(32)
self.bytes_per_pixel = int(self.nBitsPerPixel / 8)
print("IS_COLORMODE_CBYCRY: ", )
print("\tm_nColorMode: \t\t", self.m_nColorMode)
print("\tnBitsPerPixel: \t\t", self.nBitsPerPixel)
print("\tbytes_per_pixel: \t\t", self.bytes_per_pixel)
print()
elif int.from_bytes(self.sInfo.nColorMode.value, byteorder='big') == ueye.IS_COLORMODE_MONOCHROME:
# for color camera models use RGB32 mode
self.m_nColorMode = ueye.IS_CM_MONO8
self.nBitsPerPixel = ueye.INT(8)
self.bytes_per_pixel = int(self.nBitsPerPixel / 8)
print("IS_COLORMODE_MONOCHROME: ", )
print("\tm_nColorMode: \t\t", self.m_nColorMode)
print("\tnBitsPerPixel: \t\t", self.nBitsPerPixel)
print("\tbytes_per_pixel: \t\t", self.bytes_per_pixel)
print()
else:
# for monochrome camera models use Y8 mode
self.m_nColorMode = ueye.IS_CM_MONO8
self.nBitsPerPixel = ueye.INT(8)
self.bytes_per_pixel = int(self.nBitsPerPixel / 8)
print("else")
# Can be used to set the size and position of an "area of interest"(AOI) within an image
nRet = ueye.is_AOI(self.hCam, ueye.IS_AOI_IMAGE_GET_AOI, self.rectAOI, ueye.sizeof(self.rectAOI))
if nRet != ueye.IS_SUCCESS:
print("is_AOI ERROR")
self.width = self.rectAOI.s32Width
self.height = self.rectAOI.s32Height
# Prints out some information about the camera and the sensor
print("Camera model:\t\t", self.sInfo.strSensorName.decode('utf-8'))
print("Camera serial no.:\t", self.cInfo.SerNo.decode('utf-8'))
print("Maximum image width:\t", self.width)
print("Maximum image height:\t", self.height)
print()
#---------------------------------------------------------------------------------------------------------------------------------------
# Allocates an image memory for an image having its dimensions defined by width and height and its color depth defined by nBitsPerPixel
nRet = ueye.is_AllocImageMem(self.hCam, self.width, self.height, self.nBitsPerPixel, self.pcImageMemory, self.MemID)
if nRet != ueye.IS_SUCCESS:
print("is_AllocImageMem ERROR")
else:
# Makes the specified image memory the active memory
nRet = ueye.is_SetImageMem(self.hCam, self.pcImageMemory, self.MemID)
if nRet != ueye.IS_SUCCESS:
print("is_SetImageMem ERROR")
else:
# Set the desired color mode
nRet = ueye.is_SetColorMode(self.hCam, self.m_nColorMode)
# Activates the camera's live video mode (free run mode)
nRet = ueye.is_CaptureVideo(self.hCam, ueye.IS_DONT_WAIT)
if nRet != ueye.IS_SUCCESS:
print("is_CaptureVideo ERROR")
# Enables the queue mode for existing image memory sequences
# nRet = ueye.is_InquireImageMem(self.hCam, self.pcImageMemory, self.MemID, self.width, self.height, self.nBitsPerPixel, self.pitch)
# if nRet != ueye.IS_SUCCESS:
# print("is_InquireImageMem ERROR")
# else:
# print("Press ESC to leave the programm")
self.nRet = nRet
def readOpenCVImg(self):
if(self.nRet == ueye.IS_SUCCESS):
# In order to display the image in an OpenCV window we need to...
# ...extract the data of our image memory
array = ueye.get_data(self.pcImageMemory, self.width, self.height, self.nBitsPerPixel, self.pitch, copy=False)
