Topic recognition - #171

Open
KnowerSmyf wants to merge 79 commits into
shakes76:topic-recognitionfrom
KnowerSmyf:topic-recognition
Open

Topic recognition#171
KnowerSmyf wants to merge 79 commits into
shakes76:topic-recognitionfrom
KnowerSmyf:topic-recognition

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@KnowerSmyf

@KnowerSmyfKnowerSmyf commented Oct 26, 2023

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Implemented a 2D variant of the improved UNet architecture and used it to perform lesion skin boundary segmentation. I had an extension (hence the late submission), also I feel like I went pretty crazy with the commits... Sorry about that (:

@KnowerSmyf
Set up basic project skeleton
9fca4c3
@KnowerSmyf
created .gitignore to store data and model files
fe25335
@KnowerSmyf
Setup the UNet modules according to the paper
82802d5
@KnowerSmyf
Attempted to build the UNet according to paper...
9becad1
@KnowerSmyf
Implemented Encoder, changed UNet accordingly
597515b
@KnowerSmyf
Changed UNet Encoder input args
da0ebe4
@KnowerSmyf
Implemented upsampling module
241cbb7
@KnowerSmyf
Implemented Localisation module
c70f54a
@KnowerSmyf
Fixed afew bugs
5edc8b1
@KnowerSmyf
Worked on UNet + created Segmentation class
6f6ff64
@KnowerSmyf
Finished Unet + Segmentation
82d0e90
@KnowerSmyf
Cleaned up afew things
3cb04a7
@KnowerSmyf
Cleaned up the modules
d9f60b0
@KnowerSmyf
Made UNet 2D, setup Dataloader, added utils
171396a
@KnowerSmyf
Did some debugging on modules
3b364fe
@KnowerSmyf
Started implementing the training loop etc
a0ff43a
@KnowerSmyf
Realised this was the wrong spot...
1b3e31d
@KnowerSmyf
Switched from softmax to sigmoid UNet output
e465710
@KnowerSmyf
Implemented loader methods
66f6652
@KnowerSmyf
Fixed afew things
ea20f0c
@KnowerSmyf
Improved training loop
b431fce
@KnowerSmyf
Implemented a dice score method
78e3bde
@KnowerSmyf
set up my model testing
0e99346
@KnowerSmyf
started my predict.py file
c791103
@KnowerSmyf
committing a slurm script
d444b7a
@KnowerSmyf
fixed bug in dataset
0d0f302
@KnowerSmyf
modified ISICDataset __init__ method
efd6aab
@KnowerSmyf
added a check for inconsistencies in the DB
6f8b2f9
@KnowerSmyf
Put some inconsistency fixes and check in
6308bde
@KnowerSmyf
fixed check_consistency bug
662f1b3
@KnowerSmyf
Changed the threshold from 127.5 to 0.5 for binarizing the mask
ca6b114
@KnowerSmyf
The model is finally working, going to try a real training cycle
c0f75e7
@KnowerSmyf
forgot to declare 'no_improvement', fixed
7a171a8
@KnowerSmyf
fixed the error in the debugging random_split
296a12b
@KnowerSmyf
Using test partition in slurm script
8cc9427
@KnowerSmyf
Testing out validation and test batch size = 100
498f92c
@KnowerSmyf
The model works, time to train properly!
e82203c
@KnowerSmyf
Switched back to vgpu partition
051f27d
@KnowerSmyf
Gave the problem directory a meaningful name
a0d80de
@KnowerSmyf
Made the stoppage criteria less strict in training
1dda16a
@KnowerSmyf
deleted the old directory
d951222
@KnowerSmyf
Worked on my README file
856d8b8
@KnowerSmyf
Training again, lost a lot of data ):
e2f9ba6
@KnowerSmyf
created individual image and mask pre-processing
72b48cb
@KnowerSmyf
Added images
dc5ac4d
@KnowerSmyf
Added best_model.pth
4b321fa
@KnowerSmyf
Wrote the README file, finished the predict.py file
1ae7398
@KnowerSmyf
Removed debugging stuff
056988d
@KnowerSmyf
Improved the README file
7f30cbf
@KnowerSmyf
If the best_model.pth DNE execute train.py
76d6260
@KnowerSmyf
performance images
fa0eea2
@KnowerSmyf
Fixed afew README image naming bugs
dd27659
@KnowerSmyf

KnowerSmyf commented Oct 26, 2023

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Author

I'm new to github, I've tried like 3 pull requests... hopefully its all good

@wangzhaomxy

wangzhaomxy commented Nov 6, 2023•
edited
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Collaborator

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

  • Well organized files, but wrong readme.md place.
  • Algorithm solves the problem appropriately. Average Dice Coefficient in testing dataset: 0.7364, but no evidence was shown. Predicted Mask output is not good enough, just showing 25 epochs training result in readme, which seems not the best result.
  • Correctly using PyTorch to construct the Improved U-Net models and functions.
  • Good coding design.
  • Sufficient docstring and comment in the code, but need some references.
  • Easy difficulty problem, no higher difficulty marks.

@shakes76shakes76 added the Extension Extension approved label Nov 20, 2023
@shakes76

shakes76 commented Nov 20, 2023

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Owner

Marking

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

Adequate design and implementation
Good spacing and comments
Header blocks

Recognition Problem

Solves problem but poor performance from predicted mask shown -1
Driver Script present
File structure present
Shows Usage & Demo & Visualisation & Data usage, no training plots etc. -2
Module present
Commenting
No Data leakage
Difficulty: Easy -10

Commit Log

Meaningful commit messages
Progressive commits used

Documentation

ReadMe acceptable, no refs -1
Model/technical explanation minimal -1
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 commented Nov 20, 2023

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Owner

Please revert changes to repo README files for merging, does not affect grade only merge.

@shakes76shakes76 added the question Further information is requested label Nov 20, 2023
@wangzhaomxy

wangzhaomxy commented Nov 21, 2023

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Collaborator

No feedback attempt and no feedback marks lost.

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Labels

ExtensionExtension approvedImproved UNetquestionFurther information is requested

Projects

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Development

Successfully merging this pull request may close these issues.

