使用 opencv 绘制多个视频时出现此错误？

如何解决使用 opencv 绘制多个视频时出现此错误？

我正在尝试在多个视频捕获流上绘制边界框。在更改下面的代码以允许它处于 for 循环中后，我收到此错误（首先不确定这是否有效）。

有人建议我将视频捕获的数据放入一个 numpy 数组而不是列表中以避免错误，但我不确定。

这是错误：

Traceback (most recent call last):
  File "C:\Users\abdul\PythonProjects\Social-distance-detection-mastera\social_distance_detector.py",line 119,in <module>
    cv2.rectangle(frame,(startX,startY),(endX,endY),color,2)
TypeError: an integer is required (got type tuple)
[Finished in 5.2s with exit code 1]
[shell_cmd: python -u "C:\Users\abdul\PythonProjects\Social-distance-detection-mastera\social_distance_detector.py"]
[dir: C:\Users\abdul\PythonProjects\Social-distance-detection-mastera]
[path: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\bin;C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\libnvvp;C:\Program Files (x86)\Intel\Intel(R) Management Engine Components\iCLS\;C:\Program Files\Intel\Intel(R) Management Engine Components\iCLS\;C:\Program Files (x86)\Common Files\Oracle\Java\javapath;C:\ProgramData\Oracle\Java\javapath;D:\oracle\product\10.2.0\db_1\bin;C:\windows\system32;C:\windows;C:\windows\System32\Wbem;C:\windows\System32\WindowsPowerShell\v1.0\;C:\WINDOWS\system32;C:\WINDOWS;C:\WINDOWS\System32\Wbem;C:\WINDOWS\System32\WindowsPowerShell\v1.0\;C:\WINDOWS\System32\OpenSSH\;C:\Program Files (x86)\NVIDIA Corporation\PhysX\Common;C:\Program Files (x86)\Microsoft SQL Server\100\Tools\Binn\;C:\Program Files\Microsoft SQL Server\100\Tools\Binn\;C:\Program Files\Microsoft SQL Server\100\DTS\Binn\;C:\Program Files (x86)\Intel\Intel(R) Management Engine Components\DAL;C:\Program Files\Intel\Intel(R) Management Engine Components\DAL;C:\Program Files (x86)\Intel\Intel(R) Management Engine Components\IPT;C:\Program Files\Intel\Intel(R) Management Engine Components\IPT;C:\WINDOWS\system32;C:\WINDOWS;C:\WINDOWS\System32\Wbem;C:\WINDOWS\System32\WindowsPowerShell\v1.0\;C:\WINDOWS\System32\OpenSSH\;C:\Program Files\dotnet\;C:\Program Files\Microsoft SQL Server\130\Tools\Binn\;C:\Program Files (x86)\Brackets\command;C:\Program Files\Intel\WiFi\bin\;C:\Program Files\Common Files\Intel\WirelessCommon\;D:\xampp\php;C:\ProgramData\ComposerSetup\bin;d:\Program Files\Git\cmd;d:\Program Files\Git\mingw64\bin;d:\Program Files\Git\usr\bin;C:\Program Files\NVIDIA Corporation\Nsight Compute 2019.1\;C:\Program Files\NVIDIA Corporation\NVIDIA NvDLISR;d:\Users\abdul\Anaconda3;d:\Users\abdul\Anaconda3\Library\mingw-w64\bin;d:\Users\abdul\Anaconda3\Library\usr\bin;d:\Users\abdul\Anaconda3\Library\bin;d:\Users\abdul\Anaconda3\Scripts;C:\Users\abdul\AppData\Local\Microsoft\WindowsApps;C:\Users\abdul\AppData\Roaming\Composer\vendor\bin;C:\Users\abdul\AppData\Local\GitHubDesktop\bin;%DASHLANE_DLL_DIR%;C:\Users\abdul\AppData\Local\Microsoft\WindowsApps;]

发生在这个块中：

for frame) in streams:
            cv2.rectangle(frame,2)
            cv2.circle(frame,(cX,cY),5,1)

我在互联网上找到了一个建议，可以像这样在 args 中表达：

for frame in streams:
            cv2.rectangle(frame,int(startX,int(endX,1)

