动态物体检测-复杂环境下多目标动态物体实时检测算法实现-优质项目实战.zip

# Dynablox An online volumetric mapping-based approach for real-time detection of diverse dynamic objects in complex environments. <p align="center"> <img width='100%' src="https://user-images.githubusercontent.com/36043993/232650770-a042cbb9-c251-42f9-8a96-d7d9273fec96.gif"> </p> # Setup There is a [docker image](https://hub.docker.com/repository/docker/zhangkin/dynablox/general) available for this package. Check the usage in the dockerhub page. ## Installation * **Note on Versioning:** This package was developed using Ubuntu 20.04 using ROS Noetic. Other versions should also work but support can not be guaranteed. 1. If not already done so, install [ROS](http://wiki.ros.org/action/fullsearch/melodic/Installation/Ubuntu?action=fullsearch&context=180&value=linkto%3A%22melodic%2FInstallation%2FUbuntu%22). We recommend using `Desktop-Full`. 2. If not already done so, setup a catkin workspace: ```bash mkdir -p ~/catkin_ws/src cd ~/catkin_ws catkin init catkin config --extend /opt/ros/$ROS_DISTRO catkin config --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo catkin config --merge-devel ``` 2. Install system dependencies: ```bash sudo apt-get install python3-vcstool python3-catkin-tools ros-$ROS_DISTRO-cmake-modules protobuf-compiler autoconf git rsync -y ``` 3. Download the project. ```bash cd ~/catkin_ws/src # download the project ``` 4. Install ROS dependencies: ```bash cd ~/catkin_ws/src vcs import . < ./dynablox/ssh.rosinstall --recursive ``` 5. Build: ```bash catkin build dynablox_ros ``` ## Datasets To run the demos we use the [Urban Dynamic Objects LiDAR (DOALS) Dataset](https://projects.asl.ethz.ch/datasets/doku.php?id=doals). To download the data and pre-process it for our demos, use the provided script: ```bash roscd dynablox_ros/scripts ./download_doals_data.sh /home/$USER/data/DOALS # Or your preferred data destination. ``` We further collect a new dataset featuring diverse dynamic objects in complex scenes. The full dataset and description ca nbe found [here](https://projects.asl.ethz.ch/datasets/doku.php?id=dynablox). To download the processed ready-to-run data for our demos, use the provided script: ```bash roscd dynablox_ros/scripts ./download_dynablox_data.sh /home/$USER/data/Dynablox # Or your preferred data destination. ``` # Examples ## Running a DOALS Sequence 1. If not done so, download the DOALS dataset as explained [here](#datasets). 2. Adjust the dataset path in `dynablox_ros/launch/run_experiment.launch`: ```xml <arg name="bag_file" default="/home/$(env USER)/data/DOALS/hauptgebaeude/sequence_1/bag.bag" /> ``` 3. Run ```bash roslaunch dynablox_ros run_experiment.launch ``` 4. You should now see dynamic objects being detected as the sensor moves through the scene:  ## Running a Dynablox Sequence 1. If not done so, download the Dynablox dataset as explained [here](#datasets). 2. Adjust the dataset path in `dynablox_ros/launch/run_experiment.launch` and set `use_doals` to false: ```xml <arg name="use_doals" default="false" /> <arg name="bag_file" default="/home/$(env USER)/data/Dynablox/processed/ramp_1.bag" /> ``` 3. Run ```bash roslaunch dynablox_ros run_experiment.launch ``` 4. You should now see dynamic objects being detected as the sensor moves through the scene:  ## Running and Evaluating an Experiment ### Running an Experiment 1. If not done so, download the DOALS dataset as explained [here](#datasets). 2. Adjust the dataset path in `dynablox_ros/launch/run_experiment.launch`: ```xml <arg name="bag_file" default="/home/$(env USER)/data/DOALS/hauptgebaeude/sequence_1/bag.bag" /> ``` 3. In `dynablox_ros/launch/run_experiment.launch`, set the `evaluate` flag, adjust the ground truth data path, and specify where to store the generated outpuit data: ```xml <arg name="evaluate" default="true" /> <arg name="eval_output_path" default="/home/$(env USER)/dynablox_output/" /> <arg name="ground_truth_file" default="/home/$(env USER)/data/DOALS/hauptgebaeude/sequence_1/indices.csv" /> ``` 3. Run ```bash roslaunch dynablox_ros run_experiment.launch ``` 4. Wait till the dataset finished processing. Dynablox should shutdown automatically afterwards. ### Analyzing the Data - **Printing the Detection Performance Metrics:** 1. Run: ```bash roscd dynablox_ros/src/evaluation python3 evaluate_data.py /home/$USER/dynablox_output ``` 2. You should now see the performance statistics for all experiments in that folder: ``` 1/1 data entries are complete. Data object_IoU object_Precision object_Recall hauptgebaeude_1 89.8 +- 5.6 99.3 +- 0.4 90.3 +- 5.6 All 89.8 +- 5.6 99.3 +- 0.4 90.3 +- 5.6 ``` - **Inspecting the Segmentation:** 1. Run: ```bash roslaunch dynablox_ros cloud_visualizer.launch file_path:=/home/$USER/dynablox_output/clouds.csv ``` 2. You should now see the segmentation for the annotated ground truth clouds, showing True Positives (green), True Negatives (black), False Positives (blue), False Negatives (red), and out-of-range (gray) points:  - **Inspecting the Run-time and Configuration:** Additional information is automatically stored in `timings.txt` and `config.txt` for each experiment. ### Advanced Options * **Adding Drift to an Experiment:** To run an experiment with drift specify one of the pre-computed drift rollouts in `dynablox_ros/launch/run_experiment.launch`: ```xml <arg name="drift_simulation_rollout" default="doals/hauptgebaeude/sequence_1/light_3.csv" /> ``` All pre-computed rollouts can be found in `drift_simulation/config/rollouts`. Note that the specified sequence needs to match the data being played. For each sequence, there exist 3 rollouts for each intensity. Alternatively, use the `drift_simulation/launch/generate_drift_rollout.launch` to create new rollouts for other datasets. * **Changing th Configuration of Dynablox:** All parameters that exist in dynablox are listed in `dynablox_ros/config/motion_detector/default.yaml`, feel free to tune the method for your use case!