4 participants

@KnowerSmyf@wangzhaomxy@shakes76@nathasha-naranpanawa
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try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
Topic recognition - #171
Open
KnowerSmyf wants to merge 79 commits into
shakes76:topic-recognitionfrom 
KnowerSmyf:topic-recognition
Open
Topic recognition#171
KnowerSmyf wants to merge 79 commits into
shakes76:topic-recognitionfrom 
KnowerSmyf:topic-recognition
Conversation
@KnowerSmyf
@KnowerSmyfKnowerSmyf
commented
Oct 26, 2023

Copy link


Copy Markdown

Implemented a 2D variant of the improved UNet architecture and used it to perform lesion skin boundary segmentation. I had an extension (hence the late submission), also I feel like I went pretty crazy with the commits... Sorry about that (:
@KnowerSmyf
Set up basic project skeleton
9fca4c3
@KnowerSmyf
created .gitignore to store data and model files
fe25335
@KnowerSmyf
Setup the UNet modules according to the paper
82802d5
@KnowerSmyf
Attempted to build the UNet according to paper...
9becad1
@KnowerSmyf
Implemented Encoder, changed UNet accordingly
597515b
@KnowerSmyf
Changed UNet Encoder input args
da0ebe4
@KnowerSmyf
Implemented upsampling module
241cbb7
@KnowerSmyf
Implemented Localisation module
c70f54a
@KnowerSmyf
Fixed afew bugs
5edc8b1
@KnowerSmyf
Worked on UNet + created Segmentation class
6f6ff64
@KnowerSmyf
Finished Unet + Segmentation
82d0e90
@KnowerSmyf
Cleaned up afew things
3cb04a7
@KnowerSmyf
Cleaned up the modules
d9f60b0
@KnowerSmyf
Made UNet 2D, setup Dataloader, added utils
171396a
@KnowerSmyf
Did some debugging on modules
3b364fe
@KnowerSmyf
Started implementing the training loop etc
a0ff43a
@KnowerSmyf
Realised this was the wrong spot...
1b3e31d
@KnowerSmyf
Switched from softmax to sigmoid UNet output
e465710
@KnowerSmyf
Implemented loader methods
66f6652
@KnowerSmyf
Fixed afew things
ea20f0c
@KnowerSmyf
Improved training loop
b431fce
@KnowerSmyf
Implemented a dice score method
78e3bde
@KnowerSmyf
set up my model testing
0e99346
@KnowerSmyf
started my predict.py file
c791103
@KnowerSmyf
committing a slurm script
d444b7a
@KnowerSmyf
fixed bug in dataset
0d0f302
@KnowerSmyf
modified ISICDataset __init__ method
efd6aab
@KnowerSmyf
added a check for inconsistencies in the DB
6f8b2f9
@KnowerSmyf
Put some inconsistency fixes and check in
6308bde
@KnowerSmyf
fixed check_consistency bug
662f1b3
@KnowerSmyf
Changed the threshold from 127.5 to 0.5 for binarizing the mask
ca6b114
@KnowerSmyf
The model is finally working, going to try a real training cycle
c0f75e7
@KnowerSmyf
forgot to declare 'no_improvement', fixed
7a171a8
@KnowerSmyf
fixed the error in the debugging random_split
296a12b
@KnowerSmyf
Using test partition in slurm script
8cc9427
@KnowerSmyf
Testing out validation and test batch size = 100
498f92c
@KnowerSmyf
The model works, time to train properly!
e82203c
@KnowerSmyf
Switched back to vgpu partition
051f27d
@KnowerSmyf
Gave the problem directory a meaningful name
a0d80de
@KnowerSmyf
Made the stoppage criteria less strict in training
1dda16a
@KnowerSmyf
deleted the old directory
d951222
@KnowerSmyf
Worked on my README file
856d8b8
@KnowerSmyf
Training again, lost a lot of data ):
e2f9ba6
@KnowerSmyf
created individual image and mask pre-processing
72b48cb
@KnowerSmyf
Added images
dc5ac4d
@KnowerSmyf
Added best_model.pth
4b321fa
@KnowerSmyf
Wrote the README file, finished the predict.py file
1ae7398
@KnowerSmyf
Removed debugging stuff
056988d
@KnowerSmyf
Improved the README file
7f30cbf
@KnowerSmyf
If the best_model.pth DNE execute train.py
76d6260
@KnowerSmyf
performance images
fa0eea2
@KnowerSmyf
Fixed afew README image naming bugs
dd27659
@KnowerSmyf
KnowerSmyf
commented
Oct 26, 2023

Copy link


Copy Markdown

Author
I'm new to github, I've tried like 3 pull requests... hopefully its all good
@wangzhaomxy
wangzhaomxy
commented
Nov 6, 2023•

edited

Loading

Copy link


Copy Markdown

Collaborator
This is an initial inspection, no action is required at this point
  • Well organized files, but wrong readme.md place.
  • Algorithm solves the problem appropriately. Average Dice Coefficient in testing dataset: 0.7364, but no evidence was shown. Predicted Mask output is not good enough, just showing 25 epochs training result in readme, which seems not the best result.
  • Correctly using PyTorch to construct the Improved U-Net models and functions.
  • Good coding design.
  • Sufficient docstring and comment in the code, but need some references.
  • Easy difficulty problem, no higher difficulty marks.
@shakes76shakes76
added
the 
Extension
Extension approved
label
Nov 20, 2023
@shakes76
shakes76
commented
Nov 20, 2023

Copy link


Copy Markdown

Owner
Marking
Good Practice (Design/Commenting, TF/Torch Usage)
Adequate design and implementation

Good spacing and comments

Header blocks
Recognition Problem
Solves problem but poor performance from predicted mask shown -1

Driver Script present

File structure present

Shows Usage & Demo & Visualisation & Data usage, no training plots etc. -2

Module present

Commenting

No Data leakage

Difficulty: Easy -10
Commit Log
Meaningful commit messages

Progressive commits used
Documentation
ReadMe acceptable, no refs -1

Model/technical explanation minimal -1

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
commented
Nov 20, 2023

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Owner
Please revert changes to repo README files for merging, does not affect grade only merge.
@shakes76shakes76
added
the 
question
Further information is requested
label
Nov 20, 2023
@wangzhaomxy
wangzhaomxy
commented
Nov 21, 2023

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Collaborator
No feedback attempt and no feedback marks lost.
Sign up for freeto join this conversation on GitHub.
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Reviewers


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Labels

ExtensionExtension approvedImproved UNetquestionFurther information is requested

Projects


None yet


Milestone


No milestone


Development

Successfully merging this pull request may close these issues.

