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A DL model for extracting text and identifying symbols from product labels using OCR and YOLO v5 streamlines the collection of product information and assists with quality control.

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PavanSETTEM-003/Automated-Text-and-Object-Detection-with-Deep-Learning

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Automated-Text-and-Object-Detection-with-Deep-Learning

The goal of this project is to automate the process of extracting text and symbols from product label images using Optical Character Recognition (OCR) and object detection methods. The input for the project will be product label images, and the output will be the extracted text and symbols present on the label. The extracted information will be useful in various applications such as creating a product database, adding products to an e-commerce website or analyzing the contents of a product label.

This project will help in reducing the amount of manual work required in organizing and analyzing product information.A solution for extracting text and identifying symbols from product labels using OCR and YOLO v5 object detection streamlines the process of collecting product information and assists with quality control.

The following steps will be implemented in the project :

  • Recognition of text on the product label using OCR (Tesseract OCR).
  • Detection of symbols on the product label using object detection methods(YOLO v5).
  • Ordering of the symbols based on the location on the label.

It is recommended to review the project report to gain a better understanding of the approach and code used in this project.

Colab link : https://colab.research.google.com/drive/16TDbVnkjFMDhHMc9fVOLqZi76v5YAF_S?usp=share_link
Drive link : https://drive.google.com/drive/folders/1MiA3qm1lUxggOpTMbSXt2sX9cdpOTNnL?usp=share_link

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A DL model for extracting text and identifying symbols from product labels using OCR and YOLO v5 streamlines the collection of product information and assists with quality control.

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