[Project Addition] : Pharmaceutical Drugs and Vitamins Images Detection

[aaradhyasinghgaur]

Pull Request for DL-Simplified 💡

Issue Title : Pharmaceutical Drugs and Vitamins Images Detection

• Info about the related issue (Aim of the project) : The dataset includes images of popular pharmaceutical drugs and vitamins in the Philippines. This is dataset can be used for classifying drug images using CNN and transfer learning. Currently, there are ten available classes of pill images.
• Name: Aaradhya Singh
• GitHub ID: https://github.com/kyra-09
• Email ID: [email protected]
• Idenitfy yourself: (Mention in which program you are contributing in. Eg. For a JWOC 2022 participant it's, JWOC Participant) - GSSOC-2024 Contributor

Closes: #721

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

1. Utilizing 5 models such as DenseNet121 , Xception, VGG16, ResNet50, and InceptionV3 for image classification.
2. Applying data augmentation (rotation, zooming, flipping, shearing, brightness) to enhance dataset robustness.
3. Comparing model performance using accuracy scores, loss/accuracy graphs, and confusion matrices.
4. Conducting EDA for dataset insights, including image distribution, quality, class imbalances, and sample visualization.
5. Documening the process in a comprehensive README file.

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 @kyra-09 :)

[aaradhyasinghgaur]

@abhisheks008 kindly review my pr.

[abhisheks008]

Approved @kyra-09