4 participants

@KnowerSmyf@wangzhaomxy@shakes76@nathasha-naranpanawa

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Topic recognition - #171
Open
KnowerSmyf wants to merge 79 commits into
shakes76:topic-recognitionfrom 
KnowerSmyf:topic-recognition
Open
Topic recognition#171
KnowerSmyf wants to merge 79 commits into
shakes76:topic-recognitionfrom 
KnowerSmyf:topic-recognition
Conversation
@KnowerSmyf
@KnowerSmyfKnowerSmyf
commented
Oct 26, 2023

Copy link


Copy Markdown

Implemented a 2D variant of the improved UNet architecture and used it to perform lesion skin boundary segmentation. I had an extension (hence the late submission), also I feel like I went pretty crazy with the commits... Sorry about that (:
@KnowerSmyf
Set up basic project skeleton
9fca4c3
@KnowerSmyf
created .gitignore to store data and model files
fe25335
@KnowerSmyf
Setup the UNet modules according to the paper
82802d5
@KnowerSmyf
Attempted to build the UNet according to paper...
9becad1
@KnowerSmyf
Implemented Encoder, changed UNet accordingly
597515b
@KnowerSmyf
Changed UNet Encoder input args
da0ebe4
@KnowerSmyf
Implemented upsampling module
241cbb7
@KnowerSmyf
Implemented Localisation module
c70f54a
@KnowerSmyf
Fixed afew bugs
5edc8b1
@KnowerSmyf
Worked on UNet + created Segmentation class
6f6ff64
@KnowerSmyf
Finished Unet + Segmentation
82d0e90
@KnowerSmyf
Cleaned up afew things
3cb04a7
@KnowerSmyf
Cleaned up the modules
d9f60b0
@KnowerSmyf
Made UNet 2D, setup Dataloader, added utils
171396a
@KnowerSmyf
Did some debugging on modules
3b364fe
@KnowerSmyf
Started implementing the training loop etc
a0ff43a
@KnowerSmyf
Realised this was the wrong spot...
1b3e31d
@KnowerSmyf
Switched from softmax to sigmoid UNet output
e465710
@KnowerSmyf
Implemented loader methods
66f6652
@KnowerSmyf
Fixed afew things
ea20f0c
@KnowerSmyf
Improved training loop
b431fce
@KnowerSmyf
Implemented a dice score method
78e3bde
@KnowerSmyf
set up my model testing
0e99346
@KnowerSmyf
started my predict.py file
c791103
@KnowerSmyf
committing a slurm script
d444b7a
@KnowerSmyf
fixed bug in dataset
0d0f302
@KnowerSmyf
modified ISICDataset __init__ method
efd6aab
@KnowerSmyf
added a check for inconsistencies in the DB
6f8b2f9
@KnowerSmyf
Put some inconsistency fixes and check in
6308bde
@KnowerSmyf
fixed check_consistency bug
662f1b3
@KnowerSmyf
Changed the threshold from 127.5 to 0.5 for binarizing the mask
ca6b114
@KnowerSmyf
The model is finally working, going to try a real training cycle
c0f75e7
@KnowerSmyf
forgot to declare 'no_improvement', fixed
7a171a8
@KnowerSmyf
fixed the error in the debugging random_split
296a12b
@KnowerSmyf
Using test partition in slurm script
8cc9427
@KnowerSmyf
Testing out validation and test batch size = 100
498f92c
@KnowerSmyf
The model works, time to train properly!
e82203c
@KnowerSmyf
Switched back to vgpu partition
051f27d
@KnowerSmyf
Gave the problem directory a meaningful name
a0d80de
@KnowerSmyf
Made the stoppage criteria less strict in training
1dda16a
@KnowerSmyf
deleted the old directory
d951222
@KnowerSmyf
Worked on my README file
856d8b8
@KnowerSmyf
Training again, lost a lot of data ):
e2f9ba6
@KnowerSmyf
created individual image and mask pre-processing
72b48cb
@KnowerSmyf
Added images
dc5ac4d
@KnowerSmyf
Added best_model.pth
4b321fa
@KnowerSmyf
Wrote the README file, finished the predict.py file
1ae7398
@KnowerSmyf
Removed debugging stuff
056988d
@KnowerSmyf
Improved the README file
7f30cbf
@KnowerSmyf
If the best_model.pth DNE execute train.py
76d6260
@KnowerSmyf
performance images
fa0eea2
@KnowerSmyf
Fixed afew README image naming bugs
dd27659
@KnowerSmyf
KnowerSmyf
commented
Oct 26, 2023

Copy link


Copy Markdown

Author
I'm new to github, I've tried like 3 pull requests... hopefully its all good
@wangzhaomxy
wangzhaomxy
commented
Nov 6, 2023•

edited

Loading

Copy link


Copy Markdown

Collaborator
This is an initial inspection, no action is required at this point
  • Well organized files, but wrong readme.md place.
  • Algorithm solves the problem appropriately. Average Dice Coefficient in testing dataset: 0.7364, but no evidence was shown. Predicted Mask output is not good enough, just showing 25 epochs training result in readme, which seems not the best result.
  • Correctly using PyTorch to construct the Improved U-Net models and functions.
  • Good coding design.
  • Sufficient docstring and comment in the code, but need some references.
  • Easy difficulty problem, no higher difficulty marks.
@shakes76shakes76
added
the 
Extension
Extension approved
label
Nov 20, 2023
@shakes76
shakes76
commented
Nov 20, 2023

Copy link


Copy Markdown

Owner
Marking
Good Practice (Design/Commenting, TF/Torch Usage)
Adequate design and implementation

Good spacing and comments

Header blocks
Recognition Problem
Solves problem but poor performance from predicted mask shown -1

Driver Script present

File structure present

Shows Usage & Demo & Visualisation & Data usage, no training plots etc. -2

Module present

Commenting

No Data leakage

Difficulty: Easy -10
Commit Log
Meaningful commit messages

Progressive commits used
Documentation
ReadMe acceptable, no refs -1

Model/technical explanation minimal -1

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
commented
Nov 20, 2023

Copy link


Copy Markdown

Owner
Please revert changes to repo README files for merging, does not affect grade only merge.
@shakes76shakes76
added
the 
question
Further information is requested
label
Nov 20, 2023
@wangzhaomxy
wangzhaomxy
commented
Nov 21, 2023

Copy link


Copy Markdown

Collaborator
No feedback attempt and no feedback marks lost.
Sign up for freeto join this conversation on GitHub.
Already have an account?
Sign in to comment

Reviewers


No reviews


Assignees


No one assigned


Labels

ExtensionExtension approvedImproved UNetquestionFurther information is requested

Projects


None yet


Milestone


No milestone


Development

Successfully merging this pull request may close these issues.

