gistfile1.txt

        # NB : cv2.UMat array is faster than np array
            pano = cv2.UMat(np.asarray([]))
            leftimage_gpu = cv2.cuda_GpuMat()
            rightimage_gpu = cv2.cuda_GpuMat()
            readFrame = 0
            while self.running:
                try:
                    # Initialize left and right frames
                    # CSI cameras frames works on 30 or 60 FPS but the sticher works under 3FPS (slower)
                    # Therefore it needs to store a frame for a longer period of time to be able to stitch
                    # if (self.left_camera.frame is not None and self.right_camera.frame is not None) or self.GPU:
                    if (self.left_camera.frame is not None and self.right_camera.frame is not None):
                        _, left_image = self.left_camera.read()
                        _, right_image = self.right_camera.read()       
                        stitch_start_time = time.time()
                        leftimage_gpu.upload(left_image)
                        rightimage_gpu.upload(right_image)

                        if self.stitched_frames == 0 or self.to_estimate is True:
                            status = self.stitcher.estimateTransform([left_image,right_image])
                            if status_check(status):
                                print(CODES.INFO, "Transform successfully estimated")
                                self.to_estimate = False

                            status,pano = self.stitcher.composePanorama([left_image,right_image],pano)
#                            self.pano.upload(pano)
                            if not status_check(status):
                                continue