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Object Detection Using OpenCV Python

Object Detection Using OpenCV Python

Object Detection Using OpenCV is a technology that falls under the broader domain of Computer Vision. This technology is capable of identifying objects that exist in images and videos and tracking them. Object Detection, also known as Object Recognition, has various applications like face detection, vehicle detection, pedestrian counting, self-driving vehicles, security systems, and a lot more.

Identification of all objects that exist in an image Filtration of the object that seeks attention In the following tutorial, we will understand how to perform Object Detection Using OpenCV in the Python programming language. We will create a basic object detection model using OpenCV in Python by the end of this tutorial.

Object Detection Using OpenCV Python
Object Detection Using OpenCV Python

complete Demo Video :- Click Here

Deep Learning for Object Detection Deep learning techniques have demonstrated state-of-the-art performance for various object detection tasks. Some commonly used approaches in deep learning for object detection include:

  • ImageAI
  • Single Shot Detectors
  • YOLO (You Only Look Once)
  • Region-based Convolutional Neural Networks

Understanding the ImageAI library Python provides a library designed to empower programmers and developers to build applications and systems with self-contained deep learning and computer vision capabilities using simple coding scripts. ImageAI includes a Python implementation of nearly all state-of-the-art deep learning algorithms such as , YOLOv3, and TinyYOLOv3.

For Object Detection Using OpenCV in Python, we can utilize popular machine learning libraries such as YOLOv3.

1st step: Install the following commands: (activate env)

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pip install opencv-python
pip install numpy

2nd step: Download the YOLO weight file.

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How To Run

Downloading and Setting Up a Project in PyCharm:

  1. Download the Zip File:
    • Visit the download link provided.
    • Click on the “Download” button to download the zip file.
  2. Extract the File, Copy Folder, and Paste on the Desktop:
    • Locate the downloaded zip file on your computer.
    • Right-click on the file and choose “Extract” or “Extract Here” to extract its contents.
    • You should now see a folder named “bms” after extraction.
    • Copy the folder.
    • Navigate to your desktop.
    • Right-click on the desktop and choose “Paste” to copy the folder onto your desktop.
  3. Open PyCharm:
    • Locate the PyCharm IDE on your computer and open it.
    • If you don’t have PyCharm installed, you can download it from the official JetBrains website and follow the installation instructions.

Screenshots

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Conclusion

ImageAI offers several offline APIs, including object detection, video detection, and object tracking APIs, which can be used without internet access. It utilizes pre-trained models and is easily customizable.

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