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AI Photos of Yourself - Workflow Guide

Step 1: Initial Setup

Follow any standard FLUX Fine-Tuning / DreamBooth tutorial of your choice

You can also follow mine step by step : https://youtu.be/FvpWy1x5etM

Step 2: Data Collection

Gather high-quality photos of yourself

I used a Poco X6 Pro (mid-tier phone) with good results

Ensure good variety in poses and lighting

Step 3: Training

Use "ohwx man" as the only caption for all images

Keep it simple - no complex descriptions needed

Step 4: Testing & Optimization

Use SwarmUI grid to find the optimal checkpoint

Test different variations to find what works best

Step 5: Generation Settings

Upscale Parameters:

Scale: 2x

Refiner Control: 0.6

Model: RealESRGAN_x4plus.pth

Prompt Used:

photograph of ohwx man wearing an amazing ultra expensive suit on a luxury studio<segment:yolo-face_yolov9c.pt-1,0.7,0.5>photograph of ohwx man

Note: The model naturally generated smiling expressions since the training dataset included many smiling photos.

Note: yolo-face_yolov9c.pt used to mask face and auto inpaint face to improve distant shot face quality

Files

Comments

cool1

It looks impressive, but if it's upscaling won't it be inventing details that weren't in the trained lora/dreambooth (or missing details that weren't the lora/dreambooth)? Wouldn't it be more accurate if it could train at that 2048 res (though maybe it's almost impossible with Flux/SD3.5 type models without GPUs with huge amounts of VRAM. Maybe it was Nvidia's SANA that could do about 4K but that wasn't for commercial use and I think that was the one that some images at high res looked over compressed on some image(s) on reddit and I don't know that could be trained.

Sonivas Sx

If i train a dream-booth fine tune, do i need regularisation images when i want to appear with random people or other Loras ? Because when i trained a Lora of myself it tends to make all other people in the image to look like me. Also how many , and what kind of images i need for regularisation for a dataset of 20 images ?

Ross

Is there any benefit to using training photos with higher resolution than 1024x1024? I'm curious if there are any benefits or consequences to using higher quality training photos.

cool1

On Nvidia's SANA website (https://nvlabs.github.io/Sana/) they talk about 4K saying "our AE-F32 outputs 16× fewer latent tokens, which is crucial for efficient training and generating ultra-high-resolution images, such as 4K resolution."..."Linear attention achieves comparable results to vanilla, improving 4K generation by 1.7× in latency. ". Though maybe it's that 4K isn't high quality with SANA (since I think it was a sample image from that that looked too compressed with artefacts). edit: and faces get distorted in it to - that's what one video of it showed but it said they'd fix it in a later version.

cool1

Yes the 2K one doesn't look that great resolution (maybe it's also because they compress images for their AI model so much (they said they compress a lot more than others) and the model is a lot smaller than others). Though the 1024px one upscaled to 2K with Lanczos, while it looks brighter in parts, at 100% size it looks like the edges of the car (eg. the bottom edge between the wheels) on the upscaled one are more aliased/stair-case like than the 2048 original one. And at the back wheel edge there's maybe a bit more of a halo+step effect around the edge of the wheel on the upscaled one than the 2048 original one at 100% size.

eduardo

Can you explain the parameters you used for th yolo face model 1,0.7,0.5

ProudChinaLover

I have a technical question: I did follow your steps in the tutorial; however, when I used the trained dreambooth in SwarmUI, I go this error message: All available backends failed to load the model ' C:\SwarmUI\SwarmUI\Models\Stable-Diffusion\Flux\Raflux-00020.safetensors'. What is this ? I did reinstall SwarmUI or update whatever I can . Anything wrong ? I did check ae , text encorder ... I can't get any luck.

Hockey

What would the equivalent settings in Adetailer on Forge be for these settings "segment:yolo-face_yolov9c.pt-1,0.7,0.5" ?

Hockey

Thank you so much, really appreciate it. =)