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https://github.com/qengineering/traffic-counter-rock5c
A fully functional traffic counter on a bare RK3588 with MQTT and remote live viewer
https://github.com/qengineering/traffic-counter-rock5c
aarch64 bytetracker cpp deep-learning npu rk3566 rk3568 rk3588 rock5c traffic-counter traffic-counting
Last synced: 25 days ago
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A fully functional traffic counter on a bare RK3588 with MQTT and remote live viewer
- Host: GitHub
- URL: https://github.com/qengineering/traffic-counter-rock5c
- Owner: Qengineering
- Created: 2024-11-21T09:34:59.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2024-11-21T09:40:45.000Z (about 1 month ago)
- Last Synced: 2024-11-21T10:30:28.816Z (about 1 month ago)
- Topics: aarch64, bytetracker, cpp, deep-learning, npu, rk3566, rk3568, rk3588, rock5c, traffic-counter, traffic-counting
- Language: C++
- Homepage: https://qengineering.eu/deep-learning-examples-on-raspberry-32-64-os.html
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Traffic counter Rock 5C
## Traffic counter with a camera on a bare RK3566 / RK3568 / RK3588.
[](https://opensource.org/licenses/BSD-3-Clause)
Specially made for a Raspberry Pi 4, see [Q-engineering deep learning examples](https://qengineering.eu/deep-learning-examples-on-raspberry-32-64-os.html)
------------
## Introduction.
A fully functional traffic counter with a camera working on a bare Rock 5C.
Highlights:
- Stand alone.
- Lane selection.
- MQTT messages.
- JSON messages.
- Live web viewer.
- JSON settings.
- RTSP CCTV streaming.
- Debug screens.
------------
https://github.com/user-attachments/assets/9c7c9156-a5a2-4000-9dca-409b27980903
------------
## Dependencies.
To run the application, you have to:
- Optional: Code::Blocks installed. (```$ sudo apt-get install codeblocks```)
### Installing the dependencies.
Start with the usual
```shell
$ sudo apt-get update
$ sudo apt-get upgrade
$ sudo apt-get install curl libcurl4
$ sudo apt-get install cmake wget
```
#### OpenCV
Follow the Raspberry Pi 4 [guide](https://qengineering.eu/install-opencv-on-raspberry-64-os.html). Or:
```shell
$ sudo apt-get install libopencv-dev
```
#### Eigen3
```shell
$ sudo apt-get install libeigen3-dev
```
#### gflags
```shell
$ sudo apt-get install libgflags-dev
```
#### JSON for C++
written by [Niels Lohmann](https://github.com/nlohmann).
```shell
$ cd ~
$ git clone --depth=1 https://github.com/nlohmann/json.git
$ cd json
$ mkdir build
$ cd build
$ cmake ..
$ make -j4
$ sudo make install
$ sudo ldconfig
```
#### paho.mqtt (MQTT client)
```shell
$ cd ~
$ git clone --depth=1 https://github.com/eclipse/paho.mqtt.c.git
$ cd paho.mqtt.c
$ mkdir build
$ cd build
$ cmake ..
$ make -j4
$ sudo make install
$ sudo ldconfig
```
#### Mosquitto (MQTT broker)
```shell
$ sudo apt-get install mosquitto
```
------------
## Installing the app.
Download the software.
```
$ git clone https://github.com/Qengineering/Traffic-Counter-Rock5C.git
```
Your folder must now look like this:
```
.
├── CMakeLists.txt
├── config.json
├── include
│ ├── BYTETracker.h
│ ├── dataType.h
│ ├── General.h
│ ├── kalmanFilter.h
│ ├── lapjv.h
│ ├── MJPG_sender.h
│ ├── MJPGthread.h
│ ├── MQTT.h
│ ├── Numbers.h
│ ├── postprocess.h
│ ├── STrack.h
│ ├── TChannel.h
│ └── Tjson.h
├── models
│ ├── yolov5m.rknn
│ ├── yolov5n.rknn
│ ├── yolov5s_relu.rknn
│ └── yolov5s.rknn
├── src
│ ├── BYTETracker.cpp
│ ├── kalmanFilter.cpp
│ ├── lapjv.cpp
│ ├── main.cpp
│ ├── main_video.cpp
│ ├── MJPG_sender.cpp
│ ├── MJPGthread.cpp
│ ├── MQTT.cpp
│ ├── postprocess.cpp
│ ├── STrack.cpp
│ ├── TChannel.cpp
│ ├── Tjson.cpp
│ └── utils.cpp
├── Traffic.cbp
└── Traffic.mp4
```
------------
## Running the app.
You can use **Code::Blocks**.
