How to use the pypylon.pylon.TimeoutHandling_ThrowException function in pypylon

camera.Width.SetValue(new_width)

    # The parameter MaxNumBuffer can be used to control the count of buffers
    # allocated for grabbing. The default value of this parameter is 10.
    camera.MaxNumBuffer = 5

    # Start the grabbing of c_countOfImagesToGrab images.
    # The camera device is parameterized with a default configuration which
    # sets up free-running continuous acquisition.
    camera.StartGrabbingMax(countOfImagesToGrab)

    # Camera.StopGrabbing() is called automatically by the RetrieveResult() method
    # when c_countOfImagesToGrab images have been retrieved.
    while camera.IsGrabbing():
        # Wait for an image and then retrieve it. A timeout of 5000 ms is used.
        grabResult = camera.RetrieveResult(5000, pylon.TimeoutHandling_ThrowException)

        # Image grabbed successfully?
        if grabResult.GrabSucceeded():
            # Access the image data.
            print("SizeX: ", grabResult.Width)
            print("SizeY: ", grabResult.Height)
            img = grabResult.Array
            print("Gray value of first pixel: ", img[0, 0])
        else:
            print("Error: ", grabResult.ErrorCode, grabResult.ErrorDescription)
        grabResult.Release()
    camera.Close()

except genicam.GenericException as e:
    # Error handling.
    print("An exception occurred.")

prediction_list=['cardboard', 'glass', 'metal', 'paper', 'plastic', 'trash']
model=load_model('models/model1.h5', custom_objects={'relu6': mobilenet.relu6})

camera = pylon.InstantCamera(pylon.TlFactory.GetInstance().CreateFirstDevice())

numberOfImagesToGrab = 100
camera.StartGrabbingMax(numberOfImagesToGrab)

converter = pylon.ImageFormatConverter()
converter.OutputPixelFormat = pylon.PixelType_BGR8packed
converter.OutputBitAlignment = pylon.OutputBitAlignment_MsbAligned
i=0
while camera.IsGrabbing():
    time.sleep(0.005)
    grabResult = camera.RetrieveResult(5000, pylon.TimeoutHandling_ThrowException)

    if grabResult.GrabSucceeded():
        # Access the image data.
        print("SizeX: ", grabResult.Width)
        print("SizeY: ", grabResult.Height)
        #import ipdb; ipdb.set_trace()
        img = converter.Convert(grabResult).GetArray()
        cv2.imwrite('pic.png', img)
        pred_img=pp_image(img)
        yo=model.predict(pred_img)
        pred=prediction_list[np.argmax(yo)]
        cv2.putText(img, pred, (10,1000), cv2.FONT_HERSHEY_SIMPLEX, 5, (0,0,0), 5, False)
        name='img'+str(i)+'.png'
        cv2.imwrite(os.path.join('prediction_images', name), img)
        i=i+1
        #print("Gray value of first pixel: ", img[0, 0])

def read(self):
        """ """
        grabResult = self.camera.RetrieveResult(
            5000, pylon.TimeoutHandling_ThrowException
        )

        if grabResult.GrabSucceeded():
            # Access the image data.
            # print("SizeX: ", grabResult.Width)
            # print("SizeY: ", grabResult.Height)
            img = grabResult.Array
            # print("Gray value of first pixel: ", img[0, 0])
            grabResult.Release()
            return img

        else:
            return None

self._camera.StopGrabbing()

        # converting to opencv bgr format
        converter = pylon.ImageFormatConverter()
        converter.OutputPixelFormat = pylon.PixelType_BGR8packed
        converter.OutputBitAlignment = pylon.OutputBitAlignment_MsbAligned

        if(not self._impro_own_window):
            cv2.namedWindow('camera_image', cv2.WINDOW_NORMAL | cv2.WINDOW_GUI_NORMAL)
            if(window_size is not None):
                cv2.resizeWindow('camera_image', window_size[0], window_size[1])

        self._camera.StartGrabbing(grab_strategy)
        try:
            while(self._camera.IsGrabbing()):
                grab_result = self._camera.RetrieveResult(5000, pylon.TimeoutHandling_ThrowException)

                if grab_result.GrabSucceeded():
                    # Access the image data
                    image = converter.Convert(grab_result)
                    img = image.GetArray()

                    if(self._impro_own_window):
                        self._impro_function(img)
                    elif(self._impro_function is not None):
                        img = self._impro_function(img)
                        if(not isinstance(img, np.ndarray)):
                            cv2.destroyAllWindows()
                            raise ValueError("The given impro_function must return a numpy array when own_window=False")
                        cv2.imshow('camera_image', img)
                    else:
                        cv2.imshow('camera_image', img)