Building a Car Counter

Building a Car Counter with Python and OpenCV

This is a beginner computer vision project. It is the accompanying code for videos that can be found here:

• TikTok Vid
• YouTube Vid

This project is intended as a demonstration, and there will be no support.

Requirements

You need to install the following.

1. Python - Installation
2. OpenCV, Matplotlib

pip install opencv-python
pip install matplotlib

3. Detectron2 - Installation
4. This repository!

git clone https://github.com/eric-yim/building-a-car-counter.git

If you don't have a GPU for Object Detection

The object detection mechanism requires a GPU set up with appropriate drivers. If you don't have one set up, you can use google colab.

Then, instead of running the code on a webcam, you would instead run the code on a video file. You'll have to use colabs built in visualizer instead of cv2.imshow.

Running the Code

The main entry to the code is view_camera.py. There is a variable in the file called NAME_OF_CAMERA that you should edit. This can be the name of a video file like MY_FILE.mp4 or a webcam (be sure to put your video file in repository folder or use the absolute path). Your webcam maybe called something like /dev/video0 on Linux or "0" on Windows. Once that is set, you should be able to run the file.

Running the System

This opens the camera, runs the system, and shows a visualization on screen. Meanwhile, it appends counts to a file called totals.csv. Press "q" to exit.

python view_camera.py

Running only the Object Detector

You can also run only the Object Detector on the sample image provided.

python detector.py

You should get an image like this.

Displaying Results

There are sample counts stored in totals.csv. You can display them.

python analyze.py

You will get a display like this.

List of Files

1. aggregator.py - measures time increments for outputting counts
2. analyze.py - displays totals.csv using matplotlib
3. colors.py - a list of colors for visualizing tracked objects
4. counter.py - checks line crossing and keeps a count of tracked objects
5. detector.py - runs object detection on image
6. tracker.py - tracks objects
7. view_camera.py - main entry file to system

sample.png and totals.csv are samples and can be deleted once you have your own system running.