AI Generated Fruits and Real Fruits Classification using Image Processing

[AgrawalTitiksha]

Pull Request for DL-Simplified 💡

Issue Title : AI Generated Fruits and Real Fruits Classification using Image Processing

• Info about the related issue (Aim of the project) : The aim of this project to identify and predict the real fruits and AI generated fruits using Image Processing methods.
• Name: Titiksha Agrawal
• GitHub ID: 117917014
• Email ID: agrawaltn2311@gmail.com
• Idenitfy yourself: (Mention in which program you are contributing in. Eg. For a JWOC 2022 participant it's, JWOC Participant) SWOC 2024 contributor

Closes: #416

Describe the add-ons or changes you've made 📃

As per the problem statement, the project aims to classify whether an image is Real or generated by AI.
The dataset provide for same consisted of 302 images in total.
After loading the dataset, extracting its features, resizing, reshaping and preprocessing it we trained our machine learning and deep learning models and calculated their accuracy and cross verified it by prediction also.
Following are the model we used :
Principle Component Analysis (PCA)
Linear Discriminant Analysis (LDA)
Support Vector Machine (SVM) (All the three kernel viz., linear, poly and RBF)
CNN (VGG16)
CNN (ResNet)
The accuracy percentage of our models was very satisfying (all nearly about 95% -100% accurate) and also the predictions were accurate.

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? ⚙️

Describe how it has been tested
Describe how have you verified the changes made

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.

[github-actions]

Our team will soon review your PR. Thanks @AgrawalTitiksha :)

[abhisheks008]

Please add the README.md file. Follow the README template for creating that, https://github.com/abhisheks008/DL-Simplified/blob/main/.github/readme_template.md

[abhisheks008]

Hi @AgrawalTitiksha this is the project structure please follow it.

Project Name
- Dataset
  - README.md (Put the URL of the dataset incase of multiple datapoints) / dataset.csv
- Images
  - Img1.png
  - Img2.png
  - Img3.png
- Model
  - project_name.ipynb
  - README.md (Follow the README template given in the previous comment)
- requirements.txt

Please update your project according to the project structure. Put the main README.md file inside the Model folder.

@AgrawalTitiksha

[abhisheks008]

Approved. Good work!
@AgrawalTitiksha