使用GRAYSCALE图像创建BGR图像

Question

Camera提供GRAYSCALE数据，而深度学习模型需要BGR。 是否可以通过使用opencv或numpy或任何东西“堆叠”灰度图像来创建人工bgr图像？

我正在使用其他人创建的两个ROS包。 我尝试过以下方法：

试图改变模型以接受原始回购所描述的灰度。

尝试使用灰度转换为bgr

np_image = cv2.cvtColor(np_image, cv2.COLOR_GRAY2BGR)

尝试创建一个由图像时间三组成的数组

np_image = np.array([np_image, np_image, np_image])

以下代码检索图像

    def run(self):
        self._result_pub = rospy.Publisher('~result', Result, queue_size=1)
        vis_pub = rospy.Publisher('~visualization', Image, queue_size=1)
        sub = rospy.Subscriber('~input', Image,
                               self._image_callback, queue_size=1) 

        rate = rospy.Rate(self._publish_rate)
        while not rospy.is_shutdown():
            if self._msg_lock.acquire(False):
                msg = self._last_msg
                self._last_msg = None
                self._msg_lock.release()
            else:
                rate.sleep()
                continue

            if msg is not None:
                np_image = self._cv_bridge.imgmsg_to_cv2(msg, 
                    desired_encoding='mono8')
                #np_image = cv2.cvtColor(np_image, cv2.COLOR_GRAY2BGR) #(fail)
                np_image = np.array([np_image, np_image, np_image])
                # Run detection
                results = self._model.detect([np_image], verbose=0)
                result = results[0]
                result_msg = self._build_result_msg(msg, result)
                self._result_pub.publish(result_msg)

def _image_callback(self, msg):
        rospy.logdebug("Get an image")
        if self._msg_lock.acquire(False):
            self._last_msg = msg
            self._msg_lock.release()

我希望模型检索数据，评估它并返回一个对象id和掩码。 但是，我收到以下错误：

Traceback (most recent call last):
  File "/home/riwo-rack-pc/ROS_Mask_rcnn/src/mask_rcnn_ros/nodes/mask_rcnn_node", line 196, in <module>
    main()
  File "/home/riwo-rack-pc/ROS_Mask_rcnn/src/mask_rcnn_ros/nodes/mask_rcnn_node", line 192, in main
    node.run()
  File "/home/riwo-rack-pc/ROS_Mask_rcnn/src/mask_rcnn_ros/nodes/mask_rcnn_node", line 116, in run
    results = self._model.detect([np_image], verbose=0)
  File "/home/riwo-rack-pc/ROS_Mask_rcnn/src/mask_rcnn_ros/src/mask_rcnn_ros/model.py", line 2333, in detect
    molded_images, image_metas, windows = self.mold_inputs(images)
  File "/home/riwo-rack-pc/ROS_Mask_rcnn/src/mask_rcnn_ros/src/mask_rcnn_ros/model.py", line 2236, in mold_inputs
    padding=self.config.IMAGE_PADDING)
  File "/home/riwo-rack-pc/ROS_Mask_rcnn/src/mask_rcnn_ros/src/mask_rcnn_ros/utils.py", line 409, in resize_image
    image, (round(h * scale), round(w * scale)))
  File "/home/riwo-rack-pc/.local/lib/python2.7/site-packages/scipy/misc/pilutil.py", line 490, in imresize
    imnew = im.resize(size, resample=func[interp])
  File "/home/riwo-rack-pc/.local/lib/python2.7/site-packages/PIL/Image.py", line 1806, in resize
    return self._new(self.im.resize(size, resample, box))
TypeError: integer argument expected, got float

我尽可能地跟踪了痕迹，但是找不到引入浮点的点。

Answer 1

merged_image = cv2.merge((np_image, np_image, np_image))

应该给你你想要的东西。