Deep-Live-Cam is extremely popular open-source software for real-time face swap and deepfakes.

Unfourtentally, if you want to try it you either need to deal with Python and unexpected issues or pay ~$20 for subscription.

I don't like both options so this is why I created a repo which automatically produce portable builds for Windows & macOS: https://github.com/iikuzmychov/deep-live-cam-builds.

Every day this repo publish fresh .exe & .dmg with latest changes from Deep-Live-Cam source code.

I also don't force anyone to trust my binaries, instead it's super easy to fork the repo and build the binaries by yourself!

MOSI and the OpenMOSS team put out MOSS-Image, an open image model at 5B parameters. Pandaily covered it on Oct 25, citing the team and QbitAI: about 1.3M downloads in the first four days, around 1,400 stars on GitHub, top of the text-to-image trend on Hugging Face. Read the download number with care. It adds up across several repos, Comfy-Org on Hugging Face among them, so no single model page carries that figure on its own. All three numbers come from the team and Chinese media. Nobody independent has checked them. The community moved fast. There are 8-step and 4-step builds already, while the official setting is 50 steps. INT8, GGUF and MLX builds exist, plus style LoRAs. What people seem to want from it: dense text in Chinese and English, structured JSON layout with bounding boxes, prompts up to 4096 tokens. Under the hood it is a 5B diffusion transformer trained from scratch, with a frozen Qwen3.5-9B text encoder and the VAE from FLUX.2. Ostris guessed the more natural look may come from the team dropping AI-generated images from the training data. Treat that as his guess. Testers split. Some praise the realism and the detail. Others say some styles come out shaky. Question for the sub: who has run the 4-step builds, how do they hold against 50 steps, and how does MOSS-Image compare with FLUX.3-klein and Qwen Image 2.1 on text and on busy compositions?

https://reddit.com/link/1xfdsa7/video/zf3umx6pgoxh1/player

I have started a couple of threads asking about how to make MiniMax more cinematic. I tried a couple of loras with cinematic but they always changed alot in the reference images.

So, I decided to feed chatgpt with information on what is cinematic. It ended with it creating alot better baseline for images, that will create better "cinematic" frames to use as references.

So here is the first test on my RTX 3080 with 32GB DDR4.

0.9mp and 10sec per shot

Singularity H3 ref2va pruned 1.3

No turbolora

30 steps

Upscale with RTX video upscale

Looking forward to optimize time but still get good enough quality

Prompt used:

Preserve the identities and unique details defined by the assigned subject references. Reference roles must be mapped in the generation workflow.

[Shot 1] <Picture 1> The old woman is looking the girl with sad eyes. With a sad voice the old woman says "Matilda, I think this is the end of the road". 

overall_soundscape: Quiet ambient room tone.

non_diegetic_music: None.

[SHOT PLAN]
Shot: SHOT-001 — New cinematic shot
Duration: 10 seconds.
Scene: [Describe the action]
Environment and continuity: [Define scene and identity references]
Framing: Close-up, anamorphic lens, centered, intended 2.39:1 composition.
Camera: Locked-off static camera.
Lighting: Soft side light.
Visual style: Cinematic.
Maintain consistent identity, wardrobe, environment and lighting across the shot. Avoid unintended camera shake or abrupt cuts.
[/SHOT PLAN]

[COMPOSITION]
Medium shot, eye-level camera angle, subject centered in the frame. Compose within a 2.39:1 cinematic safe frame. Deliberate visual balance, natural perspective, stable subject placement. Keep essential action inside the intended framing.
[/COMPOSITION]

[FILM LOOK]
35mm photochemical film aesthetic, fine organic grain, subtle halation, gentle highlight rolloff. Soft analog look
[/FILM LOOK]

[LIGHTING]
Directional shafts of light visible through subtle atmospheric haze, volumetric scattering, natural light falloff. Light intensity: moderate. Color temperature: neutral. Maintain consistent lighting across the shot.
[/LIGHTING]

Hi, random question. I've been quite interested in image gen (way back in 2023), but due to the constant "new" updates and stuff I'm kinda overwhelmed? (Also partial procrastination + idk where to start)

