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https://github.com/pageauc/speed-camera

A Unix, Windows, Raspberry Pi Object Speed Camera using python3, opencv, video streaming, motion tracking. Includes a Standalone Web Server , Image Search using opencv template match and a whiptail Admin Menu Interface Includes picam and webcam Plugins for motion track security camera configuration including rclone sync scripts.
https://github.com/pageauc/speed-camera

matplotlib-pyplot motion-tracking moving openalpr opencv picamera2 python raspberry-pi-computer road rpi-camera speed-cam sqlite3 traffic unix vehicle video-streaming webcam-capture webserver whiptail-menu windows

Last synced: 9 days ago
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A Unix, Windows, Raspberry Pi Object Speed Camera using python3, opencv, video streaming, motion tracking. Includes a Standalone Web Server , Image Search using opencv template match and a whiptail Admin Menu Interface Includes picam and webcam Plugins for motion track security camera configuration including rclone sync scripts.

Awesome Lists containing this project

README 

        
## SPEED CAMERA - Object Motion Tracker [![Mentioned in Awesome ](https://awesome.re/mentioned-badge.svg)](https://github.com/thibmaek/awesome-raspberry-pi)

#### Raspberry Pi, Unix Disto's and Windows Speed Camera Using python3, openCV, RPI camera module, USB Cam or IP/RTSP Cam

#### For Details See [Program Features](https://github.com/pageauc/speed-camera/wiki/Program-Description#program-features), [Wiki Instructions](https://github.com/pageauc/speed-camera/wiki) and [YouTube Videos](https://github.com/pageauc/speed-camera#reference-links).



***Note re Bullseye***     

speed-cam.py will run using pi camera with libcamera, picamera2 under Raspberry Pi OS Bullseye, Bookworm,and later. Usbcam and IP/RTSP cameras

 are also supported. For picamera library support (on Bullseye only) Run ***sudo raspi-config***, Interface Options, then enable Legacy Camera option and Reboot.



### RPI Quick Install or Upgrade   

***IMPORTANT*** - A raspbian **sudo apt-get update** and **sudo apt-get upgrade** will **NOT** be performed as part of   

**speed-install.sh** so it is highly recommended you run these prior to install

to ensure your system is up-to-date.     



#### Step 1

Press GitHub copy icon on right side of code box below.  Copied! will be displayed.   



    curl -L https://raw.github.com/pageauc/speed-camera/master/source/speed-install.sh | bash



#### Step 2

On RPI putty SSH or terminal session right click, select paste then Enter to Download and Run **speed-install.sh** script.  



To get started, see Instructions at the end of the install script. Initial default config.py setting is CALIBRATE_ON=True.

You may also need to Align Camera using config.py ALIGN_CAM_ON=True setting.  Once calibration is complete set CALIBRATE_ON=False



### Mac or Windows Systems

See [Windows 10/11 or Apple Mac Docker Install Quick Start](https://github.com/pageauc/speed-camera#docker-install-quick-start)    

or [Windows or Unix Distro Installs without Docker](https://github.com/pageauc/speed-camera#windows-or-non-rpi-unix-installs)



### Program Description   

This project can run on a Raspberry Pi, Windows, Unix Distro computer.

It is written in python3 and uses openCV to detect and track the x,y coordinates of the 

largest moving object in the camera view above a minimum pixel area and calculates speed based on calibration settings.



User variables are stored in the [***config.py***](https://github.com/pageauc/speed-camera/blob/master/source/config.py) file.

Motion detection is restricted between ***MO_CROP_Y_UPPER***, ***MO_CROP_Y_LOWER***, ***MO_CROP_X_LEFT***, ***MO_CROP_X_RIGHT*** variables  (road or area of interest).

***MO_CROP_AUTO_ON*** = ***True*** overrides manual settings and will Auto calculate a rough crop area based on image size.

Motion Tracking is controlled by the ***MO_TRACK_EVENT_COUNT*** variable in config.py.  This sets the number of track events and 

the track length in pixels.  This may need to be tuned for camera view, cpu speed, etc. 

