Detection of Skin Lesions using a YOLO-based Detection Network

[mermalade0325]

This pull request aims to address the problem of detecting skin lesions within the ISIC 2017/2018 dataset. The primary goal is to develop a robust detection and classification network that can accurately identify lesions in medical images, ensuring each detection has a minimum Intersection Over Union (IoU) of 0.8 on the test set, thus achieving a suitable level of accuracy for classification. The project utilizes a YOLO-based detection network (YOLOv7).

Problem Statement
Skin cancer detection relies on identifying lesions accurately in medical images. This project contributes by building a deep learning model focused on detecting lesion locations without classifying lesion types. The main goals are:

• Localization: Detect lesion locations with high accuracy.
• Performance Metrics: Achieve a minimum IoU of 0.8 for lesion detection on the test set.

Files and Structure

The project is organized into the following files:

• modules.py: Contains core components of the model, structured as classes or functions for easy reuse and extension.
• dataset.py: Implements the data loader for the ISIC dataset, with preprocessing functions.
• train.py: Contains training, validation, and testing routines. It imports the model from modules.py and data loader from dataset.py. Training metrics, such as loss, are plotted and saved to help track model performance.
• predict.py: Shows how to load the trained model for predictions. Outputs include visualizations with bounding boxes around detected lesions.
• README.md: Documents the project setup, usage, and module descriptions.

Dataset

Regarding the data downloaded from ISIC, it should be organised as follows, with labels generated from dataset.py:

An appendix in the README file links to the ISIC dataset for reference.

As requested by tutors, this is a new Pull Request submitted from the correct branch.

[hanemma7moud]

@shaivikaaaa @gayanku

[shaivikaaaa]

Hi @mermalade0325
I believe you already have 1 PR - which is open and have been provided Feedback for
I am not sure why is there another one

[mermalade0325]

Hi @shaivikaaaa,
Tutors provided feedback on the other PR mentioning that I accidentally merged from my main instead of my topic_recognition branch. As per their feedback I made a new PR from the correct branch, and implemented all the edits they asked for on the read_me, results images, PR details etc. on here! Hope this is okay!

[gayanku]

Duplicate is #188. Please fix 188 as per feedback required section.