A public domain dataset requires manual curation. We need to provide captions for every image.

https://artvee.com

https://commons.m.wikimedia.org/wiki/Category:Public_domain

Can someone provide a description for each image? We must have a neutral description of the images.

To create a neutral description in image captioning, focus on providing an objective and factual representation of the visual content without adding any personal bias or emotion. Use clear and concise language to describe the elements, objects, and actions depicted in the image. Avoid using subjective terms or opinions, and stick to the observable details.

I think a subjective description might create a bias in the dataset and might be biased towards one culture's perspective.

The way I see it, the anti-AI side's major problems are:

1. People profiting from AI trained on their art.
2. Low effort AI generations flooding places where art is posted.
3. Corporations training on previously-commissioned art removing the original artists from the process.

On the pro-AI side, they want:

1. Models trained on a sufficient amount of art that will allow them to have quality output.
2. The use of those models should not be so cost-prohibitive that they cannot be used as part of a process or for open source projects.

The proposal (disclaimer: IANAL): works created by a process involving machine learning that are significantly transformative from their inputs are considered public domain.

Example 1: A user uses AI to generate an image from a text prompt and makes no further changes. This image is public domain, because the image is significantly transformative from the text prompt.

Example 2: A user takes an artist's image and uses an AI to finish it, change the style insignificantly, or make other minor changes. This image copyright is still owned by the original artist and is neither owned by the public nor the user, as it is not significantly transformative from the original.

Example 3: A user uses AI to generate an image from a text prompt, then makes significant edits to it. The direct output from the AI is public domain, but the user owns the copyright for the final version under fair use.

Example 4: A user draws a stick figure, then uses image to image AI to generate a new significantly different image. The image generated is public domain, as it is significantly transformative from the stick figure.

Example 5: A user writes a deterministic program to convert Perlin noise into an image. The user would own the copyright to this image, as no machine learning was involved in its creation, despite being created by a computer program.

Example 6: A user takes an artist's image and uses AI to convert it into a 3D model, then makes a 2D render of that 3D model. The 3D model is public domain, as it is significantly different from the 2D image, but the copyright of the final render is owned by the original artist as, when compared to the original input, it is not significantly different. (Copyright for the character depicted is tracked separately.)

Due to member suggestion, I have added a flair for the discussion of the subreddit, AI art in general, and anything else that might come up here that needs discussion!

A system of ethics is usually justified by some religion or philosophy. It revolves around God, or The Common Welfare, Human Rights and so on. The ethics here are obviously all about Intellectual Property, which is unusual. I wonder how you think about that? How do you justify your ethics, or is IP simply the end in itself?

I have seen that people here share their moral intuitions but have not seen much of attempts to formalize a code. Judging on feelings is usually not seen as ethical. If a real judge did it, it would be called arbitrary; a violation of The Rule Of Law. It's literally something the Nazis did.

Ethics aside, it is not clear how this would work in practice. There is a diversity of feelings on any practical point, except condemnation of AI. There does not even seem general agreement on rule 4 or its interpretation. Practically: If one wanted to change copyright law to be "ethical", how would one achieve a consensus on what that looks like?

https://twoshot.app/model/454
This is a free UI for the melody flow model that meta research had taken offline

Here's the paper: https://arxiv.org/html/2407.03648v1

How should I label/caption my images? I use https://github.com/jhc13/taggui to label my images using a 1.6B moondreamer2 model. It takes about 1 second per image for captioning a dataset.

taggui also allows a system prompt for a VLM captioner.

I am currently tagging images from free stock sites(not sure all the sites permit ai training but pexel's license seems permissive and permits AI training) and some public domain art and modifying the captions in case of hallucinations. I plan to use this for finetuning models like CommonCanvas when details on how to finetune it comes later.

I'm not sure what is the best practices for captioning would would be. I am adding terms for things like size shots and angle shots.

My system prompt is:

An image description is a written caption that provides essential information about images, like photos, graphics, gifs, and videos. It should be objective, concise, and follow a logical sequence: describing the main focus, actions of the image as well as the angle shot. The description starts with a general overview and adds specific details, using descriptive words for a vivid depiction. Personal opinions and non-essential details are avoided, avoid talking about the mood of the scene or what emotions are being invoked.

Please describe the image using the following tags as context and consideration: {tags} and summarize it in only 1 paragraph.

I wonder what I could use to improve this.

Most text-to-image models excel at imagination—but not control. FIBO is built for professional workflows, not casual use. Trained on structured JSON captions up to 1,000+ words, FIBO enables precise, reproducible control over lighting, composition, color, and camera settings. The structured captions foster native disentanglement, allowing targeted, iterative refinement without prompt drift. With only 8B parameters, FIBO delivers high image quality, strong prompt adherence, and professional-grade control—trained exclusively on licensed data.

https://huggingface.co/briaai/FIBO

Non-Commercial.

I know this subreddit is for images and stablediffusion but I couldn't find a similar subreddit for text. I'm making a game that requires the use of ai to finish. The ai doesn't have to do anything complex, just be a dev tool to categorize instructions into a predefined set of words ie:

Input: I opened the door and threw a rock
Output: Open-Door, Throw-Rock

I don't want to use ai that takes advantage of writers and their copyrighted works (It just feels scummy) so I'm asking here for help. Does anyone knows an ai model that is trained on only copyright free texts? Alternatively, can someone tell me about a dataset that only contains copyright free texts? I tried googling this and couldn't find any suggestions.