TrackBar OpenCV Python With Source Code
The TrackBar OpenCV Python was developed using Python OpenCV, Trackbar is a GUI element that lets the user select a specific color value within a range of values by sliding a slider linearly.
It’s similar to scrolling but it limits the user to select a specific value with its minimum and maximum limits.
What is OpenCV?
OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library.
OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products.
A trackbar in OpenCV provides cv2.createTrackbar() function, to read the current position of the trackbar slider you can use cv2.getTrackbarPos() function to change the position of the trackbar use cv2.setTrackbarPos().
In this Python OpenCV Project also includes a downloadable Python Project With Source Code for free, just find the downloadable source code below and click to start downloading.
By the way, if you are new to Python programming and don’t know what Python IDE to use, I have here a list of the Best Python IDE for Windows, Linux, Mac OS that will suit you.
I also have here How to Download and Install the Latest Version of Python on Windows.
To start executing TrackBar OpenCV Python With Source Code, make sure that you have installed Python 3.9 and PyCharm on your computer.
TrackBar OpenCV Python With Source Code: Steps on how to run the project
Time needed: 5 minutes
These are the steps on how to run TrackBar OpenCV Python With Source Code
- Step 1: Download the given source code below.
First, download the given source code below and unzip the source code.
- Step 2: Import the project to your PyCharm IDE.
Next, import the source code you’ve download to your PyCharm IDE.
- Step 3: Run the project.
last, run the project with the command “py main.py”
Installed Libraries
import cv2 as cv import numpy as np from matplotlib import pyplot as plt
Complete Source Code
import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt
def change(x):
# print(x)
pass
def trackbar():
img = np.zeros((300, 512, 3), np.uint8)
cv.namedWindow("image")
cv.createTrackbar('B', 'image', 0, 255, change)
cv.createTrackbar('G', 'image', 0, 255, change)
cv.createTrackbar('R', 'image', 0, 255, change)
switch = '0: OFF\n 1: ON'
cv.createTrackbar(switch, 'image', 0, 1, change)
while True:
cv.imshow("image", img)
k = cv.waitKey(1) & 0xFF
if k == 27:
break
b = cv.getTrackbarPos('B', 'image')
g = cv.getTrackbarPos('G', 'image')
r = cv.getTrackbarPos('R', 'image')
s = cv.getTrackbarPos(switch, 'image')
if s == 0:
img[:] = 0
else:
img[:] = [b, g, r]
cv.destroyAllWindows()
if __name__ == '__main__':
trackbar()
Output
Download the Source Code below
Anyway, if you want to level up your programming knowledge, especially Python OpenCV, try this new article I’ve made for you Best OpenCV Projects With Source Code For Beginners.
Summary
Trackbar is a GUI element that let the user to select a specific color value within a range of values by sliding a slider linearly.
It’s similar to scrolling but it limits the user to select a specific value with its minimum and maximum limits.
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Inquiries
If you have any questions or suggestions about TrackBar OpenCV Python With Source Code, please feel free to leave a comment below.
Frequently Asked Questions
How do OpenCV trackbars work?
cv2.createTrackbar(name, window, value, max, callback) adds a slider to a named window. Read the current slider value with cv2.getTrackbarPos. Common use: tune HSV color thresholds for object detection in real time, adjust Canny edge thresholds interactively, scale blur kernel size. Essential for prototyping any vision filter.
What OpenCV version do I need to run this project?
Use OpenCV 4.5 or newer. Install with pip install opencv-python (the standard build for desktop projects). Some projects also need opencv-contrib-python which adds extra modules (SIFT, SURF, advanced trackers). The pip install command auto-downloads pre-built wheels so no compilation is needed on Windows, Mac, or Linux.
How do I install OpenCV and the dependencies for this project?
Open a terminal, then: pip install opencv-python numpy. Most projects also need one of these: mediapipe (for face / hand / pose detection), pyzbar (for barcode and QR), pytesseract (for OCR), Pillow (for image manipulation), pyautogui (for screen capture). Pin Python version to 3.10, 3.11, or 3.12 for maximum library compatibility.
Can I use this OpenCV project for a BSIT or CSE capstone?
Yes, but extend it. A single OpenCV demo (face detection alone, lane detection alone) is too narrow for full capstone scope. Combine it with a real domain (attendance system using face recognition, traffic monitoring system using lane detection, fitness coach app using pose detection), add a database to log results, build a simple Tkinter or Streamlit UI, and document the whole pipeline in Chapter 3.
Why am I getting AttributeError or ImportError when running this code?
Three most common causes: (1) You installed opencv-python but the code needs opencv-contrib-python (extra modules like xfeatures2d). Reinstall with pip install opencv-contrib-python. (2) You are on Python 3.13 but some wheels (mediapipe) lag behind, downgrade to Python 3.11 or 3.12. (3) NumPy version mismatch, pin numpy to a version your other libraries support.
Where do I find more OpenCV and Machine Learning project ideas?
Browse our Machine Learning Projects hub for 23+ OpenCV demos with source code. For capstone-scale AI ideas (RAG, NLP, recommendation systems), see 100+ AI Capstone Project Ideas. For broader Python project ideas, our Python Projects library has 250+ working capstones.
Angel Jude Suarez
Full-Stack Developer at PIES IT Solution
Focuses on Python development, machine learning, and AI integration. Has built production AI systems including OpenAI Whisper integration for medical transcription and GPT-4o-powered diagnosis assistance. Strong background in pandas, scikit-learn, and TensorFlow.
Expertise: Python · PHP · Java · VB.NET · ASP.NET · Machine Learning · AI Integration · OpenCV · Django · CodeIgniter · View all posts by Angel Jude Suarez →