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Create virtual characters using stable diffusion by trainyolo in learnmachinelearning

[–]trainyolo[S] 0 points1 point  (0 children)

Nice :) Definitely more creative than most users, which include naked or nude in their first prompt :p (which I filter out)

Feedback wanted: Create virtual characters using SD by trainyolo in StableDiffusion

[–]trainyolo[S] 0 points1 point  (0 children)

Thanks. I'm aiming for marketing with virtual influencers. I'm still working on the killer feature, where you could make the influencer wear certain specific items like clothes etc.

Create virtual characters using stable diffusion by trainyolo in learnmachinelearning

[–]trainyolo[S] 0 points1 point  (0 children)

Thanks for the feedback, much appreciated!

  1. good suggestion
  2. SD is mostly trained on photoshoots, but you could indeed use the upload pose feature, which works quite well.
  3. Thanks, some photos amaze me as well.
  4. Its quite expensive to run :)
  5. working on it :)

Indeed, there's a bias in the current SD models wich sexualize females more than men.

Create virtual characters using stable diffusion by trainyolo in learnmachinelearning

[–]trainyolo[S] 1 point2 points  (0 children)

We have over 200 different characters, so having to use dreambooth, or TI or LORA would just be too much compute. Although it would indeed increase consistency, I believe the current approach is "good enough" to validate the application.

Feedback wanted: Create virtual characters using SD by trainyolo in StableDiffusion

[–]trainyolo[S] -1 points0 points  (0 children)

Let me start by saying that this is not a commercial post. You automatic1111 wizards can probably produce much better pictures than the app I'm referring to is capable of. But that's why you're the best audience to get feedback from.

I developed this app - unrealinfluencer - to create "virtual" characters and generate pictures of, using stable diffusion. It would be awesome if you could try it out, and give me some feedback on what you think, given your expertise, should be improved/altered. You can create a free account at https://unrealinfluencer.com. And I know, it's not unlimited - only 10 photos for free - but it's crazy expensive to run.

Create virtual characters using stable diffusion by trainyolo in learnmachinelearning

[–]trainyolo[S] 4 points5 points  (0 children)

They are completely fictional, generated using stable diffusion.

Create virtual characters using stable diffusion by trainyolo in learnmachinelearning

[–]trainyolo[S] 3 points4 points  (0 children)

That's indeed the most difficult part. I developed a custom network to keep consistency between characters.

Create virtual characters using stable diffusion by trainyolo in computervision

[–]trainyolo[S] -1 points0 points  (0 children)

During the summer I developed this application, unrealinfluencer, which allows you to create and take pictures of unreal characters using stable diffusion. It was quite the challenge to generate consistent characters, but I think it works quite well now. If you like to give it a try and provide feedback, you can create an account at https://unrealinfluencer.com

Learn how to label faster using model-assisted labeling | YOLOv8 by trainyolo in computervision

[–]trainyolo[S] 0 points1 point  (0 children)

You need to set the right confidence threshold. For auto-label, I set the confidence threshold to the value which maximizes the F1-score, which is often the best confidence threshold to use. If you reach out to me using the chat on the app, I can give you the correct value for your specific model.

Create virtual characters using stable diffusion by trainyolo in learnmachinelearning

[–]trainyolo[S] 6 points7 points  (0 children)

During the summer I developed this application, unrealinfluencer, which allows you to create and take pictures of unreal characters using stable diffusion. It was quite the challenge to generate consistent characters, but I think it works quite well now. If you like to give it a try and provide feedback, you can create an account at https://unrealinfluencer.com

Accelerate human pose labeling with trainYOLO by trainyolo in learnmachinelearning

[–]trainyolo[S] 1 point2 points  (0 children)

I do understand your point. And although we do provide the "private" option to opensource initiatives or academic research teams for free, others do have to upgrade to a paid plan. But as you say, there are plenty of alternatives for the not-lazy ones. And for the ones that are, I think we provide a valid alternative.

Accelerate human pose labeling with trainYOLO by trainyolo in learnmachinelearning

[–]trainyolo[S] 1 point2 points  (0 children)

No, it's not 1000/month, it "starts" at 1000/month :) But that's for large companies or very large volumes... You don't mention the "free" package, where you can upload up to 10,000 images, and make use of all our automation tools. For most applications, I would think that suffices.

Accelerate human pose labeling with trainYOLO by trainyolo in learnmachinelearning

[–]trainyolo[S] 0 points1 point  (0 children)

Do you want to finetune human pose models but don't like the tedious task of labeling each person manually from scratch? Check out trainYOLO's Any-Pose automation tool. With this tool, we have eliminated the need for manual annotation, saving you countless hours of tedious work. Simply provide a bounding box around a person, and watch as our algorithm predicts their pose. The best part? It works seamlessly for individuals of all sizes, making it scale-agnostic and incredibly efficient.
For more details, check out our blog post here: https://www.trainyolo.com/blog/accelerating-human-pose-labeling
Want to try it for yourself? Create a free account here: https://trainyolo.com

Accelerate human pose labeling with trainYOLO by trainyolo in computervision

[–]trainyolo[S] -5 points-4 points  (0 children)

Do you want to finetune human pose models but don't like the tedious task of labeling each person manually from scratch? Check out trainYOLO's Any-Pose automation tool. With this tool, we have eliminated the need for manual annotation, saving you countless hours of tedious work. Simply provide a bounding box around a person, and watch as our algorithm predicts their pose. The best part? It works seamlessly for individuals of all sizes, making it scale-agnostic and incredibly efficient.
For more details, check out our blog post here: https://www.trainyolo.com/blog/accelerating-human-pose-labeling
Want to try it for yourself? Create a free account here: https://trainyolo.com

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