I have initiated a single object detection model using the coco ssd.
I am trying to detect objects from 2 different cameras

我已经使用Coco SSD启动了一个单目标检测模型。我正在试着从两个不同的摄像头检测物体

THE LOGIC OF THE CODE:-

代码的逻辑是：-

model=cv2.dnn_DetectionModel(weightsPath,configPath)
cam1=cv2.VideoCapture(0)
cam1=cv2.VideoCapture(1)

#thread 1
while true:
    success1,img1 = cam1.read()
    result1=model.detect(img1)
    cv2.imshow("result1", result1)
    if cv2.waitKey(2) & 0xFF==ord('x'):
        break

#thread 2 
while true:
    success2,img2 = cam2.read()
    result2=model.detect(img2)
    cv2.imshow("result2", result2)
    if cv2.waitKey(2) & 0xFF==ord('x'):
        break

using this approach in neither of the video frames the correct objects are detected

The above image shows the output i am getting.
with a single thread it works fine but if i try running more than one thread then it starts producing such errors for all video sources.
why is this happening???
what might be the solution?

使用这种方法，在两个视频帧中都没有检测到正确的对象，上面的图像显示了我正在获得的输出。对于单个线程，它工作得很好，但如果我尝试运行多个线程，它就会开始为所有视频源产生这样的错误。为什么会发生这种事？可能的解决方案是什么？

Depending how your actual code handles race conditions, you should try using two separate instances of your model, one for each thread. Something like:

根据实际代码处理竞争条件的方式，您应该尝试使用模型的两个单独实例，每个线程一个。类似于：

model1=cv2.dnn_DetectionModel(weightsPath,configPath)
model2=cv2.dnn_DetectionModel(weightsPath,configPath)