4 participants

@KnowerSmyf@wangzhaomxy@shakes76@nathasha-naranpanawa

, 'i');
if (__m === '*' || __re.test(location.href)) {
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try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Topic recognition - #171
Open
KnowerSmyf wants to merge 79 commits into
shakes76:topic-recognitionfrom 
KnowerSmyf:topic-recognition
Open
Topic recognition#171
KnowerSmyf wants to merge 79 commits into
shakes76:topic-recognitionfrom 
KnowerSmyf:topic-recognition
Conversation
@KnowerSmyf
@KnowerSmyfKnowerSmyf
commented
Oct 26, 2023

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Implemented a 2D variant of the improved UNet architecture and used it to perform lesion skin boundary segmentation. I had an extension (hence the late submission), also I feel like I went pretty crazy with the commits... Sorry about that (:
@KnowerSmyf
Set up basic project skeleton
9fca4c3
@KnowerSmyf
created .gitignore to store data and model files
fe25335
@KnowerSmyf
Setup the UNet modules according to the paper
82802d5
@KnowerSmyf
Attempted to build the UNet according to paper...
9becad1
@KnowerSmyf
Implemented Encoder, changed UNet accordingly
597515b
@KnowerSmyf
Changed UNet Encoder input args
da0ebe4
@KnowerSmyf
Implemented upsampling module
241cbb7
@KnowerSmyf
Implemented Localisation module
c70f54a
@KnowerSmyf
Fixed afew bugs
5edc8b1
@KnowerSmyf
Worked on UNet + created Segmentation class
6f6ff64
@KnowerSmyf
Finished Unet + Segmentation
82d0e90
@KnowerSmyf
Cleaned up afew things
3cb04a7
@KnowerSmyf
Cleaned up the modules
d9f60b0
@KnowerSmyf
Made UNet 2D, setup Dataloader, added utils
171396a
@KnowerSmyf
Did some debugging on modules
3b364fe
@KnowerSmyf
Started implementing the training loop etc
a0ff43a
@KnowerSmyf
Realised this was the wrong spot...
1b3e31d
@KnowerSmyf
Switched from softmax to sigmoid UNet output
e465710
@KnowerSmyf
Implemented loader methods
66f6652
@KnowerSmyf
Fixed afew things
ea20f0c
@KnowerSmyf
Improved training loop
b431fce
@KnowerSmyf
Implemented a dice score method
78e3bde
@KnowerSmyf
set up my model testing
0e99346
@KnowerSmyf
started my predict.py file
c791103
@KnowerSmyf
committing a slurm script
d444b7a
@KnowerSmyf
fixed bug in dataset
0d0f302
@KnowerSmyf
modified ISICDataset __init__ method
efd6aab
@KnowerSmyf
added a check for inconsistencies in the DB
6f8b2f9
@KnowerSmyf
Put some inconsistency fixes and check in
6308bde
@KnowerSmyf
fixed check_consistency bug
662f1b3
@KnowerSmyf
Changed the threshold from 127.5 to 0.5 for binarizing the mask
ca6b114
@KnowerSmyf
The model is finally working, going to try a real training cycle
c0f75e7
@KnowerSmyf
forgot to declare 'no_improvement', fixed
7a171a8
@KnowerSmyf
fixed the error in the debugging random_split
296a12b
@KnowerSmyf
Using test partition in slurm script
8cc9427
@KnowerSmyf
Testing out validation and test batch size = 100
498f92c
@KnowerSmyf
The model works, time to train properly!
e82203c
@KnowerSmyf
Switched back to vgpu partition
051f27d
@KnowerSmyf
Gave the problem directory a meaningful name
a0d80de
@KnowerSmyf
Made the stoppage criteria less strict in training
1dda16a
@KnowerSmyf
deleted the old directory
d951222
@KnowerSmyf
Worked on my README file
856d8b8
@KnowerSmyf
Training again, lost a lot of data ):
e2f9ba6
@KnowerSmyf
created individual image and mask pre-processing
72b48cb
@KnowerSmyf
Added images
dc5ac4d
@KnowerSmyf
Added best_model.pth
4b321fa
@KnowerSmyf
Wrote the README file, finished the predict.py file
1ae7398
@KnowerSmyf
Removed debugging stuff
056988d
@KnowerSmyf
Improved the README file
7f30cbf
@KnowerSmyf
If the best_model.pth DNE execute train.py
76d6260
@KnowerSmyf
performance images
fa0eea2
@KnowerSmyf
Fixed afew README image naming bugs
dd27659
@KnowerSmyf
KnowerSmyf
commented
Oct 26, 2023

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Author
I'm new to github, I've tried like 3 pull requests... hopefully its all good
@wangzhaomxy
wangzhaomxy
commented
Nov 6, 2023•

edited

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Collaborator
This is an initial inspection, no action is required at this point
  • Well organized files, but wrong readme.md place.
  • Algorithm solves the problem appropriately. Average Dice Coefficient in testing dataset: 0.7364, but no evidence was shown. Predicted Mask output is not good enough, just showing 25 epochs training result in readme, which seems not the best result.
  • Correctly using PyTorch to construct the Improved U-Net models and functions.
  • Good coding design.
  • Sufficient docstring and comment in the code, but need some references.
  • Easy difficulty problem, no higher difficulty marks.
@shakes76shakes76
added
the 
Extension
Extension approved
label
Nov 20, 2023
@shakes76
shakes76
commented
Nov 20, 2023

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Owner
Marking
Good Practice (Design/Commenting, TF/Torch Usage)
Adequate design and implementation

Good spacing and comments

Header blocks
Recognition Problem
Solves problem but poor performance from predicted mask shown -1

Driver Script present

File structure present

Shows Usage & Demo & Visualisation & Data usage, no training plots etc. -2

Module present

Commenting

No Data leakage

Difficulty: Easy -10
Commit Log
Meaningful commit messages

Progressive commits used
Documentation
ReadMe acceptable, no refs -1

Model/technical explanation minimal -1

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
commented
Nov 20, 2023

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Owner
Please revert changes to repo README files for merging, does not affect grade only merge.
@shakes76shakes76
added
the 
question
Further information is requested
label
Nov 20, 2023
@wangzhaomxy
wangzhaomxy
commented
Nov 21, 2023

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No feedback attempt and no feedback marks lost.
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4 participants

