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Avdhesh-Varshney / AI-Code

AI-Code is an open-source project designed to help individuals learn and understand foundational code implementations of various AI algorithms, providing structured guides, resources, and hands-on projects across multiple AI domains like ML, DL, NLP, and GANs.
MIT License
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[Feature Request] Add GAN Model for Face Generation #8

Open Nikitakandwal opened 1 month ago

Nikitakandwal commented 1 month ago

Hello, I would like to propose adding a Generative Adversarial Network (GAN) model specifically designed for face generation to the project under SSOC'24. This model would be a valuable addition to our repository, particularly in the gan folder. The GAN model is known for its ability to generate high-quality, realistic images, and I believe it will greatly enhance the project. Objectives: Implement GAN Model: Develop a GAN model tailored for generating realistic human faces. Integrate into Repository: Add the model code and related resources to the gan folder. Documentation: Provide detailed documentation explaining the GAN model, its architecture, and how to use it. Training and Evaluation: Include scripts for training the model and evaluating its performance. Pre-trained Model: Optionally, provide a pre-trained model for users who want to quickly test the functionality.

UTSAVS26 commented 1 month ago

Hello,

Thank you for the proposal. I have outlined a detailed plan to implement and integrate a GAN model for face generation into the project under SSOC'24. Here’s what I intend to do:

  1. Implement GAN Model:

    • Research and select the appropriate GAN architecture (e.g., DCGAN, StyleGAN).
    • Develop and test the GAN model for generating realistic human faces.

  2. Integrate into Repository:

    • Create a structured gan folder in the repository.
    • Add the model code, training scripts, and evaluation scripts.

  3. Documentation:

    • Provide comprehensive documentation covering the GAN model architecture, setup, and usage instructions.
    • Include code comments and usage examples.

  4. Training and Evaluation:

    • Develop scripts for preprocessing, training, and evaluating the model.
    • Ensure reproducibility and include performance metrics.

  5. Pre-trained Model (Optional):

    • Train the model on a large dataset.
    • Provide a downloadable pre-trained model and instructions for usage.

I will start by drafting a detailed proposal and timeline for the implementation. Looking forward to feedback and collaboration to ensure the successful integration of this GAN model into the project.

Best regards, Utsav Singhal

Avdhesh-Varshney commented 1 month ago

@Nikitakandwal are you planning for the addition of the face generation model project or pathway for how to approach it? @UTSAVS26 don't comment on other issues, it will not assign any issue. Raise your own issue.

Nikitakandwal commented 1 month ago

@Nikitakandwal are you planning for the addition of the face generation model project or pathway for how to approach it? @UTSAVS26 don't comment on other issues, it will not assign any issue. Raise your own issue.

Can I just add the project and explain the working of GAN model so that anyone can understand it's implementation.

Avdhesh-Varshney commented 4 weeks ago

@Nikitakandwal This repository is just for the guidance purpose not the addition of the projects. So, Create the folder for GAN/Projects/Face-Generation-Model. Inside this directory, you have to create the full pathway to approach this project and gain insights.

Assigned to you.