# bytes_per_pixel = int(nBitsPerPixel / 8)
# ...reshape it in an numpy array...
frame = np.reshape(array,(self.height.value, self.width.value, self.bytes_per_pixel))
# ...resize the image by a half
return cv2.resize(frame,(0,0),fx=0.5, fy=0.5)
#---------------------------------------------------------------------------------------------------------------------------------------
def releaseCam(self):
# Releases an image memory that was allocated using is_AllocImageMem() and removes it from the driver management
ueye.is_FreeImageMem(self.hCam, self.pcImageMemory, self.MemID)
# Disables the hCam camera handle and releases the data structures and memory areas taken up by the uEye camera
ueye.is_ExitCamera(self.hCam)
print()
print("END")
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实际上我尝试过https://www.hackster.io/deligence-techn... hon-faf14f
这是我要与普通USB cam一起使用的程序的代码：
import argparse
import datetime
import imutils
import math
import cv2
import numpy as np
width = 800
textIn = 0
textOut = 0
def testIntersectionIn(x, y):
res = -450 * x + 400 * y + 157500
if((res >= -550) and (res < 550)):
print (str(res))
return True
return False
def testIntersectionOut(x, y):
res = -450 * x + 400 * y + 180000
if ((res >= -550) and (res <= 550)):
print (str(res))
return True
return False
camera = cv2.VideoCapture(0)
firstFrame = None
while True:
(grabbed, frame) = camera.read()
text = "Unoccupied"
if not grabbed:
break
frame = imutils.resize(frame, width=width)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (21, 21), 0)
if firstFrame is None:
firstFrame = gray
continue
frameDelta = cv2.absdiff(firstFrame, gray)
thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]
thresh = cv2.dilate(thresh, None, iterations=2)
_, cnts, _ = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
for c in cnts:
if cv2.contourArea(c) < 12000:
continue
(x, y, w, h) = cv2.boundingRect(c)
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.line(frame, (width / 2, 0), (width, 450), (250, 0, 1), 2) #blue line
cv2.line(frame, (width / 2 - 50, 0), (width - 50, 450), (0, 0, 255), 2)#red line
rectagleCenterPont = ((x + x + w) /2, (y + y + h) /2)
cv2.circle(frame, rectagleCenterPont, 1, (0, 0, 255), 5)
if(testIntersectionIn((x + x + w) / 2, (y + y + h) / 2)):
textIn += 1
if(testIntersectionOut((x + x + w) / 2, (y + y + h) / 2)):
textOut += 1
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cv2.putText(frame, "In: {}".format(str(textIn)), (10, 50),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
cv2.putText(frame, "Out: {}".format(str(textOut)), (10, 70),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
cv2.putText(frame, datetime.datetime.now().strftime("%A %d %B %Y %I:%M:%S%p"),
(10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)
cv2.imshow("Security Feed", frame)
camera.release()
cv2.destroyAllWindows()
这是仅使用picam传输视频的代码：
# import the necessary packages
from picamera.array import PiRGBArray
from picamera import PiCamera
import time
import cv2
# initialize the camera and grab a reference to the raw camera capture
camera = PiCamera()
camera.resolution = (640, 480)
camera.framerate = 32
rawCapture = PiRGBArray(camera, size=(640, 480))
# allow the camera to warmup
time.sleep(0.1)
# capture frames from the camera
for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):
# grab the raw NumPy array representing the image, then initialize the timestamp
# and occupied/unoccupied text
image = frame.array
# show the frame
cv2.imshow("Frame", image)
key = cv2.waitKey(1) & 0xFF
# clear the stream in preparation for the next frame
rawCapture.truncate(0)
# if the `q` key was pressed, break from the loop
if key == ord("q"):
break
摄像机板通过15方向带状电缆连接到Raspberry Pi。仅需要进行两个连接：带状电缆需要连接到相机PCB，并且需要连接到Raspberry Pi本身。您需要正确连接电缆，否则相机将无法工作。在摄像头PCB上，电缆的蓝色衬背应背对PCB，而在Raspberry Pi上，则应面向以太网连接（如果您使用的是A型，则以太网连接器应位于该位置）
在命令行上执行以下说明，以下载并安装最新的内核，GPU固件和应用程序。您需要互联网连接才能正常工作。
sudo apt update
sudo apt full-upgrade
现在，您需要使用首次设置Raspberry Pi时将使用的raspi-config程序来启用相机支持。
sudo raspi-config
使用光标键选择并打开接口选项，然后选择摄像头并按照提示启用摄像头。
退出raspi-config后，将要求重新启动。启用选项将确保在重新启动时通过相机驱动程序和调整运行正确的GPU固件，并且GPU内存拆分足以使相机获取足够的内存以正确运行。
要测试系统是否已安装并正常工作，请尝试以下命令：
raspistill -v -o test.jpg
显示器应显示来自摄像机的五秒钟预览，然后拍摄照片，并保存到文件test.jpg，同时显示各种信息性消息。