from random import randint mutex = Lock() + class DrawBasicDetections(Node): def __init__(self):

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def try_draw(self): if not self.unprocessed_images or not self.unprocessed_dets or self.transform is None or self.camera_info is None: return - + with mutex: image_msg = self.unprocessed_images.popleft() det_3d_msg = self.unprocessed_dets.popleft()

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for det_msg in det_3d_msg.detections: bbox = det_msg.bbox - center = np.array([bbox.center.position.x, bbox.center.position.y, bbox.center.position.z]) - rot = Rotation.from_quat([bbox.center.orientation.x, bbox.center.orientation.y, bbox.center.orientation.z, bbox.center.orientation.w]) + center = np.array( + [bbox.center.position.x, bbox.center.position.y, bbox.center.position.z]) + rot = Rotation.from_quat([bbox.center.orientation.x, bbox.center.orientation.y, + bbox.center.orientation.z, bbox.center.orientation.w]) size = np.array([bbox.size.x, bbox.size.y, bbox.size.z]) # get all 8 corners - vert = [ center + rot.apply(np.multiply(size , np.array([-1, 1, 1]))), - center + rot.apply(np.multiply(size , np.array([-1, -1, 1]))), - center + rot.apply(np.multiply(size , np.array([-1, -1, -1]))), - center + rot.apply(np.multiply(size , np.array([-1, 1, -1]))), - center + rot.apply(np.multiply(size , np.array([1, 1, 1]))), - center + rot.apply(np.multiply(size , np.array([1, -1, 1]))), - center + rot.apply(np.multiply(size , np.array([1, -1, -1]))), - center + rot.apply(np.multiply(size , np.array([1, 1, -1]))), - ] + vert = [center + rot.apply(np.multiply(size, np.array([-1, 1, 1]))), + center + rot.apply(np.multiply(size, np.array([-1, -1, 1]))), + center + rot.apply(np.multiply(size, np.array([-1, -1, -1]))), + center + rot.apply(np.multiply(size, np.array([-1, 1, -1]))), + center + rot.apply(np.multiply(size, np.array([1, 1, 1]))), + center + rot.apply(np.multiply(size, np.array([1, -1, 1]))), + center + rot.apply(np.multiply(size, np.array([1, -1, -1]))), + center + rot.apply(np.multiply(size, np.array([1, 1, -1]))), + ] color = (randint(0, 255), randint(0, 255), randint(0, 255)) verts_2d = []

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# draw edges for i in range(4): - image = cv2.line(image, verts_2d[i], verts_2d[(i+1) % 4], color, 10) # face 1 - image = cv2.line(image, verts_2d[i+4], verts_2d[(i+1) % 4 + 4], color, 10) # face 2 - image = cv2.line(image, verts_2d[i], verts_2d[i+4], color, 10) # connect faces + image = cv2.line(image, verts_2d[i], verts_2d[(i+1) % 4], color, 10) # face 1 + image = cv2.line(image, verts_2d[i+4], verts_2d[(i+1) % 4 + 4], color, 10) # face 2 + image = cv2.line(image, verts_2d[i], verts_2d[i+4], color, 10) # connect faces self.publish_viz(image, image_msg) - + def publish_viz(self, cv_img, msg): imgmsg = self.cv_bridge.cv2_to_imgmsg(cv_img, "bgr8") imgmsg.header.stamp = msg.header.stamp imgmsg.header.frame_id = msg.header.frame_id self.viz_publisher.publish(imgmsg) + def main(args=None): rclpy.init(args=args)

Detected infrastructure changes

Using md-2d_3d_detections as the source branch

Using main as the target branch