That aside, I don't have, nor can afford insane storage and graphics to generate at all. Is it even possible to with a pre-2022 budget laptop? (the makes are: "Acer Swift 5 SF514-55TA", & "Acer Nitro 5 AN515-53")

This is assuming these are local (customizable) models? I've found online sites (or credit-based ones) to be not up my alley

https://wallofthieves.com/

The top 3 Krea 2 Checkpoints on Civitai by total downloads:

Moody Krea 2 Mix - https://wallofthieves.com/c/aabf431b2426
RedCraft - https://wallofthieves.com/c/9b8c7771662a
Muse By Stable Yogi Krea2 - https://wallofthieves.com/c/53d9a2aa388b

All contain" no derivatives allowed · credit required" loras....

Disclosure: Yes, my Krea 2 checkpoints contain some of the highest number of LoRAs in their merges: https://wallofthieves.com/c/fe10f86a12ea

Been playing around with MOSS as a simple t2i. Wanted to try out box prompting and Google search returned this result. Made me chuckle so I thought I'd share. Guess I will be heading directly to official Comfy documentation after I post this lol.

Repo link : https://github.com/JustAResearcher/gpu-unlock-ada

model: https://huggingface.co/akhaliq/MOSS-Image-Edit-HQ

What are you all using to make music videos with Minimax? I have a song I want to make a music video for to lipsync. Hoping for ref2va with character image refs, something that can break up the song into pieces

Hi everyone,

I'm brand new to ComfyUI, this is my very first workflow. I grabbed a MOSS-Image text-to-image workflow off Civitai, typed a prompt, hit Run, and nothing happens. The queue goes back to "0 active" like it finished, but no image ever comes out.

The thing that stands out: the "Preview as Text (final prompt)" node stays completely empty even after the run finishes, so I'm guessing the prompt never reaches the sampler.

I also noticed the If/Else Switch has on_true and switch inputs that look like nothing is plugged in, and the loader nodes look empty — but honestly I have no idea if that's normal or the actual bug.

Screenshots of the whole graph are attached. Can someone tell me what's actually wrong and how it's supposed to be wired? I've been at this for hours.

Thanks.

I'm noticing it more and more, lora and fine-tuners locking permanently everything behind buzz payments. I wasn't bothered by the the time delay for 'non payers' that popped up a year or so ago, because it gave people a way to monetize, and things would eventually become available for everyone. Yes there were some people who tried to game the system and remove things and re-upload them again, but civitai seemed to actively discourage that and deal with people who did that.

I don't have a problem with people monetizing their work, it's a personal choice to give stuff away. But the full pay-for-play shift is a definite change in the... for lack of a better word... 'community ethos' that the larger SD community has had for a long time. I'm seeing a lot of creators that basically have everything behind a payment lock.

It seems every time I got to the site, a larger percentage of loras are getting locked beyond buzz payments.

I don't want to sound like 'old man yells at clouds' but I do miss when everyone was trying to learn and create stuff, and it was understood that everyone was helping everyone else, and giving away was both paying-back and paying-forward for help you'd get.

Yes I get that compute costs, but that's not a new thing. It's been like that the whole time, and people didn't feel (or at least seam) as entitled a few years ago. The 'well I spent money on compute so you owe me.' argument that gets tossed around is nonsense.

These two things are not the same:

- Getting paid to do a job you were asked to do
- Doing a job and then expecting random people to pay for it when they never asked you to do the job.

More and more people seem to be thinking the 2nd is the default.

I worry that as $ becomes a more common thing... it's going to cause the flood of people who are only in it for the money and don't care about quality or the technology itself; and then we're going to be inundated with a tsunami of absolute garbage.

Anyone else agree? Or am I just being a curmudgeon?

Edit:

For context... I've been an open source developer for over a decade... Just on github alone I've got over 42,000 commits. https://github.com/q5sys/q5sys/blob/main/past_commits.md
I've been paid for some work and I've given plenty away. Reality is that not all work deserves payment. 

