ComfyUI-WJNodes

ComfyUI-WJNodes

• This is a simple node package that I use myself. If there are new functions or suggestions, please provide feedback.
• If you want to use modified versions of other nodes, you need to install their corresponding dependencies

Node list:

• ImageFile: WJNode/ImageFile
  • ✅Load_Image_From_Path : Load image from path
  • ✅Save_Image_To_Path : Save image by overwriting the path
  • ✅Save_Image_Out : Save image to output and output the path
  • ✅Load_Image_Adv : Load image with mask inversion and path output, supports multiple formats (jpg, png, jpeg, webp, tiff, bmp, gif, ico, svg)
  • ✅image_url_download : Download images from URLs with configurable timeout, supports batch processing
• ImageEdit: WJNode/ImageEdit
  • ✅invert_channel_adv : Invert/separate image channels, RGBA to mask batch, replace channels, any channel to RGBA
  • ✅ListMerger : Merge multiple image lists into a single batch
  • ✅Bilateral_Filter : Image/Mask Bilateral Filtering: Can repair layered distortion caused by color or brightness scaling
  • ✅image_math : Image mathematical operations with expression support
  • ✅image_math_value : Image and value mathematical calculations
  • ✅Robust_Imager_Merge : Advanced image merging with robust handling
  • ✅image_scale_pixel_v2 : Advanced image scaling by total pixels with alignment, cropping, and bbox filling options
  • ✅image_scale_pixel_option : Generate advanced options for image_scale_pixel_v2 node
• Crop: WJNode/ImageEdit/image_crop
  • ✅adv_crop : Advanced cropping: can quickly crop/expand/move/flip images, can output background masks and custom filling
  • ✅Accurate_mask_clipping : Accurately find mask boundaries and optionally crop to those boundaries
  • ✅crop_by_bboxs : Crop images using bounding box data
• Mask Crop: WJNode/ImageEdit/mask_crop
  • ✅mask_crop_square : Square cropping based on mask data
  • ✅mask_crop_option_SmoothCrop : Smooth cropping with advanced options
  • ✅mask_crop_option_Basic : Basic mask cropping options
  • ✅crop_data_edit : Edit and modify crop data
  • ✅crop_data_CoordinateSmooth : Coordinate smoothing for crop data
• Mask Editing: WJNode/ImageEdit/MaskEdit
  • ✅mask_select_mask : Mask selection within a mask batch (intersection represents selection)
  • 🟩coords_select_mask : Coordinate selection of masks, used to assist SAM2 video keying (under development)
  • ✅mask_line_mapping : Mask line mapping, can automatically calculate maximum and minimum values when input is -1 or 256
  • ✅mask_and_mask_math : Mask to mask operations, supports addition/subtraction/intersection/multiplication operations,
    Adjustable cv2 and torch modes, if cv2 is not installed, automatically switches to torch
• Math: WJNode/Math
  • ✅any_math : Any data calculation, supports pure data input such as images/values/arrays, and outputs images or any data type
  • ✅any_math_v2 : Support arbitrary data calculation with more inputs and 3 sets of outputs
• Batch: WJNode/Batch
  • ✅Select_Images_Batch : Batch selection and recombination of images/masks with index support
  • ✅Select_Batch_v2 : Advanced batch selection with loop, limit, and processing options
  • ✅SelectBatch_paragraph : Paragraph-based batch selection
  • ✅Batch_Average : Average cutting of image/mask batches with division and completion options
• Color: WJNode/Color
  • ✅load_color_config : Load color configuration for color block to mask, supports ADE20K preprocessing color data
  • ✅color_segmentation : Color block to mask conversion, supports ADE20K and SAM2 data preprocessing
  • ✅color_segmentation_v2 : Enhanced color block to mask v2, uses keys in color configuration to select masks
  • ✅filter_DensePose_color : Filter DensePose color data
  • ✅load_ColorName_config : Load color name configuration
  • ✅Color_check_Name : Check color names and filter color data
  • ✅Color_Data_Break : Break down color data into components
• Video Merge: WJNode/video/merge
  • ✅Video_fade : Two video segments can choose two ways to fade in and out
  • ✅SaveMP4 : Save single video as MP4 format
  • ✅SaveMP4_batch : Save video batch as MP4 format
  • ✅Video_MaskBasedSplit : Split video based on mask data
