Welcome to this small tutorial on object detection using OpenCV and the MobileNet deep learning model. This repository provides a step-by-step guide to help you understand and implement object detection and text recognition in images. It's designed as a tutorial for learners to get started quickly.
To install and use this project, you can follow these steps:
- Clone the Repository
bash git clone https://github.com/chaymabh/Object-Detection-OpenCV-Tutorial.git - Navigate to the Project Directory
bash cd Object-Detection-OpenCV-Tutorial - MobileNet - Download the MobileNet model for object detection.
- OpenCV - Install OpenCV library for image processing and computer vision.
- Tensorflow - Install Tensorflow for deep learning capabilities.
- easyocr - Install the easyocr library for text recognition.
Follow these steps to go through this tutorial:
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Ensure you have all the dependencies installed as mentioned in the "Installation" section.
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Use the provided Jupyter Notebook, "object_detection.ipynb," which contains a step-by-step tutorial on object detection and text recognition in images.
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The notebook explains each concept and provides code examples for hands-on learning.
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Feel free to modify and experiment with the code to deepen your understanding.
This project is licensed under the MIT License. See the LICENSE file for details.