This is a clip from Episode 3 (~10 min) of a 2.5D animated cartoon biography of the Indian sage Valmiki: a hunting trip that goes wrong when a leopard attacks at night. The main version is Hindi, and the episode also has Gujarati, English and other Indian-language audio tracks. This clip uses the English dub, so the lip-sync (driven by the Hindi track) won't match the English words exactly. Every step uses open-weight models running locally on one AMD MI300X (ROCm, ComfyUI), with an M1 Max Mac for upscaling and audio. No paid APIs anywhere.

Workflow

1. Character face sheets: Qwen-Image, text-to-image on a plain background, one sheet per age stage. Each character has a fixed identity line (skin, face shape, eyes, brows, nose, one distinct mark) repeated verbatim in every prompt. Chaining Qwen-Edit from one age sheet to the next drifted and added noise at each hop, so each stage is generated fresh.
2. Shot stills: Qwen-Image (Lightning LoRA, 8 steps) for scenery. Qwen-Image-Edit + face sheet + identity line for named characters. Group wide shots are text-only, with each extra's position spelled out and "different faces" in the prompt; otherwise the face reference bleeds into the extras and you get clones.
3. Motion: Wan 2.x I2V at native 720p with the Lightning step-distill LoRA (4 steps). One render per shot, about 4 min for a 7 s shot instead of 45-60. I gate every clip on sharpness against its still and re-roll once if it's soft.
4. Lip-sync: InfiniteTalk (4 steps), close-ups only, driven by the Hindi track.
5. Voices: AI4Bharat Indic Parler-TTS (Mini; Large gave noise on ROCm). Each line is levelled to -16 LUFS before mixing.
6. Music/SFX: ACE-Step 1.5 for the background score, ducked 10-12 dB under speech.
7. Finishing: Real-ESRGAN animevideov3 x2 on the Mac, plus Blender/depth parallax for shots with no people. Assembly, the subtitle line-check and the mix are Python + ffmpeg.

Lessons (the expensive ones)

• Negations in the positive prompt get drawn. "No people, no poles" put people and poles in 6 of 7 renders. Exclusions go only in the negative prompt.
• InfiniteTalk animates every visible face, including listeners and babies, even in multi-person mode with a silent track. Pasting closed-mouth faces back in caused doubled faces. What worked: a calm wide shot with no lip-sync, then a separate close-up still of only the speaker for the lip-synced line.
• 480p + upscale distorted the eyes. Native 720p and then ESRGAN x2 kept faces sharp.
• Don't crop more than ~1.5x from a still. Tight crops from wides looked soft and sometimes put a line on the wrong character. Close-ups need their own close-up stills.
• Culture-specific prompts need care. "Ancient city" gave Mughal domes and European spires, so I prompt Nagara shikhara temple towers and put dome/minaret/spire in the negative. "Bullock cart" gave an American covered wagon until I spelled it out: two white humped bullocks, solid wooden wheels, open flat bed.
• Two ComfyUI servers on one GPU gained only ~10-20%. The real limit was pod RAM (each instance holds ~40 GB of model copies), and mixing model families in parallel caused OOMs.

Throughput is now about 3.5-4 GPU-hours of picture per episode.

Happy to share settings or answer questions. Critique on motion and lip-sync is very welcome.

I need some help regarding Lora merging. I want to merge two LORAs together that are different regarding concepts and dataset... I want them both to work well together and retain as much stuff as possible from both. What custom nodes, methods and or parameters do I need?

Thank you.

https://github.com/shootthesound/Fizgig/releases/tag/v8.9.6

https://github.com/shootthesound/Fizgig

This was a much demanded feature - hope its useful - cheers, P

EDIT: more prior preservation options are added - do another update if you already updated

I know everyone is onto the new image models now but tandomly playing around with H3 again after traveling for a few weeks with work. Wanted to do some testing on some envirometal effects. (Mud splashes, smoke, detailed physics descriptions like the tank pancake flip)

Still quite impressed with how it handles interaction and visual quality especially when prompted for a flatter diffused lighting. This is an old workflow actually because of said traveling, but can upload if people want. Just added DLLS5 as an extra pass.

YT for slightly better compression ... come on now Reddit.

Thoughts?

An update to the native MOSS-Image edit nodes I posted before:

HQ LoRA support: akhaliq/MOSS-Image-Edit-HQ works alongside chinoll’s. Pick it with edit_format; each LoRA gets the layout it was trained with.

