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BarCode and QR Code Recognition #651

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Mikeyzgoat
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Related Issue

  • The main goal of this project is to classify images of barcodes, QR codes, and product labels using both traditional machine learning (SIFT + SVM) and deep learning (CNN). This classification can be useful for automated product identification, inventory management, and retail automation.

  • CodePeak 2025 Participant

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Closes: #618

Describe the add-ons or changes you've made

  1. Loaded and preprocessed the dataset (grayscale conversion, resizing, and normalization).
  2. Extracted features using the SIFT algorithm for the traditional ML approach.
  3. Trained an SVM classifier using the extracted features.
  4. Designed and trained a CNN model for classification.
  5. Compared model accuracies and visualized results using Matplotlib.

Type of change

What sort of change have you made:

  • Bug fix (non-breaking change which fixes an issue)
  • New feature (non-breaking change which adds functionality)
  • Code style update (formatting, local variables)
  • Breaking change (fix or feature that would cause existing functionality to not work as expected)
  • This change requires a documentation update

##How Has This Been Tested?

  • The models were trained and tested on the dataset using an 80-20 train-test split.
  • The SIFT + SVM model was evaluated using accuracy scores on the test set.
  • The CNN model was tested by computing the classification accuracy on unseen data.
  • Training and testing loss were monitored during CNN training to ensure proper convergence.
  • Sample predictions were manually verified to check model performance.

Checklist:

  • My code follows the guidelines of this project.
  • I have performed a self-review of my own code.
  • I have commented my code, particularly wherever it was hard to understand.
  • I have made corresponding changes to the documentation.
  • My changes generate no new warnings.
  • I have added things that prove my fix is effective or that my feature works.
  • Any dependent changes have been merged and published in downstream modules.

@Mikeyzgoat
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@prathimacode-hub here is the PR

@prathimacode-hub
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It's taking more time to open your PR as it includes lot of files in form of dataset. @Mikeyzgoat

@Mikeyzgoat
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No issues, take your time. Kindly update the same in codepeak if done. Thanks!

@prathimacode-hub prathimacode-hub changed the title Added model files, README.md. Dataset to be added manually! BarCode and QR Code Recognition Mar 24, 2025
@prathimacode-hub prathimacode-hub added the codepeak 25 This label is applicable for all CodePeak issues label Mar 24, 2025
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@prathimacode-hub prathimacode-hub left a comment

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Could you share me your project separately in form of repository, this pr isn't allowing me to review it fully? Based on feedback, u can apply the changes here in this PR if required. Thank You. @Mikeyzgoat

@Mikeyzgoat
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Sure, I ll send it by EOD

@Mikeyzgoat
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@prathimacode-hub PFB the repo without dataset, just the file and readme

https://github.com/Mikeyzgoat/barcode

@prathimacode-hub
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Hi @Mikeyzgoat. I will see if I can do anything now to merge this PR. I was out of town since last 10 days. The website isn't updated yet still, awaiting for team to respond back..

@prathimacode-hub
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Your PR is approved..🤝🚀 @Mikeyzgoat

@prathimacode-hub prathimacode-hub merged commit 7aead37 into prathimacode-hub:main Apr 13, 2025
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@prathimacode-hub prathimacode-hub added Approved This PR is tagged when the solution is approved Easy This issue will be considered as Easy for CodePeak 2025. Points will be 5 labels Apr 13, 2025
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CodePeak 2025 : Barcode and QR Code Recognition
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