added crater detection model

[Kaibalya27]

Pull Request for PyVerse 💡

Requesting to submit a pull request to the PyVerse repository.

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Issue Title

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[Code Addition Request]: #749

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Info about the Related Issue

What's the goal of the project?
The goal of this project is to develop a highly accurate object detection model based on the YOLO architecture for detecting craters on the lunar surface. Accurate crater detection is vital for selecting potential landing sites for rovers and for conducting detailed lunar surface studies. By training the YOLO model on lunar images, the project aims to create a fast and reliable detection system that can handle variations in crater size, shape, and lighting conditions in Permanently Shadowed Regions (PSRs) of the moon.

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Name

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Kaibalya Mohapatra

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GitHub ID

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Kaibalya27

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Email ID

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kaibalyamohapatra27@gmail.com

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Identify Yourself

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GSSOC, HACKTOBERFEST

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Closes

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Closes: #749

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Describe the Add-ons or Changes You've Made

Model Enhancement

Integrated a YOLO-based model to improve the detection of lunar craters. This model is designed to detect craters of various sizes and shapes on the lunar surface, particularly in challenging low-light regions like Permanently Shadowed Regions (PSRs).

Data Augmentation

Added advanced data augmentation techniques, such as random brightness adjustments and rotations, to improve model robustness in detecting craters under different lighting conditions.

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Type of Change

Select the type of change:

• 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

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How Has This Been Tested?

The model has been tested using a dataset of rendered lunar surface images, with ground truth labels for crater locations.
The model was further tested on lunar images simulating low-light conditions in the Permanently Shadowed Regions (PSRs) to ensure it performs well in challenging environments.

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Checklist

Please confirm the following:

• 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.

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[Kaibalya27]

Hi @UTSAVS26, is there any problem?
this PR is not accepted yet?

[TheChaoticor]

please wait,we are fully packed with reviewing .We will approve it shortly