Speed is calculated based on ***CAL_OBJ_PX_*** and ***CAL_OBJ_MM_*** variables for L2R and R2L motion direction. A video stream frame image will be

captured and saved in ***media/images*** dated subfolders (optional) per variable ***IM_SUBDIR_MAX_FILES*** = ***2000*** 

For variable settings details see [config.py file](https://github.com/pageauc/speed-camera/blob/master/source/config.py). 



If ***LOG_DATA_TO_CSV*** = ***True*** then a ***speed-cam.csv*** file will be created/updated with event data stored in

CSV (Comma Separated Values) format. This can be imported into a spreadsheet, database, Etc program for further processing.

Release 8.9 adds a **sqlite3** database to store speed data. Default is ***data/speed_cam.db*** with data in the ***speed*** table.

Database setting can be managed from config.py.  Database is automatically created from config.py settings. For more

details see [How to Manage Sqlite3 Database](https://github.com/pageauc/speed-camera/wiki/How-to-Manage-Sqlite3-Database)



### Admin, Reports, Graphs and Utilities scripts

  

* [***menubox.sh***](https://github.com/pageauc/speed-camera/wiki/Admin-and-Settings#manage-settings-using-menuboxsh)

script is a whiptail menu system to allow easier management of program settings and operation.    

* [***speed-cam.py***](https://github.com/pageauc/speed-camera/wiki/How-to-Run)

View operation and log messages in real time in terminal session. Can be used to monitor, troubleshoot and tune speed camera (see config.py for speed-cam.py settings)   

* [***speed-cam.sh***](https://github.com/pageauc/speed-camera/tree/master/source/supervisor)

This bash script uses supervisorctl to manage start, stop, status, Etc of speed-cam.py Configured to autostart eg due to interruption of RTSP stream. 

See conf files in supervisor folder for details. Note: you must run ***./speed-cam.sh*** ***install*** to initialize symbolic links to /etc/supervisor/conf.d folder. 

Stop running any speed-cam and/or websever processes before running ***./speed-cam.sh*** ***start*** 

* [***speed-web.py***](https://github.com/pageauc/speed-camera/wiki/How-to-View-Data#how-to-view-images-and-or-data-from-a-web-browser)

Allows viewing images, video and/or data from a web browser. This will display web server messages. (see config.py for speed-web.py settings)   

* [***speed-web.sh***](https://github.com/pageauc/speed-camera/tree/master/source/supervisor)

This bash script uses supervisorctl to manage start, stop, status, Etc of speed-web.py. Configured to restart eg due to interruption 

See conf files in supervisor folder for details. Note: you must run ***./speed-web.sh*** ***install*** to initialize symbolic links to /etc/supervisor/conf.d folder. 

Stop running any speed-cam and/or websever processes before running ***./speed-web.sh*** ***start*** 

* [***rclone***](https://github.com/pageauc/speed-camera/wiki/Manage-rclone-Remote-Storage-File-Transfer)

Manage settings and setup for optional remote file sync to a remote storage service like google drive, DropBox and many others.   

* [***sql-make-graph-count-totals.py***](https://github.com/pageauc/speed-camera/wiki/How-to-Generate-Speed-Camera-Graphs#sql-make-graph-count-totalspy) Query sqlite database and Generate one or more matplotlib graph images and save to media/graphs folder.

Graphs display counts by hour, day or month for specfied previous days and speed over. Multiple reports can be managed from

the config.py ***GRAPH_RUN_LIST*** variable under matplotlib image settings section.       

* [***sql-make-graph-speed-ave.py***](https://github.com/pageauc/speed-camera/wiki/How-to-Generate-Speed-Camera-Graphs#sql-make-graph-speed-avepy) Query sqlite database and Generate one or more matplotlib graph images and save to media/graphs folder.

Graphs display Average Speed by hour, day or month for specfied previous days and speed over. Multiple reports can be managed from

the config.py ***GRAPH_RUN_LIST*** variable under matplotlib image settings section.    

* [***sql-speed_gt.py***](https://github.com/pageauc/speed-camera/wiki/How-to-Generate-Speed-Camera-Graphs#sql-speed_gtpy) Query sqlite database and Generate html formatted report with links to images and save to media/reports folder.