  • ✅Detecting_videos_mask : Detect masks in video sequences
  • ✅Cutting_video : Cut video sequences based on segment data
  • ✅Video_OverlappingSeparation_test : Test overlapping separation in videos
• GetData: WJNode/GetData
  • ✅Mask_Detection : Mask detection: detect whether there is a mask, detect whether it is all hard edges,
    detect whether the mask is pure white/pure black/pure gray and output values 0-255
  • ✅get_image_data : Obtain image size data from images/masks (batch/width/height/channels/shape)
  • ✅get_image_ratio : Obtain image aspect ratio data (max/min dimensions, ratio float/string, ratio classification)
• Other Functions: WJNode/Other-functions
  • ✅Any_Pipe : Group any data, known bug: nested grouping will split
  • ✅Determine_Type : Display data type and determine data characteristics
• Other: WJNode/Other
  • 🟩Load value feature recognition model (e.g., nsfw, aesthetic score, AI value, time)
  • 🟩Input recognition model and image batch, output batch and corresponding feature values
  • 🟩Sort image batches through specified arrays (e.g., feature value arrays)
• Detection: WJNode/Other-plugins/Detection
  • ✅load_torchvision_model : Load pre-trained torchvision models (ResNet, DenseNet, etc.) for feature extraction
  • ✅Run_torchvision_model : Calculate similarity between images using loaded models and various distance metrics
• Hardware: WJNode/Other-node
  • ✅Graphics_Detection_Reference : Test GPU computing capabilities including hardware info, precision tests, memory bandwidth,
    operator performance, and AI benchmarks with RTX 4090 comparison
• WAS Plugins: WJNode/Other-plugins/WAS (To use the following nodes, you must install WAS plugin)
  • ✅WAS_Mask_Fill_Region_batch : Optimize WAS plugin's WAS_Mask_Fill_Region (mask cleanup) to support batches
    Thanks to @WASasquatch
• Impact Pack Plugins: WJNode/Other-plugins (To use the following nodes, you must install Impact Pack plugin)
  • ✅SegmDetectorCombined_batch : Optimize impact-pack plugin's SegmDetectorCombined (segm detection mask) to support batches
    Thanks to @ltdrdata
  • ✅bbox_restore_mask : Add impact-pack plugin's seg decomposition, restore cropped images through cropping data (SEG editing)
  • ✅Sam2AutoSegmentation_data : Add Sam2AutoSegmentation (kijai) node's color list/coordinate output, used to assist SAM2 video keying
    Thanks to @kijai
  • ✅run_yolo_bboxs : Run YOLO detection and return bounding boxes
  • ✅run_yolo_bboxs_v2 : Enhanced YOLO detection with additional features
• EasyOCR Plugins: WJNode/Other-plugins/EasyOCR (To use the following nodes, you must install EasyOCR)
  • ✅load_EasyOCR_model : Load OCR models separately for faster operation and model caching
  • ✅ApplyEasyOCR_batch : Modify OCR recognition nodes to support batch processing
    Thanks to @prodogape
• Path: WJNode/Path
  • ✅ComfyUI_Path_Out : Output ComfyUI common paths (root, output/input, plugins, models, cache, Python environment)
  • ✅Str_Append : Add prefix/suffix to strings (reference KJNode)
  • ✅del_file : Detect whether file or path exists, whether to delete file, operation requires input signal, deletion requires write permission
  • ✅Split_Path : Path slicing, input path, output: disk symbol/path/file/extension + detect whether it is a file
  • ✅Folder_Operations_CH : Folder operations with Chinese support

Models Directory (Optional)

These models are automatically downloaded to ComfyUI's models directory and shared with other plugins:

models/
├── torchvision/              # Torchvision models for similarity detection
│   └── resnet/
│       ├── resnet50-11ad3fa6.pth
│       └── ...
├── EasyOCR/                  # OCR models
│   ├── craft_mlt_25k.pth
│   ├── latin_g2.pth
│   └── zh_sim_g2.pth
└── sam2/                     # SAM2 models (if using SAM2 features)
    ├── sam2_hiera_small.safetensors
    └── ...

Installation

1. Clone or download this repository to your ComfyUI custom_nodes directory:

cd ComfyUI/custom_nodes
git clone https://github.com/807502278/ComfyUI-WJNodes.git

2. Install dependencies (optional, most are already included in ComfyUI):

cd ComfyUI-WJNodes
pip install -r requirements.txt