qinglong_controlnet-lllite
| Property | Value |
|---|---|
| License | CC-BY-NC-SA 4.0 |
| Framework | Diffusers |
| Downloads | 26,705 |
| Author | bdsqlsz |
What is qinglong_controlnet-lllite?
qinglong_controlnet-lllite is a specialized ControlNet implementation designed for anime-style image processing. It offers multiple variants trained on specific tasks including AnimeFaceSegment, Normal mapping, T2i-Color/Shuffle, and lineart anime denoise capabilities.
Implementation Details
The model is built on the Diffusers library and supports ONNX runtime, making it highly efficient for deployment. It's primarily trained on anime-style content and uses base models like Kohaku-XL and ProtoVision XL for different variants.
- Supports multiple preprocessing methods including anime face segmentation
- Implements various control types: depth mapping, line art, color manipulation
- Compatible with ComfyUI and sd-webui-controlnet extension
Core Capabilities
- Anime face segmentation and processing
- Depth-aware image generation using Marigold
- Line art conversion and enhancement
- Color palette manipulation and recoloring
- Tile-based processing with α and β versions for different use cases
Frequently Asked Questions
Q: What makes this model unique?
The model's specialization in anime-style processing and its lightweight nature (LLLite) make it particularly efficient for specific use cases. It offers multiple control types in a single framework, from face segmentation to tile-based processing.
Q: What are the recommended use cases?
The model excels in anime-style image manipulation, particularly in tasks like face segmentation, line art conversion, and color manipulation. It's especially useful for artists working with anime-style content and requires less computational resources than full ControlNet models.