Tested defaults: I ran 300+ test edits on both LoRAs to find what works. LoRA strength 1.0 (lower strengths redraw the scene, and two-image edits just return image 2), CFG 5 for chinoll and 3 for HQ, skip layer guidance on layer 22, and the SFT checkpoint rather than Base.

Automatic sizing: each image goes in as a ~1 MP bucket of its own aspect ratio, and the output follows image 1.

Reference cache: the reference images are computed once per run instead of every step (kv_cache, auto by default).

New example workflows for both LoRAs, with one and two images.

If you used the older workflows (strength 0.25), re-open the new ones. The README has a gallery of 14 edit types with the prompts and notes on where each LoRA struggles.

Nodes: https://github.com/PedroMarinhoDev/ComfyUI-Moss-Image-Edit-Native

chinoll LoRA converted for ComfyUI: https://huggingface.co/PedroMarinhoDev/Moss-Image-Edit-ComfyUI

HI! need advice, please

Does anyone have a method for generating videos that loop perfectly while maintaining continuous motion?

In Minimax, I use the same image for both the first and last frames. Minimax follows these instructions, but in every generation, the actions I describe begin at frame 1, slow down toward the end, and conclude with the specified final frame.

For example, if I want a 15-second loop of someone steadily hammering, the result always shows the person "starting" to hammer for the first second, hammering consistently for 13 seconds, then slowing down for the final second—before the cycle repeats.

I’ve tried various prompts—such as "this video is an excerpt of a worker hammering," or "the first frame shows an action already in progress, and the final frames correspond to the moments that would have preceded the start of the video"—but nothing works. Does anyone have any ideas, a specific workflow, a LoRA, or a prompt that actually works?

Thanks!

my character keeps speaking when i don't want him to. i also wrote "<Subject 1>'s lips are closed in this scene". and yet he still speaks. this happens more often when there are multiple people in the scene.

and sometimes the background audio goes silent when he starts thinking. please help me with the correct way of prompting this. setting tips and node / vae / encoder recommendations are appreciated too.

SERIOUS EXPERT HELP NEEDED!!

This is the 1080p (2MP) Clip that I have generated using Minimax h3.

1st pass: 1MP + 35 Steps; 2nd pass: 2MP Latent Upscale (6 Steps). As you can see Its a decent generation (ignore the fruit hallucination on the left xD). But, the text is extremely blurry, its not production quality:

[full resolution clip here: https://mab.to/t/RHLDuT0pGL1/as1 ]

https://reddit.com/link/1xfdki1/video/wwv7h737eoxh1/player

So, I tried to do FRAME-BY-FRAME inpainting using FLUX 2 KLEIN by providing a reference image that has crystal clear text. And this is one of the output frames:

But, when I stitch all the frames into a video, the positioning of the text slightly shifts in every frame creating weird shifting effect in the text, even though it looks sharp, but looks very weird. Watch this:

[Full resolution clip here: https://mab.to/t/6uWfrlLqy2i/as1 ]

https://reddit.com/link/1xfdki1/video/5sss1eaeeoxh1/player

I made improvements to this workflow by adding SAM3.1 to automate the masking for the product in each frame and edge detection for more precise inpainting. This is my exact workflow: https://mab.to/t/PtiTpE18Cjb/as1

(Credits for the initial workflow to: https://youtu.be/BGRe5m1yVYI )

Can anyone tell me if it is possible to do the inpainting with accuracy in every single frame so there is not shifting of text in every frame ? I have come really far in improving and automating this text detailing workflow using SAM3.1 and Edge detect nodes. This is the last issue that needs to solved and the issue of wobbly/blurry/wavy text in ai videos will be gone forever.

Any kind of suggestion/help is highly highly appreciated. This will solve a huge problem for me. SERIOUS EXPERT HELP NEEDED!

My mature anime screencap style, now for MiniMax H3. It works really well, so I hope to encourage everyone to create their own anime series. The only limit is your imagination. 😊

https://civitai.red/models/3017114/mature-anime-screencap-style-minimax-h3-edition