Node to filter raw human detection locations with the Wire package

Here is how the human detection pipeline currently works:

1. The darknet node pushes out bounding boxes of detected objects.
2. These bounding boxes are captured by the rgb_human_detection_node along with near-syncrhonous depth images. Image transofmrations are used to rectify the bounding boxes into the depth frame, from which a depth value is extracted, and projected into the real world relative to the RealSense camera. These relative human locations in (x,y,z) are then pushed out as /dragoon_messages/Objects.
3. This node (detection_filter) grabs these relative human detection locations and pre-processes them (April 12: Pre-processesing only consists of ignoring relative detections over 8m away or under 0.05m away). These pre-processed detections are then transformed to the /map frame using the TF-tree and are published as wire_msgs/WorldEvidence to be fed into the global Kalman filter.
4. The global Kalman filter wire_core takes in these wire_msgs/WorldEvidence evidences, does probability magic, and outputs wire_msgs/WorldState messages representing our filtered human detections in the /map frame.
5. The visualizer eats up wire_msgs/WorldEvidence and wire_msgs/WorldState to display markers that represent the world evidence (pre-processed detections transformed to the global frame) and the world state (aka filtered detections) in their appropriate places on the /map frame.

So we clearly have some issues with the human detection pipeline. Where are they? Fuck me I don't know but lets find out. Something is certainly wrong in the rgb_human_detection_node, detection_filter, and/or visualizer, or some synchronization/timing issue between imagery. Testing out an updated node anywehere along this chain requires removing some of the messages from the rosbag above. Specifically, it requires removing all messages along this pipeline downstream of the targeted node.

That said, the best way to try out new algorithms is the folliwing procedure:

1. Remove all rosmsgs downstream of the darknet node
2. Run all downstream nodes locally
3. Replay the rosbag with use_sime_time set to true and --clock set to the rosbag timer

Use this command to filter the new bag into a filtered one called April12_Filtered.bag or whatever the fuck you want I'm not your dad

rosbag filter April12_SVD_test_human_detection_tf_off.bag April12_Filtered.bag "topic!='/world_state' and topic!='/world_evidence' and topic!='/ObjectPoses'"

1. Pull our repos for darkenet_ros_msgs (see last section for cloning only msgs without the rest), RealSenseDev (which includes rgb_human_detection_node), detection_filter, wire and visualizer into you catkin_ws/src/. If you havent already installed jsk for the visualizer then: sudo apt-get install ros-melodic-jsk-visualization. There might be other dependencies just hmu if you run into issues building these nodes. wire is gonna throw a fuck ton of warnings when you build about some highly problematic Cube, idk what they are but don't worry about them.
2. The rgb_human_detection_node requires pyrealsense2 libraries. pip install pyrealsense2
3. catkin_make duh
4. roslaunch dragoon_bringup detection_testing.launch This launches rgb_human_detection_node, detection_filter, wire_core, and visualizer
5. rosbag play <FILTERED_BAGFILE>.bag --clock <FILTERED_BAGFILE>.bag

There you have it. Happy bug hunting

If you just want the messages and not having to pull the whole darknet repo with all the weights and shit:

cd catkin_ws/src/
mkdir darknet_ros
cd darknet_ros
git init
git remote add origin https://github.com/howde-robotics/darknet_ros.git
git fetch
git checkout origin/master darknet_ros_msgs/*