Can accept parameters or will prompt user if run from console with no parameters

* [***makehtml.py***](https://github.com/pageauc/speed-camera/wiki/How-to-View-Data#view-combined-imagedata-html-pages-on-a-web-browser)

Creates html files that combine csv and image data for easier viewing from a web browser and saved to media/html folder.    

* [***speed-search.py***](https://github.com/pageauc/rpi-speed-camera/wiki/How-to-Run-speed-search.py)

allows searching for similar target object images using opencv template matching.  Results save to media/search folder.    

* [***alpr-speed.py***](https://github.com/pageauc/speed-camera/wiki/alpr-speed.py---Process-speed-images-with-OPENALPR-Automatic-License-Plate-Reader)

This is a demo that processes existing speed camera images with a front or back view of vehicle using [OPENALPR](https://github.com/openalpr/openalpr)

License plate reader. Output is saved to media/alpr folder. For installation, Settings and Run details see

[ALPR Wiki Documentaion](https://github.com/pageauc/speed-camera/wiki/alpr-speed.py---Process-speed-images-with-OPENALPR-Automatic-License-Plate-Reader)       



### Reference Links

* YouTube Tutorial Video https://www.youtube.com/watch?v=n2WT3Qb0SIU

* YouTube Speed Lapse Video https://youtu.be/-xdB_x_CbC8

* YouTube Speed Camera Video https://youtu.be/eRi50BbJUro

* YouTube motion-track video https://youtu.be/09JS7twPBsQ  

* [How to Build a Cheap Homemade Speed Camera](https://mass.streetsblog.org/2021/02/26/how-to-build-a-homemade-speed-camera/)  

* Speed Camera RPI Forum post https://www.raspberrypi.org/forums/viewtopic.php?p=1004150#p1004150

* YouTube Channel https://www.youtube.com/user/pageaucp 

* Speed Camera GitHub Repo https://github.com/pageauc/speed-camera      



### Requirements

[***Raspberry Pi computer***](https://www.raspberrypi.org/documentation/setup/) and a [***RPI camera module installed***](https://www.raspberrypi.org/documentation/usage/camera/)

or USB Camera plugged in. Make sure hardware is tested and works. Most [RPI models](https://www.raspberrypi.org/products/) will work OK. 

A quad core RPI will greatly improve performance due to threading. A recent version of 

[Raspbian operating system](https://www.raspberrypi.org/downloads/raspbian/) is Recommended.   

or  

***MS Windows or Unix distro*** computer with a USB Web Camera plugged in and a

[recent version of python installed](https://www.python.org/downloads/)

For Details See [***Wiki details***](https://github.com/pageauc/speed-camera/wiki/Prerequisites-and-Install#windows-or-non-rpi-unix-installs).



It is recommended you upgrade to OpenCV version 3.x.x  For Easy compile of opencv 3.4.2 from source 

See https://github.com/pageauc/opencv3-setup



### Windows or Non RPI Unix Installs

For Windows or Unix computer platforms (non RPI or Debian) ensure you have the most

up-to-date python version. For Download and Install [python](https://www.python.org/downloads) and [Opencv](https://docs.opencv.org/4.x/d5/de5/tutorial_py_setup_in_windows.html)    



The latest python3 versions includes numpy and recent opencv version that is required to run this code. 

You will also need a USB web cam installed and working. 

To install this program access the GitHub project page at https://github.com/pageauc/speed-camera

Select the ***green Clone or download*** button. The files will be cloned or zipped

to a speed-camera folder. You can run the code from python IDLE application (recommended), GUI desktop

or command prompt terminal window. Note bash .sh shell scripts will not work with windows unless 

special support for bash is installed for windows Eg http://win-bash.sourceforge.net/  http://www.cygwin.com/

***Note:*** I have Not tested these.   



### Docker Install Quick Start

speed camera supports a docker installation on    

Apple Macintosh per [System requirements and Instructions](https://docs.docker.com/desktop/mac/install/)    

and      

Microsoft Windows 10/11 64 bit with BIOS Virtualization enabled

and [Microsoft Windows Subsystem for Linux WSL 2](https://docs.microsoft.com/en-us/windows/wsl/install) 

per [System requirements and Instructions](https://docs.docker.com/desktop/windows/install/).   