- Load the project file *.cbp in Code::Blocks.
- Select _Release_, not Debug.
- Compile and run with F9.
- You can alter command line arguments with _Project -> Set programs arguments..._
Or use **Cmake**.
```shell
$ cd *MyDir*
$ mkdir build
$ cd build
$ cmake ..
$ make -j4
```
------------
## Settings.
All important settings are stored in the `config.json`
You can alter these to your liking. Please note the use of commas after each line, except the last one.
```json
{
"VERSION": "1.0.0.0",
"MQTT_ON": true,
"MQTT_SERVER_example": "broker.hivemq.com:1883",
"MQTT_SERVER": "localhost:1883",
"MQTT_CLIENT_ID": "Arrow",
"MQTT_TOPIC": "traffic",
"DEVICE_NAME": "highway 12",
"ANNOTATE": true,
"STREAM_example1": "rtsp://admin:[email protected]:554/stream1",
"STREAM_example2": "RaspiCam",
"STREAM": "Traffic.mp4",
"BORDER_X1": 10,
"BORDER_Y1": 300,
"BORDER_X2": 450,
"BORDER_Y2": 300,
"JSON_PORT": 8070,
"MJPEG_PORT": 8090,
"MJPEG_WIDTH": 640,
"MJPEG_HEIGHT": 480,
"MESSAGE_TIME": 2,
"PARAM_MODEL": "./models/yolo-fastestv2-opt.param",
"BIN_MODEL": "./models/yolo-fastestv2-opt.bin"
}
```
| Global parameter | Comment |
| ---- | ---- |
| VERSION | Current version. |
| MQTT_ON | Enable MQTT messages. 'true-false'. |
| MQTT_SERVER | MQTT server. Default `localhost:1883` |
| MQTT_CLIENT_ID | MQTT client ID. Default `Arrow` |
| MQTT_TOPIC | MQTT topic. Default `traffic` |
| DEVICE_NAME | Name of the camera, used in the MQTT messages. |
| ANNOTATE | Show lines, boxes and numbers in live view. Default `true` |
| STREAM | The used input source.
It can be a video or a `RaspiCam`, or an RTSP stream, like CCTV cameras. |
| BORDER_X1 | Left X position of the imaginary borderline. |
| BORDER_Y1 | Left Y position of the imaginary borderline. |
| BORDER_X2 | Right X position of the imaginary borderline. |
| BORDER_Y2 | Right Y position of the imaginary borderline. |
| JSON_PORT | The JSON message port number.|
| MJPEG_PORT | The thumbnail browser overview. |
| MJPEG_WIDTH | Thumbnail width |
| MJPEG_HEIGHT | Thumbnail height |
| MESSAGE_TIME | Define the interval between (MQTT) messages in seconds. Default 2. |
| PARAM_MODEL | Used nccn DNN model (parameters). |
| BIN_MODEL | Used nccn DNN model (weights). |
------------
------------
## Debug.
You can use debug mode to find the optimal position for the borderline.
To enable debug mode, start the app with the --debug flag set to true:
```shell
./Traffic --debug=true
```
Alternatively, you can modify the command line argument in Code::Blocks by navigating to Project -> Set programs arguments...
In debug mode, you’ll see the tail of each vehicle. When a vehicle’s tail crosses the imaginary borderline, it is added to the count.
At this point, the bounding box is highlighted, which helps in identifying any missed vehicles.
https://github.com/user-attachments/assets/a0c47f52-f53c-41e8-b216-f17174b6b1ed
------------
## MQTT messages.
You can receive MQTT messages locally at localhost:1883, the default setting. Messages are printed to the terminal.
When connected to the internet, you can send MQTT messages to any broker you choose, such as broker.hivemq.com:1883.
The app only sends messages when the MQTT_ON setting is set to true. The refresh rate, in seconds, is determined by MESSAGE_TIME.
At midnight, all cumulative counts are reset.
You can also follow the messages in a web browser. To do so, enter the port number after the IP address of your Raspberry Pi.
------------
## Preview.
If your Raspberry Pi is connected to the internet, you can view live footage in a browser.
Simply combine the Raspberry Pi’s IP address with the MJPEG_PORT number specified in the settings to access the camera feed.
------------
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