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
this paper is like when you tell an art student just draw it in your own style and they actually do it perfectly on the first try 🎨 diffusion models getting too powerful fr
It's 2025, you shouldn't be hand writing SQL! This is a big step in making it where anyone can do in depth analysis on a dataset. Let us know what you think 🤗
Keeping up with open-source AI in 2024 = overwhelming.
Here's help: We're launching our Year in Review on what actually matters, starting today!
Fresh content dropping daily until year end. Come along for the ride - first piece out now with @clem's predictions for 2025.
Think of it as your end-of-year AI chocolate calendar.
Kudos to @BrigitteTousi@clefourrier@Wauplin@thomwolf for making it happen. We teamed up with aiworld.eu for awesome visualizations to make this digestible—it's a charm to work with their team.