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The TextEncodeQwenImageEditPlus node processes text prompts and optional images to generate conditioning data for image generation or editing tasks. It uses a specialized template to analyze input images and understand how text instructions should modify them, then encodes this information for use in subsequent generation steps. The node can handle up to three input images and optionally generate reference latents when a VAE is provided.

Inputs

Note: When a VAE is provided, the node generates reference latents from all provided input images. Up to three images can be processed at once. Images are scaled to a target area of 384x384 pixels (aspect ratio preserved) for vision-language processing, and to dimensions divisible by 8 (with a target area of 1024x1024 pixels) for VAE encoding.

Outputs

This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! Edit on GitHub

Source fingerprint (SHA-256): 5eea53a84045924b44d445244e6149b341188d22573aaaced87bac8a139dac96