1. Download and install [Docker Desktop](https://www.docker.com/get-started) for your System

1. Clone the GitHub [Speed Camera repository](https://github.com/pageauc/speed-camera) using green Clone button (top right)

1. Run [docker-compose up](https://docs.docker.com/compose/reference/up/) from the directory you cloned the repo into.

1. The Docker container will likely exit because it is using a default config.

1. Edit the configuration file @ `config/config.py`

1. Run [docker-compose up](https://docs.docker.com/compose/reference/up/) per documentation

1. Run [docker build](https://docs.docker.com/engine/reference/commandline/build/) command locally to get a fresh image.

 

### Raspberry pi Manual Install or Upgrade   

From logged in RPI SSH session or console terminal perform the following. Allows you to review install code before running



    cd ~

    wget https://raw.github.com/pageauc/speed-camera/master/source/speed-install.sh

    more speed-install.sh       # You can review code if you wish

    chmod +x speed-install.sh

    ./speed-install.sh  # runs install script.

    

### Run to view verbose logging 



    cd ~/speed-camera    

    ./speed-cam.py

    

See [***How to Run***](https://github.com/pageauc/speed-camera/wiki/How-to-Run) speed-cam.py wiki section



***IMPORTANT*** Speed Camera will start in ***CALIBRATE_ON*** = ***True*** Mode.    

Review settings in ***config.py*** file and edit variables with nano as required.

You will need to perform a calibration to set the correct value for config.py ***CAL_OBJ_PX_*** and ***CAL_OBJ_MM_*** for

L2R and R2L directions. The variables are based on the distance from camera to objects being measured for speed.

See [***Calibration Procedure***](https://github.com/pageauc/speed-camera/wiki/Calibrate-Camera-for-Distance) for more details.     



The config.py motion tracking variable called ***track_counter*** = can be adjusted for your system and opencv version.

Default is 5 but a quad core RPI3 and latest opencv version eg 3.4.2 can be 10-15 or possibly greater.  This will

require monitoring the verbose log messages in order to fine tune.

    

### Run menubox.sh 



    cd ~/speed-camera

    ./menubox.sh



Admin speed-camera Easier using menubox.sh (Once calibrated and/or testing complete) 

 

![menubox main menu](https://github.com/pageauc/speed-camera/blob/master/assets/menubox.png)     



View speed-cam data and trends from web browser per sample screen shots. These can be generated 

from Menubox.sh menu pick or by running scripts from console or via crontab schedule.



![Speed Camera GRAPHS Folder Web Page](https://github.com/pageauc/speed-camera/blob/master/assets/speed_web_graphs.png)  

![Speed Camera REPORTS Folder Web Page](https://github.com/pageauc/speed-camera/blob/master/assets/speed_web_reports.png)   

![Speed Camera HTML Folder Web Page](https://github.com/pageauc/speed-camera/blob/master/assets/speed_web_html.png)    



You can view recent or historical images directly from the speed web browser page.  These are dynamically created

and show up-to-date images.  Press the web page refresh button to update display 

![Speed Camera RECENT Folder Web Page](https://github.com/pageauc/speed-camera/blob/master/assets/speed_web_recent.png)   

![Speed Camera IMAGES Folder Web Page](https://github.com/pageauc/speed-camera/blob/master/assets/speed_web_images.png)   



### Credits  

Some of this code is based on a YouTube tutorial by

Kyle Hounslow using C here https://www.youtube.com/watch?v=X6rPdRZzgjg



Thanks to Adrian Rosebrock jrosebr1 at http://www.pyimagesearch.com 

for the PiVideoStream Class code available on github at

https://github.com/jrosebr1/imutils/blob/master/imutils/video/pivideostream.py

  

Have Fun   

Claude Pageau    

YouTube Channel https://www.youtube.com/user/pageaucp   

GitHub Repo https://github.com/pageauc