FM_nodes

A collection of ComfyUI nodes.

Click name to jump to workflow

1. WFEN Face Restore. Paper: Efficient Face Super-Resolution via Wavelet-based Feature Enhancement Network
2. RealViformer - Paper: Investigating Attention for Real-World Video Super-Resolution
3. ProPIH. Paper: Progressive Painterly Image Harmonization from Low-level Styles to High-level Styles
4. CoLIE. Paper: Fast Context-Based Low-Light Image Enhancement via Neural Implicit Representations
5. PCSR. Paper: Accelerating Image Super-Resolution Networks with Pixel-Level Classification

Workflows

WFEN

Download the model here and place it in models/wfen/WFEN.pth.

workflow_wfen_facecrop.json

RealViformer

Download the model here and place it in models/realviformer/weights.pth.

workflow_realviformer.json

(Not a workflow-embedded image)

https://github.com/user-attachments/assets/e89003c0-7be5-4263-b281-fd609807cea1

RealViFormer upscale example

ProPIH

Download the vgg_normalised.pth model in the Installation section and latest_net_G.pth in the Train/Test section

models/propih/vgg_normalised.pth
models/propih/latest_net_G.pth

workflow_propih.json

CoLIE

No model needed to be downloaded. Lower loss_mean seems to result in brighter images. Node works with image and batched/video.

workflow_colie_lowlight.json

PCSR

Download models from https://github.com/3587jjh/PCSR/tree/main/save

carn-pcsr-phase1/iter_last.pth
fsrcnn-pcsr-phase1/iter_last.pth
srresnet-pcsr-phase1/iter_last.pth

and place them here:

models/carn_pcsr/iter_last.pth
models/fsrcnn_pcsr/iter_last.pth
models/srresnet_pcsr/iter_last.pth

Install dependencies

pip install fast-pytorch-kmeans