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Style Transfer for Custom Images #857
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Status: Up for Grabs
Up for grabs issue.
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Thank you for creating this issue! We'll look into it as soon as possible. Your contributions are highly appreciated! 😊 |
@abhisheks008 plz assign me this issue |
All the four above mentioned models will going to be implemented for the problem statement right? |
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Deep Learning Simplified Repository (Proposing new issue)
🔴 Project Title : Style Transfer for Custom Images
🔴 Aim : To apply the artistic style of one image to the content of another image using various style transfer algorithms and determine the most effective method through comparative analysis.
🔴 Dataset : Custom images collected from diverse sources to ensure a variety of styles and contents for comprehensive testing.
🔴 Approach : Perform exploratory data analysis (EDA) to understand the characteristics and distribution of the custom images.
Implement and compare multiple style transfer algorithms:
Neural Style Transfer using VGG-19
Fast Style Transfer
Adaptive Instance Normalization (AdaIN)
StyleGAN-based approach
Evaluate the performance of each algorithm by comparing the visual quality and accuracy scores of the styled images.
Determine the best-fitting algorithm based on the comparative analysis results.
📍 Follow the Guidelines to Contribute in the Project :
requirements.txt
- This file will contain the required packages/libraries to run the project in other machines.Model
folder, theREADME.md
file must be filled up properly, with proper visualizations and conclusions.🔴🟡 Points to Note :
✅ To be Mentioned while taking the issue :
Implement and compare multiple style transfer algorithms:
Neural Style Transfer using VGG-19
Fast Style Transfer
Adaptive Instance Normalization (AdaIN)
StyleGAN-based approach
Evaluate the performance of each algorithm by comparing the visual quality and accuracy scores of the styled images.
Determine the best-fitting algorithm based on the comparative analysis results.
Happy Contributing 🚀
All the best. Enjoy your open source journey ahead. 😎
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