但我得到了这个错误：

    Traceback (most recent call last):
  File "C:\Users\abdul\PythonProjects\Social-distance-detection-mastera\social_distance_detector.py",2)
ValueError: int() base must be >= 2 and <= 36,or 0
[Finished in 2.8s with exit code 1]
[shell_cmd: python -u "C:\Users\abdul\PythonProjects\Social-distance-detection-mastera\social_distance_detector.py"]
[dir: C:\Users\abdul\PythonProjects\Social-distance-detection-mastera]
[path: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\bin;C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\libnvvp;C:\Program Files (x86)\Intel\Intel(R) Management Engine Components\iCLS\;C:\Program Files\Intel\Intel(R) Management Engine Components\iCLS\;C:\Program Files (x86)\Common Files\Oracle\Java\javapath;C:\ProgramData\Oracle\Java\javapath;D:\oracle\product\10.2.0\db_1\bin;C:\windows\system32;C:\windows;C:\windows\System32\Wbem;C:\windows\System32\WindowsPowerShell\v1.0\;C:\WINDOWS\system32;C:\WINDOWS;C:\WINDOWS\System32\Wbem;C:\WINDOWS\System32\WindowsPowerShell\v1.0\;C:\WINDOWS\System32\OpenSSH\;C:\Program Files (x86)\NVIDIA Corporation\PhysX\Common;C:\Program Files (x86)\Microsoft SQL Server\100\Tools\Binn\;C:\Program Files\Microsoft SQL Server\100\Tools\Binn\;C:\Program Files\Microsoft SQL Server\100\DTS\Binn\;C:\Program Files (x86)\Intel\Intel(R) Management Engine Components\DAL;C:\Program Files\Intel\Intel(R) Management Engine Components\DAL;C:\Program Files (x86)\Intel\Intel(R) Management Engine Components\IPT;C:\Program Files\Intel\Intel(R) Management Engine Components\IPT;C:\WINDOWS\system32;C:\WINDOWS;C:\WINDOWS\System32\Wbem;C:\WINDOWS\System32\WindowsPowerShell\v1.0\;C:\WINDOWS\System32\OpenSSH\;C:\Program Files\dotnet\;C:\Program Files\Microsoft SQL Server\130\Tools\Binn\;C:\Program Files (x86)\Brackets\command;C:\Program Files\Intel\WiFi\bin\;C:\Program Files\Common Files\Intel\WirelessCommon\;D:\xampp\php;C:\ProgramData\ComposerSetup\bin;d:\Program Files\Git\cmd;d:\Program Files\Git\mingw64\bin;d:\Program Files\Git\usr\bin;C:\Program Files\NVIDIA Corporation\Nsight Compute 2019.1\;C:\Program Files\NVIDIA Corporation\NVIDIA NvDLISR;d:\Users\abdul\Anaconda3;d:\Users\abdul\Anaconda3\Library\mingw-w64\bin;d:\Users\abdul\Anaconda3\Library\usr\bin;d:\Users\abdul\Anaconda3\Library\bin;d:\Users\abdul\Anaconda3\Scripts;C:\Users\abdul\AppData\Local\Microsoft\WindowsApps;C:\Users\abdul\AppData\Roaming\Composer\vendor\bin;C:\Users\abdul\AppData\Local\GitHubDesktop\bin;%DASHLANE_DLL_DIR%;C:\Users\abdul\AppData\Local\Microsoft\WindowsApps;]

我是个菜鸟，所以我把完整的代码放在这一行后面以防万一它有帮助

# USAGE
# python social_distance_detector.py --input pedestrians.mp4
# python social_distance_detector.py --input pedestrians.mp4 --output output.avi

# import the necessary packages
from TheLazyCoder import social_distancing_config as config
from TheLazyCoder.detection import detect_people
from scipy.spatial import distance as dist
import numpy as np
import argparse
import imutils
import cv2
import os

# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i","--input",type=str,default="",help="path to (optional) input video file")
ap.add_argument("-o","--output",help="path to (optional) output video file")
ap.add_argument("-d","--display",type=int,default=1,help="whether or not output frame should be displayed")
args = vars(ap.parse_args())

# load the COCO class labels our YOLO model was trained on
labelsPath = os.path.sep.join([config.MODEL_PATH,"coco.names"])
LABELS = open(labelsPath).read().strip().split("\n")

# derive the paths to the YOLO weights and model configuration
weightsPath = os.path.sep.join([config.MODEL_PATH,"yolov3.weights"])
configPath = os.path.sep.join([config.MODEL_PATH,"yolov3.cfg"])

