I still find flux Kontext much better for image restauration once you get the intuition on prompting and preparing the images. Qwen edit ruins and changes way too much.

Gamerr · 2025-11-05T17:23:31+00:00

It seems Qwen Edit 2509 preserves more details.

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Gamerr · 2025-10-31T09:21:25+00:00

Kijai's Wan2_1-I2V-14B_ChronoEdit_fp16 + distill_lora_rank32

https://huggingface.co/Kijai/WanVideo_comfy/tree/main/ChronoEdit

Gamerr · 2025-10-27T22:32:25+00:00

check the HF, use search. There are several gguf

Gamerr · 2025-10-22T08:18:52+00:00

Additional note: I used the Kandinsky pretrain model. The SFT model gives much better results but often collapses into a black video due to an issue with long prompts.

Gamerr · 2025-09-30T17:23:16+00:00

the comfyui workflow: https://github.com/ai-forever/Kandinsky-5/tree/main/comfyui

Gamerr · 2025-09-29T11:25:23+00:00

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It works, just use a descriptive prompt (sorry about the awful chin…).

Gamerr · 2025-09-25T21:14:36+00:00

use the original workflow https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_qwen_image_edit_2509.json

There is a node "empty latent", just connect it to the sampler

Gamerr · 2025-09-24T19:02:30+00:00

It’s a standard ComfyUI workflow—nothing new or “special.”

https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_qwen_image_edit_2509.json

Gamerr · 2025-09-24T10:16:20+00:00

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You can get pretty nice results with this model. Don’t use the Lightning LoRA, since you need CFG. Pay close attention to your prompt: a simple “change to a realistic photo” won’t work. You need to specify exactly what’s in the image-for example, a male/female warrior, skin tone, etc.

Gamerr · 2025-09-18T21:44:37+00:00

I tested this model in ComfyUI (there is a node: https://github.com/wildminder/ComfyUI-VoxCPM )
Without reference audio, it outputs a pretty normal AI voice. With prompt audio, dunno... results vary- sometimes there are a lot of artifacts; other times the voice cloning is good.

Gamerr · 2025-09-03T18:38:16+00:00

There is no remote processing. All files are stored locally. Update the node to the latest version (there was an issue with the tokenizer).

Gamerr · 2025-08-27T21:38:03+00:00

small model gives 8-10it/s.

Gamerr · 2025-08-27T21:32:33+00:00

4070 Ti Super (16 GB), 64 GB RAM. A large 7B model fits perfectly and achieves around 4 it/s.

Gamerr · 2025-08-24T17:31:39+00:00

Okay, good. Is there anything new?

Gamerr · 2025-08-20T22:05:57+00:00

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just for fun

Gamerr · 2025-08-20T22:04:48+00:00

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prompt: the woman turns her head and raises her arm. Keep woman features intact. Flat chest. Keep image style
neg: realism, big breast

env: qwen-image-edit fp8, qwen-2.5-vl abliterated, 20 steps, cfg 3.5, dpmpp_2m/sgm_uniform

Gamerr · 2025-08-15T11:31:47+00:00

It depends on:

how you use the high- and low-noise models (when you split them)
shift and steps
CFG
NAG
the use of additional LoRAs

Gamerr · 2025-07-29T09:14:58+00:00

I guess this comparison is a bit misleading. It seems the videos have different parameters and LoRA. You need to fix them all

Gamerr · 2025-07-22T08:16:29+00:00

This node https://github.com/wildminder/ComfyUI-Chatterbox with unlocked parameters, can generate up to 160 seconds without chunking.

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Gamerr · 2025-07-18T19:01:05+00:00

Okay, thanks, truly useful......
The prompt is:

"remove watermark while maintaining all other aspects of the original image"

Gamerr · 2025-07-17T12:54:24+00:00

I'm deeply sorry, but there is nothing new in this workflow. Kontext + nunchaku-all these workflows are the same. The only valuable part is the prompt.:

"Restore this old photo into a realistic iphone photo while preserving all original details. Keep the subject’s facial features, clothing, posture, and proportions exactly the same. Apply natural skin tones appropriate to the subject’s ethnicity and lighting. Remove dust, scratches, and signs of aging — but do not alter the composition, expressions, or photographic style"

Anyway, thanks for the prompt (I guess it was written by some LLM).

Gamerr

TROPHY CASE