@KnowerSmyf@wangzhaomxy@shakes76@nathasha-naranpanawa

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
Topic recognition - #171
Open
KnowerSmyf wants to merge 79 commits into
shakes76:topic-recognitionfrom 
KnowerSmyf:topic-recognition
Open
Topic recognition#171
KnowerSmyf wants to merge 79 commits into
shakes76:topic-recognitionfrom 
KnowerSmyf:topic-recognition
Conversation
@KnowerSmyf
@KnowerSmyfKnowerSmyf
commented
Oct 26, 2023

Copy link


Copy Markdown

Implemented a 2D variant of the improved UNet architecture and used it to perform lesion skin boundary segmentation. I had an extension (hence the late submission), also I feel like I went pretty crazy with the commits... Sorry about that (:
@KnowerSmyf
Set up basic project skeleton
9fca4c3
@KnowerSmyf
created .gitignore to store data and model files
fe25335
@KnowerSmyf
Setup the UNet modules according to the paper
82802d5
@KnowerSmyf
Attempted to build the UNet according to paper...
9becad1
@KnowerSmyf
Implemented Encoder, changed UNet accordingly
597515b
@KnowerSmyf
Changed UNet Encoder input args
da0ebe4
@KnowerSmyf
Implemented upsampling module
241cbb7
@KnowerSmyf
Implemented Localisation module
c70f54a
@KnowerSmyf
Fixed afew bugs
5edc8b1
@KnowerSmyf
Worked on UNet + created Segmentation class
6f6ff64
@KnowerSmyf
Finished Unet + Segmentation
82d0e90
@KnowerSmyf
Cleaned up afew things
3cb04a7
@KnowerSmyf
Cleaned up the modules
d9f60b0
@KnowerSmyf
Made UNet 2D, setup Dataloader, added utils
171396a
@KnowerSmyf
Did some debugging on modules
3b364fe
@KnowerSmyf
Started implementing the training loop etc
a0ff43a
@KnowerSmyf
Realised this was the wrong spot...
1b3e31d
@KnowerSmyf
Switched from softmax to sigmoid UNet output
e465710
@KnowerSmyf
Implemented loader methods
66f6652
@KnowerSmyf
Fixed afew things
ea20f0c
@KnowerSmyf
Improved training loop
b431fce
@KnowerSmyf
Implemented a dice score method
78e3bde
@KnowerSmyf
set up my model testing
0e99346
@KnowerSmyf
started my predict.py file
c791103
@KnowerSmyf
committing a slurm script
d444b7a
@KnowerSmyf
fixed bug in dataset
0d0f302
@KnowerSmyf
modified ISICDataset __init__ method
efd6aab
@KnowerSmyf
added a check for inconsistencies in the DB
6f8b2f9
@KnowerSmyf
Put some inconsistency fixes and check in
6308bde
@KnowerSmyf
fixed check_consistency bug
662f1b3
@KnowerSmyf
Changed the threshold from 127.5 to 0.5 for binarizing the mask
ca6b114
@KnowerSmyf
The model is finally working, going to try a real training cycle
c0f75e7
@KnowerSmyf
forgot to declare 'no_improvement', fixed
7a171a8
@KnowerSmyf
fixed the error in the debugging random_split
296a12b
@KnowerSmyf
Using test partition in slurm script
8cc9427
@KnowerSmyf
Testing out validation and test batch size = 100
498f92c
@KnowerSmyf
The model works, time to train properly!
e82203c
@KnowerSmyf
Switched back to vgpu partition
051f27d
@KnowerSmyf
Gave the problem directory a meaningful name
a0d80de
@KnowerSmyf
Made the stoppage criteria less strict in training
1dda16a
@KnowerSmyf
deleted the old directory
d951222
@KnowerSmyf
Worked on my README file
856d8b8
@KnowerSmyf
Training again, lost a lot of data ):
e2f9ba6
@KnowerSmyf
created individual image and mask pre-processing
72b48cb
@KnowerSmyf
Added images
dc5ac4d
@KnowerSmyf
Added best_model.pth
4b321fa
@KnowerSmyf
Wrote the README file, finished the predict.py file
1ae7398
@KnowerSmyf
Removed debugging stuff
056988d
@KnowerSmyf
Improved the README file
7f30cbf
@KnowerSmyf
If the best_model.pth DNE execute train.py
76d6260
@KnowerSmyf
performance images
fa0eea2
@KnowerSmyf
Fixed afew README image naming bugs
dd27659
@KnowerSmyf
KnowerSmyf
commented
Oct 26, 2023

Copy link


Copy Markdown

Author
I'm new to github, I've tried like 3 pull requests... hopefully its all good
@wangzhaomxy
wangzhaomxy
commented
Nov 6, 2023•

edited

Loading

Copy link


Copy Markdown

Collaborator
This is an initial inspection, no action is required at this point
  • Well organized files, but wrong readme.md place.
  • Algorithm solves the problem appropriately. Average Dice Coefficient in testing dataset: 0.7364, but no evidence was shown. Predicted Mask output is not good enough, just showing 25 epochs training result in readme, which seems not the best result.
  • Correctly using PyTorch to construct the Improved U-Net models and functions.
  • Good coding design.
  • Sufficient docstring and comment in the code, but need some references.
  • Easy difficulty problem, no higher difficulty marks.
@shakes76shakes76
added
the 
Extension
Extension approved
label
Nov 20, 2023
@shakes76
shakes76
commented
Nov 20, 2023

Copy link


Copy Markdown

Owner
Marking
Good Practice (Design/Commenting, TF/Torch Usage)
Adequate design and implementation

Good spacing and comments

Header blocks
Recognition Problem
Solves problem but poor performance from predicted mask shown -1

Driver Script present

File structure present

Shows Usage & Demo & Visualisation & Data usage, no training plots etc. -2

Module present

Commenting

No Data leakage

Difficulty: Easy -10
Commit Log
Meaningful commit messages

Progressive commits used
Documentation
ReadMe acceptable, no refs -1

Model/technical explanation minimal -1

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
commented
Nov 20, 2023

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Owner
Please revert changes to repo README files for merging, does not affect grade only merge.
@shakes76shakes76
added
the 
question
Further information is requested
label
Nov 20, 2023
@wangzhaomxy
wangzhaomxy
commented
Nov 21, 2023

Copy link


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Collaborator
No feedback attempt and no feedback marks lost.
Sign up for freeto join this conversation on GitHub.
Already have an account?
Sign in to comment

Reviewers


No reviews


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No one assigned


Labels

ExtensionExtension approvedImproved UNetquestionFurther information is requested

Projects


None yet


Milestone


No milestone


Development

Successfully merging this pull request may close these issues.

