Simple prompt 2x latent upscaled FLUX - Fine Tuning / DreamBooth Images - Can be trained on as low as 6 GB GPUs - Each image 2048x2048 pixels
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Simple prompt 2x latent upscaled FLUX - Fine Tuning / DreamBooth Images - Can be trained on as low as 6 GB GPUs - Each image 2048x2048 pixels
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AI Photos of Yourself - Workflow Guide
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AI Photos of Yourself - Workflow Guide
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Step 1: Initial Setup
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Step 1: Initial Setup
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Follow any standard FLUX Fine-Tuning / DreamBooth tutorial of your choice
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Follow any standard FLUX Fine-Tuning / DreamBooth tutorial of your choice
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You can also follow mine step by step : 
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You can also follow mine step by step : 
https://youtu.be/FvpWy1x5etM
https://youtu.be/FvpWy1x5etM
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Step 2: Data Collection
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Step 2: Data Collection
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Gather high-quality photos of yourself
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Gather high-quality photos of yourself
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I used a Poco X6 Pro (mid-tier phone) with good results
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I used a Poco X6 Pro (mid-tier phone) with good results
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Ensure good variety in poses and lighting
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Ensure good variety in poses and lighting
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Step 3: Training
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Step 3: Training
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Use "ohwx man" as the only caption for all images
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Use "ohwx man" as the only caption for all images
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Keep it simple - no complex descriptions needed
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Keep it simple - no complex descriptions needed
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Step 4: Testing & Optimization
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Step 4: Testing & Optimization
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Use SwarmUI grid to find the optimal checkpoint
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Use SwarmUI grid to find the optimal checkpoint
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Test different variations to find what works best
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Test different variations to find what works best
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Step 5: Generation Settings
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Step 5: Generation Settings
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Upscale Parameters:
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Upscale Parameters:
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Scale: 2x
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Scale: 2x
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Refiner Control: 0.6
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Refiner Control: 0.6
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Model: RealESRGAN_x4plus.pth
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Model: RealESRGAN_x4plus.pth
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Prompt Used:
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Prompt Used:
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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
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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
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Note: The model naturally generated smiling expressions since the training dataset included many smiling photos.
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Note: The model naturally generated smiling expressions since the training dataset included many smiling photos.
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Note: yolo-face_yolov9c.pt used to mask face and auto inpaint face to improve distant shot face quality
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Note: yolo-face_yolov9c.pt used to mask face and auto inpaint face to improve distant shot face quality
Simple prompt 2x latent upscaled FLUX - Fine Tuning / DreamBooth Images - Can be trained on as low as 6 GB GPUs - Each image 2048x2048 pixels

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
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