Image Processing using OpenCV

Description ✍️

• Detecting the Red and Blue Objects within the Given Frame and Making a Line Between Them
• This repository contains Python code that utilizes OpenCV for detecting and tracking orange and blue objects within a video.
• The code identifies the largest contours of the red and blue objects, draws rectangles around them, and connects them with a line.

Ideation

• The Idea to make this project was from the Company 'Kshatra Infotech Pvt. Ltd.'

Authors 👑

• @Fardin-Multani😎

Demo 🖼️

Installation ⬇️

Dependencies

1. python == 3.10.9
2. opencv-python == 4.6.0
3. numpy == 1.25.0

⚠️ Note: These were the dependencies on which this project was done. It may or may not work as efficiently/correctly on other versions

Installing dependencies

Creating the conda environment:

conda create -n <Environment_name> python=3.10.9

Activating the conda environment:

conda activate <Environment_name>

Installing opencv

conda install -c conda-forge opencv==4.6.0

Installing numpy

conda install -c conda-forge numpy==1.25.0

or you can also refer environment.yml 🤝

(!to run the environment.yml directly here is the command)

conda env update --name <Environment_name> --file <Path/To>environment.yml --prune

Usage/Examples 👨‍💻

• It is used to detect orange and blue objects from the image/video or live camera its parts or chunks of codes can be used in various places as per requirement 😊

• Every line or chunks are explained in code along with comments 🫡

1. Run the main script:

   ⚠️After activating the environment only

   python <pathto/>main_program.py
   

2. The script will open the webcam and start processing the video stream in real-time. It will detect and track red and blue objects, drawing rectangles around them and connecting them with a line.

3. Press 'ESC' to exit the application.

Acknowledgements ®️

• OpenCV - Open Source Computer Vision Library
• NumPy - Numerical Computing Library

Customization ⚙️

• If you want to find the distance between this to color object you can add the distance formula in it.

• You can adjust the color ranges and other parameters in the main_program.py to fine-tune the object detection based on your specific requirements.

License 🪪

This project is licensed under the MIT License

Conclusion✔️

In this project, we have explored image processing techniques using OpenCV to detect and track orange and blue objects. The code utilizes color masking and contour analysis to identify the largest contours of the objects, draws rectangles around them, and connects them with a line. This can be useful in various applications such as object tracking, computer vision, and robotics. Feel free to explore the code and adapt it to suit your specific needs.