4 participants

@KnowerSmyf@wangzhaomxy@shakes76@nathasha-naranpanawa

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Topic recognition - #171
Open
KnowerSmyf wants to merge 79 commits into
shakes76:topic-recognitionfrom 
KnowerSmyf:topic-recognition
Open
Topic recognition#171
KnowerSmyf wants to merge 79 commits into
shakes76:topic-recognitionfrom 
KnowerSmyf:topic-recognition
Conversation
@KnowerSmyf
@KnowerSmyfKnowerSmyf
commented
Oct 26, 2023

Copy link


Copy Markdown

Implemented a 2D variant of the improved UNet architecture and used it to perform lesion skin boundary segmentation. I had an extension (hence the late submission), also I feel like I went pretty crazy with the commits... Sorry about that (:
@KnowerSmyf
Set up basic project skeleton
9fca4c3
@KnowerSmyf
created .gitignore to store data and model files
fe25335
@KnowerSmyf
Setup the UNet modules according to the paper
82802d5
@KnowerSmyf
Attempted to build the UNet according to paper...
9becad1
@KnowerSmyf
Implemented Encoder, changed UNet accordingly
597515b
@KnowerSmyf
Changed UNet Encoder input args
da0ebe4
@KnowerSmyf
Implemented upsampling module
241cbb7
@KnowerSmyf
Implemented Localisation module
c70f54a
@KnowerSmyf
Fixed afew bugs
5edc8b1
@KnowerSmyf
Worked on UNet + created Segmentation class
6f6ff64
@KnowerSmyf
Finished Unet + Segmentation
82d0e90
@KnowerSmyf
Cleaned up afew things
3cb04a7
@KnowerSmyf
Cleaned up the modules
d9f60b0
@KnowerSmyf
Made UNet 2D, setup Dataloader, added utils
171396a
@KnowerSmyf
Did some debugging on modules
3b364fe
@KnowerSmyf
Started implementing the training loop etc
a0ff43a
@KnowerSmyf
Realised this was the wrong spot...
1b3e31d
@KnowerSmyf
Switched from softmax to sigmoid UNet output
e465710
@KnowerSmyf
Implemented loader methods
66f6652
@KnowerSmyf
Fixed afew things
ea20f0c
@KnowerSmyf
Improved training loop
b431fce
@KnowerSmyf
Implemented a dice score method
78e3bde
@KnowerSmyf
set up my model testing
0e99346
@KnowerSmyf
started my predict.py file
c791103
@KnowerSmyf
committing a slurm script
d444b7a
@KnowerSmyf
fixed bug in dataset
0d0f302
@KnowerSmyf
modified ISICDataset __init__ method
efd6aab
@KnowerSmyf
added a check for inconsistencies in the DB
6f8b2f9
@KnowerSmyf
Put some inconsistency fixes and check in
6308bde
@KnowerSmyf
fixed check_consistency bug
662f1b3
@KnowerSmyf
Changed the threshold from 127.5 to 0.5 for binarizing the mask
ca6b114
@KnowerSmyf
The model is finally working, going to try a real training cycle
c0f75e7
@KnowerSmyf
forgot to declare 'no_improvement', fixed
7a171a8
@KnowerSmyf
fixed the error in the debugging random_split
296a12b
@KnowerSmyf
Using test partition in slurm script
8cc9427
@KnowerSmyf
Testing out validation and test batch size = 100
498f92c
@KnowerSmyf
The model works, time to train properly!
e82203c
@KnowerSmyf
Switched back to vgpu partition
051f27d
@KnowerSmyf
Gave the problem directory a meaningful name
a0d80de
@KnowerSmyf
Made the stoppage criteria less strict in training
1dda16a
@KnowerSmyf
deleted the old directory
d951222
@KnowerSmyf
Worked on my README file
856d8b8
@KnowerSmyf
Training again, lost a lot of data ):
e2f9ba6
@KnowerSmyf
created individual image and mask pre-processing
72b48cb
@KnowerSmyf
Added images
dc5ac4d
@KnowerSmyf
Added best_model.pth
4b321fa
@KnowerSmyf
Wrote the README file, finished the predict.py file
1ae7398
@KnowerSmyf
Removed debugging stuff
056988d
@KnowerSmyf
Improved the README file
7f30cbf
@KnowerSmyf
If the best_model.pth DNE execute train.py
76d6260
@KnowerSmyf
performance images
fa0eea2
@KnowerSmyf
Fixed afew README image naming bugs
dd27659
@KnowerSmyf
KnowerSmyf
commented
Oct 26, 2023

Copy link


Copy Markdown

Author
I'm new to github, I've tried like 3 pull requests... hopefully its all good
@wangzhaomxy
wangzhaomxy
commented
Nov 6, 2023•

edited

Loading

Copy link


Copy Markdown

Collaborator
This is an initial inspection, no action is required at this point
  • Well organized files, but wrong readme.md place.
  • Algorithm solves the problem appropriately. Average Dice Coefficient in testing dataset: 0.7364, but no evidence was shown. Predicted Mask output is not good enough, just showing 25 epochs training result in readme, which seems not the best result.
  • Correctly using PyTorch to construct the Improved U-Net models and functions.
  • Good coding design.
  • Sufficient docstring and comment in the code, but need some references.
  • Easy difficulty problem, no higher difficulty marks.
@shakes76shakes76
added
the 
Extension
Extension approved
label
Nov 20, 2023
@shakes76
shakes76
commented
Nov 20, 2023

Copy link


Copy Markdown

Owner
Marking
Good Practice (Design/Commenting, TF/Torch Usage)
Adequate design and implementation

Good spacing and comments

Header blocks
Recognition Problem
Solves problem but poor performance from predicted mask shown -1

Driver Script present

File structure present

Shows Usage & Demo & Visualisation & Data usage, no training plots etc. -2

Module present

Commenting

No Data leakage

Difficulty: Easy -10
Commit Log
Meaningful commit messages

Progressive commits used
Documentation
ReadMe acceptable, no refs -1

Model/technical explanation minimal -1

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
commented
Nov 20, 2023

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Copy Markdown

Owner
Please revert changes to repo README files for merging, does not affect grade only merge.
@shakes76shakes76
added
the 
question
Further information is requested
label
Nov 20, 2023
@wangzhaomxy
wangzhaomxy
commented
Nov 21, 2023

Copy link


Copy Markdown

Collaborator
No feedback attempt and no feedback marks lost.
Sign up for freeto join this conversation on GitHub.
Already have an account?
Sign in to comment

Reviewers


No reviews


Assignees


No one assigned


Labels

ExtensionExtension approvedImproved UNetquestionFurther information is requested

Projects


None yet


Milestone


No milestone


Development

Successfully merging this pull request may close these issues.

