VideoCapture.read() 返回过去的图像

Question

我在Raspberry pi 上运行python3.6 和openCV（操作系统为Raspbian）

代码大致结构如下。

1. image 以时间间隔（3~5 分钟）捕获。

2. 捕获的image 在函数中处理并返回测量值（精度类型）

3. 迭代 1.~2。直到end_check() 返回True

问题是最近拍摄的image 已过期。看起来它是在大约 10 分钟前拍摄的。最近拍摄的所有图像都迟到了。但是开头拍摄的images 似乎是定时的。并且正确输入的所有.jpg文件中记录的时间 +看起来这个问题是在一个多小时后发生的。 （20~22 次迭代）

Images 在cv2 包中被cam0.read() 捕获。以下是代码的主要部分。上传完整代码很长。有人要求，我会更新。

def run(interval,model_list):
    cam0 = cv2.VideoCapture(0)  #Only cam0 is used. cam2 is just to record.
    camdir = "/home/pi/capstone/cam0/"
    cam2 = cv2.VideoCapture(1)
    cam2dir = "/home/pi/capstone/cam2/"
    runNo = 0
    acc_list = list()
    error_list = list()
    end = False
    while(end == False):
        print(runNo,"th run")

        img_name = "%s.jpg" %runNo
        frame, res = cam0.read()   #`res` is the image which will be processed
        cv2.imwrite(os.path.join(camdir,img_name),res)
        _ , cam2pic = cam2.read()
        cv2.imwrite(os.path.join(cam2dir,img_name),cam2pic)
        try:
            temp = Real(res)
            mat = temp.match(model_list)
            acc_list.append([mat,runNo])
            print("Accuracy=", mat)
        except ValueError:
            acc_list.append(["ValueError",runNo])
            error_list.append(["ValueError",runNo])
        except AttributeError:
            acc_list.append(["AttributeError", runNo])
            error_list.append(["AttributeError",runNo])
        except SmallObjectError:
            acc_list.append(["SmallObjectError", runNo])
            error_list.append(["SmallObjectError",runNo])
        runNo = runNo+1
        endNo = 40
        if(runNo/2 > endNo):
            end_check(res, end)
        elif(runNo > endNo):
            end = True
        sleep(interval*60)

    with open("acc_list.txt", "w") as output: #records for tracking errors
        output.write(str(acc_list))
    with open("err_list.txt", "w") as output:
        output.write(str(error_list))
    cam0.release()
    cam2.release()

run(3.5,model_list)

(+) 一些新发现的东西和猜测

• 随着代码的运行，images 的时间差距越来越大
• 代码终于显示OpenCV Error
• 看起来有点像 Video signal 存储在 RAM 中的 R-pi 和 .read() 返回过时的 image 在 RAM
• 将Video signal 存储在RAM 中引发资源问题

下面是OpenCV Error

OpenCV Error: Assertion failed (dsize.area() > 0 || (inv_scale_x > 0 && inv_scale_y > 0)) in resize, file /home/pi/opencv/opencv-3.4.0/modules/imgproc/src/resize.cpp, line 4045
Traceback (most recent call last):
  File "runpi.py", line 264, in <module>
    run(3.5,model_list)
  File "runpi.py", line 234, in run
    mat = temp.match(model_list)
  File "runpi.py", line 184, in match
    self.__resize(model.get_m_inform())
  File "runpi.py", line 147, in __resize
    self.mask = cv2.resize(self.mask, None, fx=reratio, fy=reratio, interpolation = inter_method)
cv2.error: /home/pi/opencv/opencv-3.4.0/modules/imgproc/src/resize.cpp:4045: error: (-215) dsize.area() > 0 || (inv_scale_x > 0 && inv_scale_y > 0) in function resize

(+) 部分代码引发错误

这是__.resize() 方法。当我手动处理OpenCV Error 发生的image 时，即使OpenCV Error 指出image 的大小很重要，它也能正常工作。所以我认为这与image 本身或size 从md_inf() 获得无关。无论如何，这是代码。

def __resize(self, md_inf):       
    #md_inf = [219, 122, 132, 171, 262] <-sample
    reratio = md_inf[0]/self.y
    if(reratio>1):
        inter_method = cv2.INTER_LINEAR
    else:
        inter_method = cv2.INTER_AREA

    ###below is line 147###
    self.mask = cv2.resize(self.mask, None, fx=reratio, fy=reratio, interpolation = inter_method)
    temp = np.zeros((md_inf[3], md_inf[4]), np.uint8)
    m_cx, m_cy = md_inf[1:3]

    _, contour, _ = cv2.findContours(self.mask, cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)

    total_contour = contour[0]
    for ctr in contour[1:]:
        total_contour = np.concatenate((total_contour, ctr), axis =0)
    mmt = cv2.moments(total_contour)
    if(mmt['m00'] < 7500):
        raise SmallObjectError

    self.cy = int(mmt['m10']/mmt['m00']) #y is horrizon axis
    self.cx = int(mmt['m01']/mmt['m00']) #x is vertical axis

    x, y = self.mask.shape

    adjust = m_cx - self.cx + x - temp.shape[0]
    if(adjust > 0):
        m_cx = m_cx - adjust

    temp[(m_cx-self.cx):(m_cx-self.cx) +x, (m_cy-self.cy):(m_cy-self.cy) +y] = self.mask

    self.mask = temp

Answer 1

我同意Mark Serchell 的评论。我使用的方式是将变量设置为time + x seconds 并检查。 OpenCV 具有跳帧的有用功能，例如cam.grab()。它只会从缓冲区中读取该帧，但不会对其执行任何操作。这样，您可以避免“遭受缓冲”。简单的代码是：

import cv2
import time
cam = cv2.VideoCapture(url)
ret,frame = cam.read()
timeCheck = time.time()
future = 10*60 # delay
while ret:
    if time.time() >= timeCheck:
        ret,frame = cam.read()
        # Do your staff here
        timeCheck = time.time()+future
    else:
        # Read from buffer, but skip it
        ret = cam.grab() # note that grab() function returnt only status code,not the frame