rasberry pi 4的相机与opencv集成

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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")

[这些开源库无济于事：https://en.ids-imaging.com/techtipps-detail/en_techtip-embedded-vision-kit.htmlhttps://en.ids-imaging.com/store/customer/account/login/referer/aHR0cHM6Ly9lbi5pZHMtaW1hZ2luZy5jb20vcHJvZ3JhbW1pbmctZXhhbXBsZXMuaHRtbA ,,

答案

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
另一答案

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。

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