ComfyUI DAAM

ComfyUI custom nodes for Diffusion Attentive Attribution Maps (DAAM)

This extension enables visualization of cross-attention heatmaps within Stable Diffusion models, showing exactly which parts of the image correspond to specific words in the prompt — good for analyzing and debugging model outputs and LoRA training.

👉 Example workflows are available in workflows.

This project was adapted from the SD Web UI implementation. Special thanks to @kousw for the original work!

✨ Features

• ✅ Positive / Negative prompt heatmap visualization
• ✅ SDXL and SD 1.5 support
• ✅ Batched input support

🚀 Installation

Now Available on Comfy Registry and Custom Node Manager!

Manual Install

Clone this repo into your ComfyUI custom_nodes directory:

git clone https://github.com/nisaruj/comfyui-daam.git

Then install the required packages

cd comfyui-daam
python -s -m pip install -r requirements.txt

Restart ComfyUI.

🧩 DAAM Nodes

CLIPTextEncodeWithTokens

Identical to CLIPTextEncode but also outputs the tokenized prompt required for the analysis.

KSamplerDAAM

A hooked version of KSampler. During sampling, it records attention maps for later analysis.

Outputs:

• latent — standard latent output
• pos_heatmaps — positive prompt's raw heatmaps for input into the analyzer
• neg_heatmaps — negative prompt's raw heatmaps for input into the analyzer

DAAMAnalyzer

This node generates overlay heatmaps that show which parts of the image correspond to selected words in the prompt.

Inputs:

• clip — CLIP model used to encode the attention text
• tokens — from CLIPTextEncodeWithTokens
• heatmaps — from KSamplerDAAM
• images — the output images to overlay the heatmaps
• A text box for comma-separated words to generate heatmaps

Output:

• A batch of images with word-level heatmaps overlaid

📷 Example Output

Prompt: A photo of corgi with a cowboy hat riding a skateboard in the park

Attention words: corgi,skateboard,hat,park

📦 Changelog

• 0.3.0

  • Negative prompt support
  • Code Refactor and Minor bug fixes

• 0.2.0

  • Added support for batched inputs
  • SD 1.5 models compatibility
  • Bug fixes and stability improvements

• 0.1.1

  • Initial Version with SDXL support