ComfyUI Extension: Comfyui-QwenEditUtils

Authored by lrzjason

Created

Updated

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A collection of utility nodes for Qwen-based image editing in ComfyUI.

Custom Nodes (2)

README

Comfyui-QwenEditUtils

A collection of utility nodes for Qwen-based image editing in ComfyUI.

Example

<p align="center"> <img src="example.png" alt="Example Workflow" width="45%" /> <img src="result.png" alt="Result Image" width="45%" /> </p>

You can find a complete ComfyUI workflow example in the qwen-edit-plus_example.json file. This workflow demonstrates how to use the TextEncodeQwenImageEditPlus node with two reference images to create an outfit transfer effect.

Update Log

v1.1.7

  • Use 1,2,3 instead of 0,1,2 for the pro node resize logic

v1.1.6

  • Add new node for new image resize handling

v1.1.5

  • Rollback the vl resize and not resize output sequence

v1.1.4

  • Updated crop method pad to preserve most of the image
  • Add CropWithPadInfo to crop generated image with pad info
  • Add the initial version node for running hub

Node

TextEncodeQwenImageEditPlus 小志Jason(xiaozhijason)

This node provides text encoding functionality with reference image support for Qwen-based image editing workflows. It allows you to encode prompts while incorporating up to 5 reference images for more controlled image generation.

Inputs

  • clip: The CLIP model to use for encoding
  • prompt: The text prompt to encode
  • vae (optional): The VAE model for image encoding
  • image1 (optional): First reference image for image editing
  • image2 (optional): Second reference image for image editing
  • image3 (optional): Third reference image for image editing
  • image4 (optional): Fourth reference image for image editing
  • image5 (optional): Fifth reference image for image editing
  • enable_resize (optional): Enable automatic resizing of the reference image for VAE encoding
  • enable_vl_resize (optional): Enable automatic resizing of the reference image for VL encoding
  • llama_template (optional): Custom Llama template for image description and editing instructions

Outputs

  • CONDITIONING: The encoded conditioning tensor
  • image1: The processed first reference image
  • image2: The processed second reference image
  • image3: The processed third reference image
  • image4: The processed fourth reference image
  • image5: The processed fifth reference image
  • LATENT: The encoded latent representation of the first reference image

Behavior

  • Encodes text prompts using CLIP with optional reference image guidance
  • Supports up to 5 reference images for complex editing tasks
  • Automatically resizes reference images to optimal dimensions for both VAE and VL encoding
  • Integrates with VAE models to encode reference images into latent space
  • Supports custom Llama templates for more precise image editing instructions
  • Processes images separately for VAE encoding (1024x1024) and VL encoding (384x384)
  • Returns individual processed images for more flexible workflow connections

TextEncodeQwenImageEditPlusAdvance 小志Jason(xiaozhijason)

This advanced node provides enhanced text encoding functionality with reference image support for Qwen-based image editing workflows. It offers more precise control over image resizing and supports flexible image input configurations with separate processing for VAE and VL encoding.

Inputs

  • clip: The CLIP model to use for encoding
  • prompt: The text prompt to encode
  • vae (optional): The VAE model for image encoding
  • vl_resize_image1 (optional): First reference image for VL encoding with resizing
  • vl_resize_image2 (optional): Second reference image for VL encoding with resizing
  • vl_resize_image3 (optional): Third reference image for VL encoding with resizing
  • not_resize_image1 (optional): First reference image without VL resizing
  • not_resize_image2 (optional): Second reference image without VL resizing
  • not_resize_image3 (optional): Third reference image without VL resizing
  • target_size (optional): Target size for VAE encoding (options: 1024, 1344, 1536, 2048, 768, 512)
  • target_vl_size (optional): Target size for VL encoding (default: 384)
  • upscale_method (optional): Method for upscaling images (options: "lanczos", "bicubic", "area")
  • crop (optional): Cropping method (options: "center", "disabled")
  • instruction (optional): Custom instruction for image editing

