ComfyUI-Buff-Nodes

Several quality-of-life batch operation and string manipulation nodes.

WORK IN PROGRESS

In part written with Claude-3.7-Sonnet in a human in-the-loop development standard.

File Path Selector Node

The FilePathSelectorFromDirectory node is a utility for ComfyUI that helps you select files from a specified directory.

• Directory Selection: Choose any directory on your system to scan for files
• File Type Filtering: Specify which file extensions to include (e.g., "mp4,jpg,png")
• Selection Modes:
  • Randomize: Pick a random file from the directory (can be seeded for reproducibility)
  • Sequential: Go through files one by one in alphabetical order, remembering position between runs
• Subdirectory Support: Optionally search through subdirectories for matching files
• Persistent Memory: Tracks the sequential position between ComfyUI sessions
• Caching: Efficient file list caching with configurable duration

String Processor Node

The StringProcessor node allows you to manipulate text strings with various operations:

• Operations:
  • First/Last N Characters: Extract the first or last specified number of characters
  • First/Last N Words: Extract the first or last specified number of words using a custom delimiter
  • Custom Expression: Use Python expressions to transform strings with full flexibility
• Features:
  • Custom word delimiters
  • Comprehensive tooltips with examples
  • Error handling for custom expressions

Console Output Node

The ConsoleOutput node provides a simple way to display text in the console:

• Features:
  • Custom prefix to identify your outputs
  • Optional timestamps
  • Acts as a terminal output node in workflows
  • Useful for debugging or logging information

Most Recent File Selector Node

The MostRecentFileSelector node finds the most recently modified file in a specified directory:

• Features:
  • Automatically detects the most recently modified file in a directory
  • Optional file type filtering using comma-separated extensions
  • Can create a black initialization image if no file is found
  • Configurable black image dimensions and format
• Input Options:
  • Directory Path: Path to search for files (defaults to ComfyUI's input directory)
  • File Types: Optional comma-separated list of file extensions to filter by (e.g., "png,jpg")
  • Create Init Image: Option to create a black image if no file is found
  • Init Image Settings: Configurable width, height, and format (png/jpg) for the black image
• Output:
  • Returns the full path to the most recent file
  • Returns an empty string if no file is found and init image creation is disabled
  • Creates and returns path to a black image if no file is found and init image creation is enabled
• Behavior:
  • Always re-executes when the workflow is queued
  • Handles missing directories gracefully
  • Provides detailed console logging for debugging

Two Image Concatenator Node

Note: The following node is for the use of TemporalNet2 in video streaming workflows

The TwoImageConcatenator node combines two 3-channel images into a single 6-channel image:

• Features:
  • Concatenates two input images along the channel dimension
  • Maintains batch processing capability
  • Useful for temporal models that require both previous and current frames
  • Preserves image dimensions while doubling the channel count
• Input Requirements:
  • Both images must have the same batch size, height, and width
  • Both images must be 3-channel images
• Output:
  • Single 6-channel image tensor (batch, height, width, 6 channels)

Frame Rate Modulator Node

The FrameRateModulator node allows you to modify the frame rate of image sequences by resampling frames:

• Features:
  • Mode Selection: Choose between exact frame count or multiplier-based resampling
  • Frame Count Mode: Set a specific target number of output frames
  • Multiplier Mode: Scale input frame count by a factor (2.0 = slow motion, 0.5 = speed up)
  • Interpolation Methods:
    • Nearest: Simple frame duplication/skipping (fastest)
    • Linear: Smooth blending between adjacent frames
    • Cubic: High-quality cubic interpolation for smooth motion
  • Loop Modes for handling edge cases:
    • Clamp: Use first/last frame for out-of-bounds positions
    • Repeat: Loop the sequence seamlessly
    • Mirror: Reverse and repeat for ping-pong effect
• Input Requirements:
  • Batch of images in ComfyUI format (batch, height, width, channels)
• Output:
  • Resampled image sequence with target frame count
  • Frame count as integer for downstream processing
• Use Cases:
  • Creating slow motion effects (50 frames → 75 frames)
  • Speeding up sequences (50 frames → 25 frames)
  • Standardizing frame counts across different clips
  • Temporal upsampling with smooth interpolation

Raft Optical Flow Node

Note: The following node is for the use of TemporalNet2 in video streaming workflows

The RaftOpticalFlowNode calculates optical flow between two images using the RAFT (Recurrent All-Pairs Field Transforms) model:

• Features:
  • Uses the state-of-the-art RAFT model for optical flow estimation
  • Processes images in batches
  • Automatically handles device placement (CPU/GPU)
  • Produces a visualization of motion between frames
• Input Requirements:
  • Two input images (typically previous and current frames)
  • Images should be in ComfyUI's standard format (batch, height, width, channels)
• Output:
  • Optical flow visualization as an image
  • Color-coded representation of motion between frames
  • Output is normalized to [0,1] range

Use Cases

• Randomly selecting input files for processing
• Creating workflows that process batches of files in sequence
• Manipulating text data within workflows (filenames, prompts, metadata)
• Extracting portions of text from larger strings
• Debugging workflows by logging intermediate values to the console
• Formatting and transforming text for use in prompts or file operations
• Processing video frames for motion analysis
• Combining multiple image channels for temporal models
• Visualizing motion between consecutive frames
• Finding the latest output from a previous workflow run
• Creating initialization images for new workflows
• Monitoring directories for new files
• Setting up automated workflows that process the most recent file

Technical Details

The File Path Selector node saves its sequential position state to a JSON file, allowing it to remember where it left off even if you restart ComfyUI. When using the randomize mode with a seed, you'll get consistent, reproducible selections.

The String Processor supports Python expressions that give you the full power of string manipulation in a controlled environment.

The Raft Optical Flow Node uses the RAFT model from torchvision, which provides high-quality optical flow estimation. The model is automatically downloaded when first used and cached for subsequent runs.