ComfyUI Nodes for External Tooling

Provides nodes and API geared towards using ComfyUI as a backend for external tools.

Nodes for sending and receiving images

ComfyUI exchanges images via the filesystem. This requires a multi-step process (upload images, prompt, download images), is rather inefficient, and invites a whole class of potential issues. It's also unclear at which point those images will get cleaned up if ComfyUI is used via external tools.

Load Image (Base64)

Loads an image from a PNG embedded into the prompt as base64 string.

Inputs: base64 encoded binary data of a PNG image
Outputs: image (RGB) and mask (alpha) if present

Load Mask (Base64)

Loads a mask (single channel) from a PNG embedded into the prompt as base64 string.

Inputs: base64 encoded binary data of a PNG image
Outputs: the first channel of the image as mask

Send Image (WebSocket)

Sends an output image over the client WebSocket connection as PNG binary data.

Inputs: the image (RGB or RGBA)

This will first send one binary message for each image in the batch via WebSocket:

12<PNG-data>

That is two 32-bit integers (big endian) with values 1 and 2 followed by the PNG binary data. There is also a JSON message afterwards:

{'type': 'executed', 'data': {'node': '<node ID>', 'output': {'images': [{'source': 'websocket', 'content-type': 'image/png', 'type': 'output'}, ...]}, 'prompt_id': '<prompt ID>}}

Nodes for working on regions

When integrating ComfyUI into tools which use layers and compose them on the fly, it is useful to only receive relevant masked regions.

Crop Image

Crops an image. (ComfyUI has a CropMask node, this is the same for images.)

Inputs: image, x and y offset, width and height
Outputs: image in the region (x, y) -> (x + width, y + height)

Apply Mask to Image

Copies a mask into the alpha channel of an image.

Inputs: image and mask
Outputs: RGBA image with mask used as transparency

API for model inspection

There are various types of models that can be loaded as checkpoint, LoRA, ControlNet, etc. which cannot be used interchangeably. The following API helps to categorize and filter them.

/etn/model_info

Lists available models with additional classification info.

Paramters: none

Output: list of model files

{
    "checkpoint_file.safetensors": {
        "base_model": "sd15"|"sd20"|"sd21"|"sdxl"|"ssd1b"|"svd",
        "is_inpaint": true|false,
        "is_refiner": true|false
    },
    ...
}

The entry is {"base_model": "unknown"} for models which are not in safetensors format or do not match any of the known base models.

Note: currently only supports checkpoints. May add other models in the future.

Installation

Download the repository and unpack into the custom_nodes folder in the ComfyUI installation directory.

Or clone via GIT, starting from ComfyUI installation directory:

cd custom_nodes
git clone https://github.com/Acly/comfyui-tooling-nodes.git

Restart ComfyUI and the nodes are functional.

SeedV/comfyui-tooling-nodes