4 participants

@KnowerSmyf@wangzhaomxy@shakes76@nathasha-naranpanawa

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Topic recognition - #171
Open
KnowerSmyf wants to merge 79 commits into
shakes76:topic-recognitionfrom 
KnowerSmyf:topic-recognition
Open
Topic recognition#171
KnowerSmyf wants to merge 79 commits into
shakes76:topic-recognitionfrom 
KnowerSmyf:topic-recognition
Conversation
@KnowerSmyf
@KnowerSmyfKnowerSmyf
commented
Oct 26, 2023

Copy link


Copy Markdown

Implemented a 2D variant of the improved UNet architecture and used it to perform lesion skin boundary segmentation. I had an extension (hence the late submission), also I feel like I went pretty crazy with the commits... Sorry about that (:
@KnowerSmyf
Set up basic project skeleton
9fca4c3
@KnowerSmyf
created .gitignore to store data and model files
fe25335
@KnowerSmyf
Setup the UNet modules according to the paper
82802d5
@KnowerSmyf
Attempted to build the UNet according to paper...
9becad1
@KnowerSmyf
Implemented Encoder, changed UNet accordingly
597515b
@KnowerSmyf
Changed UNet Encoder input args
da0ebe4
@KnowerSmyf
Implemented upsampling module
241cbb7
@KnowerSmyf
Implemented Localisation module
c70f54a
@KnowerSmyf
Fixed afew bugs
5edc8b1
@KnowerSmyf
Worked on UNet + created Segmentation class
6f6ff64
@KnowerSmyf
Finished Unet + Segmentation
82d0e90
@KnowerSmyf
Cleaned up afew things
3cb04a7
@KnowerSmyf
Cleaned up the modules
d9f60b0
@KnowerSmyf
Made UNet 2D, setup Dataloader, added utils
171396a
@KnowerSmyf
Did some debugging on modules
3b364fe
@KnowerSmyf
Started implementing the training loop etc
a0ff43a
@KnowerSmyf
Realised this was the wrong spot...
1b3e31d
@KnowerSmyf
Switched from softmax to sigmoid UNet output
e465710
@KnowerSmyf
Implemented loader methods
66f6652
@KnowerSmyf
Fixed afew things
ea20f0c
@KnowerSmyf
Improved training loop
b431fce
@KnowerSmyf
Implemented a dice score method
78e3bde
@KnowerSmyf
set up my model testing
0e99346
@KnowerSmyf
started my predict.py file
c791103
@KnowerSmyf
committing a slurm script
d444b7a
@KnowerSmyf
fixed bug in dataset
0d0f302
@KnowerSmyf
modified ISICDataset __init__ method
efd6aab
@KnowerSmyf
added a check for inconsistencies in the DB
6f8b2f9
@KnowerSmyf
Put some inconsistency fixes and check in
6308bde
@KnowerSmyf
fixed check_consistency bug
662f1b3
@KnowerSmyf
Changed the threshold from 127.5 to 0.5 for binarizing the mask
ca6b114
@KnowerSmyf
The model is finally working, going to try a real training cycle
c0f75e7
@KnowerSmyf
forgot to declare 'no_improvement', fixed
7a171a8
@KnowerSmyf
fixed the error in the debugging random_split
296a12b
@KnowerSmyf
Using test partition in slurm script
8cc9427
@KnowerSmyf
Testing out validation and test batch size = 100
498f92c
@KnowerSmyf
The model works, time to train properly!
e82203c
@KnowerSmyf
Switched back to vgpu partition
051f27d
@KnowerSmyf
Gave the problem directory a meaningful name
a0d80de
@KnowerSmyf
Made the stoppage criteria less strict in training
1dda16a
@KnowerSmyf
deleted the old directory
d951222
@KnowerSmyf
Worked on my README file
856d8b8
@KnowerSmyf
Training again, lost a lot of data ):
e2f9ba6
@KnowerSmyf
created individual image and mask pre-processing
72b48cb
@KnowerSmyf
Added images
dc5ac4d
@KnowerSmyf
Added best_model.pth
4b321fa
@KnowerSmyf
Wrote the README file, finished the predict.py file
1ae7398
@KnowerSmyf
Removed debugging stuff
056988d
@KnowerSmyf
Improved the README file
7f30cbf
@KnowerSmyf
If the best_model.pth DNE execute train.py
76d6260
@KnowerSmyf
performance images
fa0eea2
@KnowerSmyf
Fixed afew README image naming bugs
dd27659
@KnowerSmyf
KnowerSmyf
commented
Oct 26, 2023

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I'm new to github, I've tried like 3 pull requests... hopefully its all good
@wangzhaomxy
wangzhaomxy
commented
Nov 6, 2023•

edited

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This is an initial inspection, no action is required at this point
  • Well organized files, but wrong readme.md place.
  • Algorithm solves the problem appropriately. Average Dice Coefficient in testing dataset: 0.7364, but no evidence was shown. Predicted Mask output is not good enough, just showing 25 epochs training result in readme, which seems not the best result.
  • Correctly using PyTorch to construct the Improved U-Net models and functions.
  • Good coding design.
  • Sufficient docstring and comment in the code, but need some references.
  • Easy difficulty problem, no higher difficulty marks.
@shakes76shakes76
added
the 
Extension
Extension approved
label
Nov 20, 2023
@shakes76
shakes76
commented
Nov 20, 2023

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Owner
Marking
Good Practice (Design/Commenting, TF/Torch Usage)
Adequate design and implementation

Good spacing and comments

Header blocks
Recognition Problem
Solves problem but poor performance from predicted mask shown -1

Driver Script present

File structure present

Shows Usage & Demo & Visualisation & Data usage, no training plots etc. -2

Module present

Commenting

No Data leakage

Difficulty: Easy -10
Commit Log
Meaningful commit messages

Progressive commits used
Documentation
ReadMe acceptable, no refs -1

Model/technical explanation minimal -1

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
commented
Nov 20, 2023

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Please revert changes to repo README files for merging, does not affect grade only merge.
@shakes76shakes76
added
the 
question
Further information is requested
label
Nov 20, 2023
@wangzhaomxy
wangzhaomxy
commented
Nov 21, 2023

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No feedback attempt and no feedback marks lost.
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4 participants

