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Complex Image Generation Workflow
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This workflow appears to represent a complex image generation process utilizing various nodes for image processing, masking, latent space encoding/decoding, text conditioning, and noise application. The sequence ends with image blending and saves the outputs. It employs models like CLIPSeg for masking, a VAE for encoding/decoding images to/from latent space, KSampler for sampling in latent space with conditioning, and upscales the images using models. The workflow integrates iterative refinement stages with conditional inputs influencing image characteristics, likely to generate high-quality, refined images based on text prompts and model guidance.
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