lllyasviel/ControlNet
ControlNet
Let us control diffusion models!
Builder
lllyasviel
lllyasviel • individual
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33,780
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Forks
3,001
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0/100
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Created
Feb 1, 2023
Project creation date
README Summary
ControlNet is a neural network structure that adds spatial conditioning controls to large, pretrained text-to-image diffusion models. It allows users to control the generation process using additional input conditions like edge maps, depth maps, segmentation maps, and human poses while preserving the quality and capabilities of the original model.
AI Dev Skills
Unmapped
Diffusion ModelsConditional Image GenerationNeural Network Architecture DesignComputer VisionImage-to-Image TranslationSpatial ConditioningTransfer LearningDeep Learning Model Control
Tags
Diffusion ModelsConditional Image GenerationNeural Network Architecture DesignComputer VisionImage-to-Image TranslationSpatial ConditioningTransfer LearningDeep Learning Model ControlControllable AI GenerationDigital ArtResearch EnvironmentPose-guided Human Image SynthesisCloud APIEdge-guided Image CreationFoundation Model ControlGame DevelopmentArchitecture VisualizationCreative IndustriesFilm/VFXMultimodal ConditioningStyle Transfer with Structural PreservationSelf-hostedImageDepth-conditioned Scene GenerationArchitectural Rendering ControlFashion DesignControlled Image GenerationMultimodalPython
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Recent Activity
Updated 2 years ago
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Quality
research- Quality
- high
- Maturity
- research
Categories
Learning ResourcesPrimaryNLP & TextCoding & Dev ToolsData Science & AnalyticsMultimodal AIEdge & Mobile AISearch & KnowledgeOther AI / MLFoundation ModelsGenerative MediaComputer Vision
PM Skills
Product Discovery
Languages
Python100.0%
Timeline
- Project created
- Feb 1, 2023
- Forked
- Mar 22, 2026
- Your last push
- 2 years ago
- Upstream last push
- 2 years ago
- Tracked since
- Feb 25, 2024
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