@KnowerSmyf@wangzhaomxy@shakes76@nathasha-naranpanawa

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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Topic recognition - #171
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KnowerSmyf:topic-recognition
Open
Topic recognition#171
KnowerSmyf wants to merge 79 commits into
shakes76:topic-recognitionfrom 
KnowerSmyf:topic-recognition
Conversation
@KnowerSmyf
@KnowerSmyfKnowerSmyf
commented
Oct 26, 2023

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Implemented a 2D variant of the improved UNet architecture and used it to perform lesion skin boundary segmentation. I had an extension (hence the late submission), also I feel like I went pretty crazy with the commits... Sorry about that (:
@KnowerSmyf
Set up basic project skeleton
9fca4c3
@KnowerSmyf
created .gitignore to store data and model files
fe25335
@KnowerSmyf
Setup the UNet modules according to the paper
82802d5
@KnowerSmyf
Attempted to build the UNet according to paper...
9becad1
@KnowerSmyf
Implemented Encoder, changed UNet accordingly
597515b
@KnowerSmyf
Changed UNet Encoder input args
da0ebe4
@KnowerSmyf
Implemented upsampling module
241cbb7
@KnowerSmyf
Implemented Localisation module
c70f54a
@KnowerSmyf
Fixed afew bugs
5edc8b1
@KnowerSmyf
Worked on UNet + created Segmentation class
6f6ff64
@KnowerSmyf
Finished Unet + Segmentation
82d0e90
@KnowerSmyf
Cleaned up afew things
3cb04a7
@KnowerSmyf
Cleaned up the modules
d9f60b0
@KnowerSmyf
Made UNet 2D, setup Dataloader, added utils
171396a
@KnowerSmyf
Did some debugging on modules
3b364fe
@KnowerSmyf
Started implementing the training loop etc
a0ff43a
@KnowerSmyf
Realised this was the wrong spot...
1b3e31d
@KnowerSmyf
Switched from softmax to sigmoid UNet output
e465710
@KnowerSmyf
Implemented loader methods
66f6652
@KnowerSmyf
Fixed afew things
ea20f0c
@KnowerSmyf
Improved training loop
b431fce
@KnowerSmyf
Implemented a dice score method
78e3bde
@KnowerSmyf
set up my model testing
0e99346
@KnowerSmyf
started my predict.py file
c791103
@KnowerSmyf
committing a slurm script
d444b7a
@KnowerSmyf
fixed bug in dataset
0d0f302
@KnowerSmyf
modified ISICDataset __init__ method
efd6aab
@KnowerSmyf
added a check for inconsistencies in the DB
6f8b2f9
@KnowerSmyf
Put some inconsistency fixes and check in
6308bde
@KnowerSmyf
fixed check_consistency bug
662f1b3
@KnowerSmyf
Changed the threshold from 127.5 to 0.5 for binarizing the mask
ca6b114
@KnowerSmyf
The model is finally working, going to try a real training cycle
c0f75e7
@KnowerSmyf
forgot to declare 'no_improvement', fixed
7a171a8
@KnowerSmyf
fixed the error in the debugging random_split
296a12b
@KnowerSmyf
Using test partition in slurm script
8cc9427
@KnowerSmyf
Testing out validation and test batch size = 100
498f92c
@KnowerSmyf
The model works, time to train properly!
e82203c
@KnowerSmyf
Switched back to vgpu partition
051f27d
@KnowerSmyf
Gave the problem directory a meaningful name
a0d80de
@KnowerSmyf
Made the stoppage criteria less strict in training
1dda16a
@KnowerSmyf
deleted the old directory
d951222
@KnowerSmyf
Worked on my README file
856d8b8
@KnowerSmyf
Training again, lost a lot of data ):
e2f9ba6
@KnowerSmyf
created individual image and mask pre-processing
72b48cb
@KnowerSmyf
Added images
dc5ac4d
@KnowerSmyf
Added best_model.pth
4b321fa
@KnowerSmyf
Wrote the README file, finished the predict.py file
1ae7398
@KnowerSmyf
Removed debugging stuff
056988d
@KnowerSmyf
Improved the README file
7f30cbf
@KnowerSmyf
If the best_model.pth DNE execute train.py
76d6260
@KnowerSmyf
performance images
fa0eea2
@KnowerSmyf
Fixed afew README image naming bugs
dd27659
@KnowerSmyf
KnowerSmyf
commented
Oct 26, 2023

Copy link


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Author
I'm new to github, I've tried like 3 pull requests... hopefully its all good
@wangzhaomxy
wangzhaomxy
commented
Nov 6, 2023•

edited

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Collaborator
This is an initial inspection, no action is required at this point
  • Well organized files, but wrong readme.md place.
  • Algorithm solves the problem appropriately. Average Dice Coefficient in testing dataset: 0.7364, but no evidence was shown. Predicted Mask output is not good enough, just showing 25 epochs training result in readme, which seems not the best result.
  • Correctly using PyTorch to construct the Improved U-Net models and functions.
  • Good coding design.
  • Sufficient docstring and comment in the code, but need some references.
  • Easy difficulty problem, no higher difficulty marks.
@shakes76shakes76
added
the 
Extension
Extension approved
label
Nov 20, 2023
@shakes76
shakes76
commented
Nov 20, 2023

Copy link


Copy Markdown

Owner
Marking
Good Practice (Design/Commenting, TF/Torch Usage)
Adequate design and implementation

Good spacing and comments

Header blocks
Recognition Problem
Solves problem but poor performance from predicted mask shown -1

Driver Script present

File structure present

Shows Usage & Demo & Visualisation & Data usage, no training plots etc. -2

Module present

Commenting

No Data leakage

Difficulty: Easy -10
Commit Log
Meaningful commit messages

Progressive commits used
Documentation
ReadMe acceptable, no refs -1

Model/technical explanation minimal -1

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
commented
Nov 20, 2023

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Owner
Please revert changes to repo README files for merging, does not affect grade only merge.
@shakes76shakes76
added
the 
question
Further information is requested
label
Nov 20, 2023
@wangzhaomxy
wangzhaomxy
commented
Nov 21, 2023

Copy link


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Collaborator
No feedback attempt and no feedback marks lost.
Sign up for freeto join this conversation on GitHub.
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Reviewers


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No one assigned


Labels

ExtensionExtension approvedImproved UNetquestionFurther information is requested

Projects


None yet


Milestone


No milestone


Development

Successfully merging this pull request may close these issues.

4 participants

@KnowerSmyf@wangzhaomxy@shakes76@nathasha-naranpanawa