junyanz/iGAN
IGAN
iGAN 是一个使用生成对抗网络（GAN）生成合成图像的框架。它提供了一个基于 Web 的界面，允许用户使用预训练模型在风景、建筑和时尚等类别中交互式地创建和编辑图像。
该系统通过潜在空间探索、插值和投影，实现了对视觉输出的精确控制。用户可以使用包含绘图、着色和变形画笔的交互式编辑器来引导生成过程，实时细化特定区域或形状。
该项目既支持基于边缘或颜色图的自动化脚本生成，也支持通过基于种子的候选选择进行手动精修。它还包含用于调试生成模型的诊断工具，通过可视化和探测其输出空间来辅助开发。
Features
- Generative Adversarial Image Synthesis - Implements a framework for high-resolution synthetic image synthesis using generative adversarial networks.
- Latent Vector Refinement - Updates the underlying latent representation in real-time based on user-drawn masks or brush strokes.
- Constraint-Based Image Synthesis - Provides the ability to produce synthetic images that match specific edge or color maps by optimizing latent vectors.
- Image-to-Latent Projections - Converts existing images into latent vectors using optimization or networks to enable generative manipulation.
- Latent Space Manipulations - Modifies latent representations of images to enable precise control over visual transitions and attribute interpolation.
- Generative Image Models - Uses pre-trained generative models to produce synthetic imagery across categories like landscapes, architecture, and fashion.
- Real-Time Image Generation - Enables the creation of synthetic images by guiding the generative process through manual input and real-time edits.
- Synthetic Image Generators - Provides a framework for producing model-based images across categories like landscapes and architecture using pre-trained networks.
- Semantic Image Synthesis - Produces synthetic images that adhere to specific semantic requirements like color or edge maps via automated scripts.
- Mask-Guided Image Editors - Offers a system for refining generated images using sketching, coloring, and warping brushes to guide the model.
- Generative Image Refinement - Provides coloring, sketching, and warping brushes to refine specific regions or shapes of generated images.
- Latent Space Interpolations - Calculates linear and spherical paths between latent vectors to create smooth visual transitions between images.
- Generative AI Interfaces - Provides a web-based tool for interactively creating and editing synthetic images using Generative Adversarial Networks.
- Scripted Generation - Supports producing multiple images based on specific color and edge maps through automated scripts.
- Latent Space Sampling - Generates a grid of varied image thumbnails by sampling different points around a specific region of the latent space.
- Generative Model Debuggers - Provides a visualization tool for analyzing the capabilities and limitations of a generative model through iterative output testing.
- Interpolation Visualizers - Provides a mechanism to visualize a sequence of transitions between a random image and a user edit via playback controls.
- Generated Result Selection - Allows users to browse and switch between multiple generated thumbnails to select the best result.
- Latent Space Explorers - Provides an interface for navigating and interpolating between latent vectors to visualize transformations in generative models.
- Generative Adversarial Networks - Interactive visual manipulation on the natural image manifold.
- Image Editing and Manipulation - Interactive visual manipulation on natural image manifolds.
- Image Generation - Interactive generative manipulation on natural image manifolds.
- Image Synthesis - Enables interactive visual manipulation on image manifolds.
