Pull Request for DL-Simplified 💡

Issue Title : Cassava Leaf Disease Classification #418

Info about the related issue (Aim of the project) : The aim of this project is to identify the defected leaf using image processing methods.
Name: Arijit De
GitHub ID: arijitde92
Email ID: arijitde2050@gmail.com
Idenitfy yourself: (Mention in which program you are contributing in. Eg. For a JWOC 2022 participant it's, JWOC Participant) SWOC 2024

Closes: #418

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

I have done exploratory data analysis (EDA) on the dataset, solved the class imbalance issue by under sampling the majority class, then used data augmentation while training to increase the sample size and reduce overfitting. I have trained four different models - EfficientNetB1, InceptionV3, DenseNet121 and MobileNetV2 to classify the images and did a comparison of the model performance in the test set.

Type of change ☑️

What sort of change have you made:

[x] Bug fix (non-breaking change which fixes an issue)
[x] 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? ⚙️

Compared model results on the test dataset and also created confusion matrix to see the multi-class performance of each model and how they are able to classify each class.

Checklist: ☑️

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

abhisheks008 / DL-Simplified

Added Cassava Leaf Disease Classification. #418 #451