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Topic recognition #145

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larsmoan
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Detection and classification of skin lesions on the ISIC2017 dataset using YOLOV7 architecture

larsmoan and others added 30 commits October 5, 2023 17:02
… with yolo architecture, just missing the testset
@nathasha-naranpanawa
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This is an initial inspection, no action is required at this point

Difficulty: Normal

Readme: 
Poor

  • no insights/discussion/interpretation of results
  • no description about how the YOLOv7 algorithm works
  • no training/testing loss or accuracy(mAP) plots shown
  • no detection results shown in readme (some images are included in the reults folder)

Commit messages: 
OK

Code:

  • Only has Jupyter notebooks, does not have the file structure required
  • Uses an open source YOLOv7 implementation by someone else, with command line arguments
  • No hyperparameter tuning or attempts to improve performance

Functionality/Performance:

  • Classification accuracy is below 0.8 for all classes
  • No detection results shown/No IoU metrics shown

@larsmoan
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Thanks for the feedback, obviously a lot of stuff I didn't deliver on during the initial push. I have now done a series of changes, most related to the readme and documentation of the project. I hope this is sufficient.
When it comes to the structure of the project with filenames as model.py, train.pyy etc I find this difficult to implement given the fact that I use the yolov7 library. If I were to follow this rigid structure I would just add more unnecessary code, hope you understand my point of view on this.
Again thanks for the feedback.

@shakes76
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shakes76 commented Nov 20, 2023

Marking

Some parts marked as per content for due date

Good Practice (Design/Commenting, TF/Torch Usage)

Adequate design and implementation, YOLOv7 external implementation -3
Good spacing and comments
Header blocks missing -1

Recognition Problem

Solves problem
Driver Script present
File structure not present, needs to be in own folder -2
Shows Usage & Demo & Visualisation & Data usage, no detection results initially shown -2
Module present
Commenting
No Data leakage
Difficulty: Normal -5

Commit Log

Meaningful commit messages
Progressive commits used

Documentation

ReadMe good but missing refs -1
Model/technical explanation
Good Description and Comments
Markdown used and PDF submitted

Pull Request

Successful Pull Request (Working Algorithm Delivered on Time in Correct Branch)
No Feedback required
Request Description minimal -1

@shakes76 shakes76 added the invalid This doesn't seem right label Nov 20, 2023
@shakes76
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Cannot be merged as external implementation of YOLOv7, otherwise grade normally.

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3 participants