# load our YOLO object detector trained on COCO dataset (80 classes)
print("[INFO] loading YOLO from disk...")
net = cv2.dnn.readNetFromDarknet(configPath,weightsPath)

# check if we are going to use GPU
if config.USE_GPU:
    # set CUDA as the preferable backend and target
    print("[INFO] setting preferable backend and target to CUDA...")
    net.setPreferableBackend(cv2.dnn.DNN_BACKEND_CUDA)
    net.setPreferableTarget(cv2.dnn.DNN_TARGET_CUDA)

# determine only the *output* layer names that we need from YOLO
ln = net.getLayerNames()
ln = [ln[i[0] - 1] for i in net.getUnconnectedOutLayers()]

# initialize the video stream and pointer to output video file
print("[INFO] accessing video stream...")
vs =[ 
cv2.VideoCapture(0,cv2.CAP_DSHOW),cv2.VideoCapture(0,cv2.CAP_DSHOW)
]

writer = None

# loop over the frames from the video stream
while True:
    # read the next frame from the file
    streams=[]
    for cap in vs:
        grabbed,frame = cap.read()
        streams.append([grabbed,frame])


    

    # if the frame was not grabbed,then we have reached the end
    # of the stream
    if not grabbed:
        break

    # resize the frame and then detect people (and only people) in it
    
    frame = imutils.resize(frame,width=700)
    results = detect_people(frame,net,ln,personIdx=LABELS.index("person"))

    # initialize the set of indexes that violate the minimum social
    # distance
    violate = set()

    # ensure there are *at least* two people detections (required in
    # order to compute our pairwise distance maps)
    if len(results) >= 2:
        # extract all centroids from the results and compute the
        # Euclidean distances between all pairs of the centroids
        centroids = np.array([r[2] for r in results])
        D = dist.cdist(centroids,centroids,metric="euclidean")

        # loop over the upper triangular of the distance matrix
        for i in range(0,D.shape[0]):
            for j in range(i + 1,D.shape[1]):
                # check to see if the distance between any two
                # centroid pairs is less than the configured number
                # of pixels
                if D[i,j] < config.MIN_DISTANCE:
                    # update our violation set with the indexes of
                    # the centroid pairs
                    violate.add(i)
                    violate.add(j)

    # loop over the results
    for (i,(prob,bbox,centroid)) in enumerate(results):
        # extract the bounding box and centroid coordinates,then
        # initialize the color of the annotation
        (startX,startY,endX,endY) = bbox
        (cX,cY) = centroid
        color = (0,255,0)

        # if the index pair exists within the violation set,then
        # update the color
        if i in violate:
            color = (0,255)

        # draw (1) a bounding box around the person and (2) the
        # centroid coordinates of the person,for frame in streams:
            cv2.rectangle(frame,1)

    # draw the total number of social distancing violations on the
    # output frame
    for frame in streams:
        text = "Social Distancing Violations: {}".format(len(violate))
        cv2.putText(frame,text,(10,frame.shape[0] - 25),cv2.FONT_HERSHEY_SIMPLEX,0.85,(0,255),3)

    # check to see if the output frame should be displayed to our
    # screen
    for number,(grabbed,frame) in enumerate(streams):
        if args["display"] > 0:
        # show the output frame
            cv2.imshow(f'Cam {number}',frame)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

    # if an output video file path has been supplied and the video
    # writer has not been initialized,do so now
    if args["output"] != "" and writer is None:
        # initialize our video writer
        fourcc = cv2.VideoWriter_fourcc(*"MJPG")
        writer = cv2.VideoWriter(args["output"],fourcc,25,(frame.shape[1],frame.shape[0]),True)

    # if the video writer is not None,write the frame to the output
    # video file
    if writer is not None:
        writer.write(frame)

解决方法

您可以从 bbox 获得 startX、startY、endX、endY。我们不知道 bbox 是什么样子，因为这里没有显示 detect_people 函数。你得到的错误是说这些值之一， startX,startY,endX,endY 可能是一个元组而不是单个数字。只是为了检查，在调用 cv2.rectangle 之前打印出所有四个值。另外，我认为您误解了 int 转换建议。它应该是这样的：

cv2.rectangle(frame,(int(startX),int(startY)),(int(endX),int(endY)),color,2)

使用 opencv 绘制多个视频时出现此错误？

如何解决使用 opencv 绘制多个视频时出现此错误？

解决方法

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