Train the model using new data created in issue #4

[Chintan2108]

• Train the model using the new dataset as created in issue Implement skew for dataset augmentation #4

• Compare the model performance, assess the generated images' quality using the stipulated measures (code available in the notebook) and document the same in readme of the PR

• Update repository readme with the quantitative comparison info of these two models

[Namyalg]

I would like to work on this

[Preetesh21]

I would also like to contribute to this issue.

[Chintan2108]

@Namyalg @Preetesh21
You both can train the model on the new skewed dataset as sampled by @Preetesh21 in issue #4

• Train the model using the same hyperparameters
• Report analytical and comparative model performance
  • Compare your respective models with the current project model (link in readme)
  • Compare each others' model
• Update readme with a comparison table in terms of our 3 evaluation metrics - PSNR, SSIM and Pearson Correlation
• Also provide epoch vs error graphs (for both of you)

[Namyalg]

Okay, will do that Namya LG

…

On Tue, Oct 27, 2020, 6:21 PM vesper2108 ***@***.***> wrote: @Namyalg <https://github.com/Namyalg> @Preetesh21 <https://github.com/Preetesh21> You both can train the model on the new skewed dataset as sampled by @Preetesh21 <https://github.com/Preetesh21> in issue #4 <#4> - Train the model using the same hyperparameters - Report analytical and comparative model performance - Compare your respective models with the current project model (link in readme) - Compare each others' model - Update readme with a comparison table in terms of our 3 evaluation metrics - PSNR, SSIM and Pearson Correlation - Also provide epoch vs error graphs (for both of you) — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#5 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AM3BEYPUADSOTYLHXO5QD2LSM265HANCNFSM4SPD74YA> .