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This repository contains notebooks showcasing various generative models, including DCGAN and VAE for anime face generation, an Autoencoder for converting photos to sketches, a captioning model using an attention mechanism for an image caption generator, and more.

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AI Generative Models Projects

Project Highlights:

  • DCGAN-Anime Face Generation: Step into the world of anime with the DCGAN Anime Face Generation project. Utilizing Deep Convolutional Generative Adversarial Networks (DCGAN), this project brings to life a mesmerizing collection of anime faces. Witness the power of AI as it creates intricate, unique, and captivating anime-style facial images. Explore the magic of generative art and embark on a journey through the boundless creativity of machine learning.

  • VAE Anime Face Generation: VAE Anime Face Generation invites you to discover the enchanting world of anime through Variational Autoencoders (VAEs). With the aid of VAEs, this project generates anime-style faces that are both diverse and captivating. Immerse yourself in the beauty of probabilistic generative models and experience the wonder of creating anime faces that evoke emotion and storytelling.

  • Photo to Sketch Autoencoder: Transform your photos into artistic sketches with the Photo-to-Sketch Autoencoder project. Harnessing the power of autoencoders, this project converts your ordinary photographs into remarkable pencil sketch renditions. Explore the intersection of art and technology as you watch your images come to life uniquely and creatively.

  • Image Caption Generator: The Image Caption Generator project is your gateway to the world of computer vision and natural language processing. Using cutting-edge techniques, this project automatically generates descriptive captions for your images. Witness the synergy of visual understanding and language generation as it brings a new dimension to your image content. Immerse yourself in the power of AI-driven storytelling and explore the limitless potential of image captioning.

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This repository contains notebooks showcasing various generative models, including DCGAN and VAE for anime face generation, an Autoencoder for converting photos to sketches, a captioning model using an attention mechanism for an image caption generator, and more.

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