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Awesome GitHub RepositoriesComputer Vision Guidance Frameworks
Algorithms for processing and transforming input data into control signals for generative models.
Distinguishing note: Focuses on the pre-processing and guidance signal generation for models, rather than the model training itself.
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- lllyasviel/ControlNet
lllyasviel/ControlNet
33,654View on GitHubControlNet is a framework for structural image generation that extends pre-trained diffusion models with neural network architectures designed for precise spatial control. By injecting structural guidance directly into the latent-space denoising process, the system enables users to enforce geometric or semantic constraints on generated outputs while maintaining style consistency. The framework distinguishes itself through a weight-locked copying mechanism that preserves the integrity of the original model while introducing new control signals. It supports multi-condition synthesis, allowing f
Transforms raw input images into specialized control maps to guide the output of generative models.
Python
