Real Time Object Detection OpenCV Python With Source Code

Real-Time Object Detection OpenCV Python – The task of executing real-time object detection with quick inference while retaining a base level of accuracy is known as real-time object detection.

Importance of Real-Time Object Detection Python OpenCV

Object detection is closely related to other similar computer vision techniques like image recognition and image segmentation in that it aids in the comprehension and analysis of situations in photos and video.

Real-Time Object Detection In Python: Project Details and Technology

Project Name:Real-Time Object Detection Project In Python With Source Code
AbstractObject Detection Python OpenCV – The computer vision technique of object detection is used to locate instances of things in photos or movies.
Language/s Used:Python Deep Learning
Python version (Recommended):3.8/3.9
Type:Desktop Application
Developer:Source Code Hero
Real-Time Object Detection Project In Python – Project Information

Real-Time Object Detection OpenCV Python: About the project

This Real-Time Object Detection OpenCV Python script is a small experimental tool to detect common objects (COCO) simply with your built-in webcam using Python OpenCV.

It makes use of the readNet method in opencv as well as the external yolov3-tiny model (which can be upgraded to the full-sized model).

The readNet function in Opencv only operates on the CPU (not the GPU), is quite resource intensive, and thus is not suitable for large AI applications.

Using pretrained yolov3 models, the Object Detection OpenCV Python provides an image and video object detection classifier.

The yolov3 models are from the official yolov3 paper from 2018. Darknet provided the yolov3 implementation. Also included in this project is the ability to perform real-time classification using the webcam.

This Real-Time Object Detection In Python also includes a downloadable Python Project With Source Code for free, just find the downloadable source code below and click to start downloading.

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To start executing a Real-Time Object Detection OpenCV Python With Source Code, make sure that you have installed Python on your computer.

Real-Time Object Detection OpenCV Python With Source Code: Steps on how to run the project

Time needed: 5 minutes

These are the steps on how to run Real-Time Object Detection OpenCV Python With Source Code

  • Step 1: Download Source Code

    First, download the provided source code below.
    object detection download source code

  • Step 2: Extract File

    Next, after the download is finished extract the zip file.
    object detection extract file

  • Step 3: Import the project to your PyCharm IDE.

    Next, import the source code you’ve downloaded to your PyCharm IDE.
    object detection open project

  • Step 4: Install all Libraries.

    Next, install all libraries given below.
    object detection import libraries

  • Step 5: Open cmd.

    Next, click the folder directory of the project and type cmd.
    object detection open cmd

  • Step 6: Run Project.

    last, run the project with the command “py”
    object detection run project

Download the Source Code below


This project implements an image and video object detection classifier using pretrained yolov3 models. The yolov3 models are taken from the official yolov3 paper which was released in 2018.

The yolov3 implementation is from darknet. Also, this project implements an option to perform classification real-time using the webcam.


If you have any questions or suggestions about Real-Time Object Detection OpenCV Python With Source Code, please feel free to leave a comment below.

2 thoughts on “Real Time Object Detection OpenCV Python With Source Code”

  1. I have always getting the error in line 13 which is

    output_layers = [layers_names[i[0] – 1] for i in net.getUnconnectOutLayers()]
    Can you help me with that


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