Outputs

  • CONDITIONING: The encoded conditioning tensor
  • LATENT: The encoded latent representation of the first reference image
  • target_image1: The processed first target reference image
  • target_image2: The processed second target reference image
  • target_image3: The processed third target reference image
  • vl_resized_image1: The first VL-resized reference image
  • vl_resized_image2: The second VL-resized reference image
  • vl_resized_image3: The third VL-resized reference image

Behavior

  • Provides advanced text encoding with separate control over VAE and VL image processing
  • Supports 3 reference images with different resize behaviors
  • Offers multiple target size options for more flexible image processing
  • Maintains separate image outputs for VAE-encoded and VL-resized images
  • Provides enhanced upscale and crop controls for optimal image processing
  • Integrates with custom instructions for tailored image editing

TextEncodeQwenImageEditPlusPro 小志Jason(xiaozhijason)

This professional node provides the most flexible text encoding functionality with reference image support for Qwen-based image editing workflows. It offers fine-grained control over which images are VL-resized and includes a main image designation for focused conditioning.

Inputs

  • clip: The CLIP model to use for encoding
  • prompt: The text prompt to encode
  • vae (optional): The VAE model for image encoding
  • image1 (optional): First reference image for image editing
  • image2 (optional): Second reference image for image editing
  • image3 (optional): Third reference image for image editing
  • image4 (optional): Fourth reference image for image editing
  • image5 (optional): Fifth reference image for image editing
  • vl_resize_indexs (optional): Comma-separated indexes of images to apply VL resizing (default: "0,1,2")
  • main_image_index (optional): Index of the main reference image for focused conditioning (default: 0)
  • target_size (optional): Target size for VAE encoding (options: 1024, 1344, 1536, 2048, 768, 512)
  • target_vl_size (optional): Target size for VL encoding (options: 384, 392)
  • upscale_method (optional): Method for upscaling images (options: "lanczos", "bicubic", "area")
  • crop_method (optional): Cropping method (options: "pad", "center", "disabled")
  • instruction (optional): Custom instruction for image editing

Outputs

  • CONDITIONING: The encoded conditioning tensor with all reference latents
  • LATENT: The encoded latent representation of the main reference image
  • image1: The processed first reference image
  • image2: The processed second reference image
  • image3: The processed third reference image
  • image4: The processed fourth reference image
  • image5: The processed fifth reference image
  • CONDITIONING: The encoded conditioning tensor with only the main reference latent
  • ANY: The pad information dictionary containing scaling and padding details

Behavior

  • Provides professional-level text encoding with maximum flexibility for image processing
  • Supports up to 5 reference images with configurable VL-resizing per image
  • Allows designation of a main reference image for focused conditioning
  • Offers separate conditioning outputs for full reference and main reference conditioning
  • Provides multiple target size options for more flexible image processing
  • Includes pad information for potential image cropping and scaling operations
  • Provides enhanced upscale and crop controls, including padding for image preservation

Key Features

  • Multi-Image Support: Incorporate up to 3 reference images into your text-to-image generation workflow
  • Dual Resize Options: Separate resizing controls for VAE encoding (1024px) and VL encoding (384px)
  • Individual Image Outputs: Each processed reference image is provided as a separate output for flexible connections
  • Latent Space Integration: Encode reference images into latent space for efficient processing
  • Qwen Model Compatibility: Specifically designed for Qwen-based image editing models
  • Customizable Templates: Use custom Llama templates for tailored image editing instructions

Installation

  1. Clone or download this repository into your ComfyUI's custom_nodes directory.
  2. Restart ComfyUI.
  3. The node will be available in the "advanced/conditioning" category.

Update Log

v1.1.3

  • Updated crop method pad to preserve most of the image
  • Add CropWithPadInfo to crop generated image with pad info

v1.0.6

  • Updated advance node

v1.0.5

  • Updated node to support separate enable_vl_resize parameter
  • Modified return types to provide 5 individual IMAGE outputs instead of a single combined output
  • Improved image processing logic with separate handling for VAE and VL encoding
  • Enhanced documentation to accurately reflect node inputs and outputs
  • Fixed latent output handling to properly return first reference image latent

v1.0.1

  • Initial release with basic text encoding and single image reference support

Contact

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