Final submission for OASIS 2D U-Net segmentation project

[tmthyngyn]

This pull request contains the final implementation and report for the COMP3710 recognition project: 2D U-Net for Multi Class Brain MRI Segmentation using the OASIS Dataset. The project implements a full segmentation pipeline including data preprocessing, model training, validation, and prediction using a 2D U-Net architecture in PyTorch. All code and documentation are complete, well-commented, and consistent with the required four-file structure.

[24msingh24]

This is an initial inspection, no action is required at this point

2D UNet – Prostate MRI Segmentation → Easy

Category		Marks	Comments
Algorithm solves the problem	5	5	Works as intended.
Implementation functions as intended	3	3	Implemented looks all completed.
Good design	1	1	UNet blocks and encoder-decoder modularity look good.
Commenting	1	1
Algorithm above Normal Difficulty	5	0
Algorithm is Hard difficulty	5	0	Easy
Section IV : Max mark 10 from 20	10

• Discussion: None provided. This is needed.

Suggestions/Notes:

• Good work.

[gayanku]

Marking

Good/OK/Fair Practice (Design/Commenting, TF/Torch Usage)
	Good design and implementation.
	Spacing and comments.
	Header blocks.
Recognition Problem
	Good solution to problem.
	Driver Script present.
	File structure present.
	Good Usage & Demo & Visualisation & Data usage.
	Module present.
	Commenting present.
	No Data leakage found.
	Difficulty : Easy. Easy. Unet 2D	-10
Commit Log
	Good Meaningful commit messages.
	Good Progressive commits.
Documentation
	Readme :Good.
	Model/technical explanation :Good.
	Description and Comments :Good.
	Markdown used. PDF NOT submitted.	-2
Pull Request
	Pull Request has problems.	-1
	No Feedback required.
	Request Description is good.
TOTAL		-13

Marked as per the due date and changes after which aren't necessarily allowed to contribute to grade for fairness.
Subject to approval from Shakes

[wangzhaomxy]

s4699147

[tmthyngyn]

A PDF was submitted on blackboard.