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Gautam Dobariya 2023-04-13 14:36:49 +02:00
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README.md
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@ -7,45 +7,45 @@ Platform: ROS 2, Humble, Ubuntu 22.04
## How to install dependencies??
- Install `git`
```
$ sudo apt install git
sudo apt install git
```
- Install `ROS 2 Humble` on `Ubuntu 22.04` by following https://docs.ros.org/en/foxy/Installation/Ubuntu-Install-Debians.html
- Install `colcon build` by following https://docs.ros.org/en/foxy/Tutorials/Beginner-CLI-Tools/Configuring-ROS2-Environment.html
```
$ sudo apt install python3-colcon-common-extensions
sudo apt install python3-colcon-common-extensions
```
- Instal `pip` for python packages
```
$ sudo apt install python3-pip
sudo apt install python3-pip
```
- Now clone the repository
```
$ git clone https://tea.der-space.de/apoorva/greenhouse.git
git clone https://tea.der-space.de/apoorva/greenhouse.git
```
- Install `ultralytics` for yolov3 package
```
$ pip install ultralytics
pip install ultralytics
```
- For `yolov3_ros`, there are a bunch of other requirements. Go to `yolov3` folder and install using following commands:
```
$ cd ~/greenhouse/yolov3
$ pip install -r requirements.txt
cd ~/greenhouse/yolov3
pip install -r requirements.txt
```
- Go to `ros2_ws` inside `greenhouse`. Make sure you only have `src` folder.
```
$ cd ~/greenhouse/ros2_ws
$ ls
cd ~/greenhouse/ros2_ws
ls
src
```
- Inside `ros2_ws` folder, start building individual packages in the below sequence to avoid errors.
```
$ colcon build --packages-select pipe_msgs
$ colcon build --packages-select pcl_ros
$ colcon build --allow-overriding pcl_ros
$ colcon build --packages-select pcl_conversions
$ colcon build --allow-overriding pcl_conversions
$ colcon build --packages-select find-pose
$ colcon build --packages-select yolov3_ros
colcon build --packages-select pipe_msgs
colcon build --packages-select pcl_ros
colcon build --allow-overriding pcl_ros
colcon build --packages-select pcl_conversions
colcon build --allow-overriding pcl_conversions
colcon build --packages-select find-pose
colcon build --packages-select yolov3_ros
. install/setup.bash
```
- The code should be ready to launch as explained in [How to run Live Detection?](#how-to-run-live-detection)
@ -54,22 +54,22 @@ This section explains what each module is responsible for.
This module is responsible for providing `pcl_conversions` and `pcl_ros` modules in `ros 2`.
To build, run the following command:
```
$ cd ros2_ws/
$ colcon build --packages-select perception_pcl
$ . install/setup.bash
cd ros2_ws/
colcon build --packages-select perception_pcl
. install/setup.bash
```
## pipe_msgs
This module contains ros msgs for storing information about the detected object's bounding box.
```
$ cd ros2_ws/
$ colcon build --packages-select pipe_msgs
$ . install/setup.bash
cd ros2_ws/
colcon build --packages-select pipe_msgs
. install/setup.bash
```
To check if msgs are built properly, run following command
```
$ ros2 interface show pipe_msgs/msg/BoundingBox
ros2 interface show pipe_msgs/msg/BoundingBox
```
The output will be:
float64 probability
int64 xmin
@ -78,7 +78,7 @@ int64 xmax
int64 ymax
int16 id
string class_id
```
## find-pose
This ROS module is responsible for determining the position of the detected objects.
@ -92,9 +92,9 @@ Output:
How to build and run?
This package is dependent on custom `pcl_conversion` and `pcl_ros` module. Make sure you have built those before building this package.
```
$ colcon build --packages-select find-pose
$ . install/setup.bash
$ ros2 launch find-pose find-pose-node.launch.py
colcon build --packages-select find-pose
. install/setup.bash
ros2 launch find-pose find-pose-node.launch.py
```
All the topics can be remapped in the launch file.
@ -118,10 +118,10 @@ The following are the output topics:
How to build and run?
```
$ colcon build --packages-select yolov3_ros
$ . install/setup.bash
$ cd greenhouse/ros2_ws/
$ ros2 launch yolov3_ros pipe_detection.launch.py
colcon build --packages-select yolov3_ros
. install/setup.bash
cd greenhouse/ros2_ws/
ros2 launch yolov3_ros pipe_detection.launch.py
```
All the topics can be remapped in the launch file. The path to best_weights can also be changed inside the launch file.
Launch file is stored in `yolov3_ros/launch/`.
@ -141,7 +141,7 @@ drive.mount("/content/gdrive")
```
- Upload the yolov3 code and cd into the location of code
```
%cd /content/gdrive/MyDrive/yolov3
cd /content/gdrive/MyDrive/yolov3
```
- Run the training script
```
@ -162,12 +162,12 @@ This ROS module converts the rosbag data to images for yolo training purpose etc
- Create folder called `stereo` inside convert_2_img module.
- Run following command to launch the node. Currently, this node listens for `/camera/color/image_raw` topic.
```
$ cd ros2_ws/src/convert_2_img
$ python3 convert_2_img/convert_to_img.py
cd ros2_ws/src/convert_2_img
python3 convert_2_img/convert_to_img.py
```
- Play the rosbag in another terminal
```
$ ros2 bag play bag/bag.db
ros2 bag play bag/bag.db
```
- Once bag has finished playing, the images will be stored inside `stereo` folder.
@ -175,8 +175,8 @@ $ ros2 bag play bag/bag.db
This module is used to label images for yolo. The pre-defined custom classes file was changed to use new labels. This file is stored in `cd labelImg/data/predefined_classes.txt`
To launch the gui, run
```
$ cd labelImg
$ python3 labelImg.py
cd labelImg
python3 labelImg.py
```
More details: https://github.com/heartexlabs/labelImg
@ -216,7 +216,7 @@ You have the following required data in forms of ros topic:
How do you get this data?
- This data can come from a pre recorded Rosbag. If this is the case, do following:
```
$ ros2 bag play bag-folder/bag-name.db3
ros2 bag play bag-folder/bag-name.db3
```
- This data can come directly from camera's (D455/ZED2I) ROS Node: Launch your node in a terminal.
- If your camera topics have different names than the default topic names mentioned above, update/remap ONLY the `pipe_detection.launch.py` script stored in `ros2_ws/src/yolov3_ros/launch` folder.
@ -227,13 +227,13 @@ Steps to run:
- Run `$ cd greenhouse/ros2_ws/` and `$ . install/setup.bash`.
- Launch node for object detection:
```
$ ros2 launch yolov3_ros pipe_detection.launch.py
ros2 launch yolov3_ros pipe_detection.launch.py
```
- This node will output two topics: `/bboxes` and `/detection_image`.
- Make sure that you run this launch file from `greenhouse/ros2_ws/` folder since the path of weights is relative (`/src/pipe_weights.pt`) inside the launch file.
- Launch node for pose estimation:
```
$ ros2 launch find-pose find-pose-node.launch.py
ros2 launch find-pose find-pose-node.launch.py
```
- This node will output TF topics between `/camera_link` and `/${detected_object_name}`.
- Open RVIZ by running `$ rviz2`. Change `fixed frame` from `map` to `camera_link`.