glide-text2im
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| dalle-2-preview | glide-text2im | |
|---|---|---|
| 61 | 32 | |
| 1,049 | 3,467 | |
| 0.0% | 1.2% | |
| 1.8 | 0.0 | |
| almost 2 years ago | about 2 months ago | |
| Python | ||
| - | MIT License |
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dalle-2-preview
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Microsoft-backed OpenAI to let users customize ChatGPT | Reuters
We believe that many decisions about our defaults and hard bounds should be made collectively, and while practical implementation is a challenge, we aim to include as many perspectives as possible. As a starting point, we’ve sought external input on our technology in the form of red teaming. We also recently began soliciting public input on AI in education (one particularly important context in which our technology is being deployed).
- OpenAI AI not available for Algeria, gotta love Algeria
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The argument against the use of datasets seems ultimately insincere and pointless
From this OpenAI document:
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Dalle-2 is > 1,000x as dollar efficient as hiring a human illustrator.
It's also of note that you can't sell a game using this method, as Dalle-2's terms of service prevent use in commercial projects. It's hard to justify rate of return considering you can only ever give it away for free, and even in that case there are some uncertain legal elements regarding copyright and the images that are used to train the dataset.
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It's pretty obvious where dalle-2 gets some of their training data from! Anyone else had the Getty Images watermark? Prompt was "man in a suit standing in a fountain with his hair on fire."
On their GitHub https://github.com/openai/dalle-2-preview/blob/main/system-card.md I can only see references to v1.
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“Pinterest” for Dalle-2 images and prompts
"b) Exploration of the bolded part of OpenAI's comment "Each generated image includes a signature in the lower right corner, with the goal of indicating when DALL·E 2 helped generate a certain image." (source)." (source link: https://github.com/openai/dalle-2-preview/blob/main/system-c...)
I feel the DALL-E 2 watermark signature could be a seed or something.
- I’m an outsider to digital art and have a couple questions about A.I created art.
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The AI Art Apocalypse
DALL-E's docs for example mention it can output whole copyrighted logos and characters[1] and understands it's possible to generate human faces that are bear the likeness of those in the training data. We've also seen people recently critique Stable Diffusion's output for attempting to recreate artists' signatures that came from the commercial trained data.
That said by a certain point the kinks will be ironed out and likely skirt around such issues by only incorporating/manipulating just enough to be considered fair use and creative transformation.
[1] "The model can generate known entities including trademarked logos and copyrighted characters." https://github.com/openai/dalle-2-preview/blob/main/system-c...
- Trabalhei no projeto Dall-e, me pergunte qualquer coisa (AMA)
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Official Dalle server: Why “furry art” is a banned phrase
Some types of content were purposely excluded from the training dataset(s) (source).
glide-text2im
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인공지능에 대한 이해 : https://youtu.be/g1ARrNTwBHg 1편 - 딥러닝의 원리 https://youtu.be/CA5Ggqg5x6o 2편 - 인공지능의 창의성과 테슬라 AI https://youtu.be/jHYYggG7qq8 3편 - 코딩, 과학, 수학 난제를 해결하려는 A.I. https://youtu.be/BWJWAdMZGNY ---------------------------------------------------- 영상에 등장하는 링크 : ADOP(2021) https://arxiv.org
GLIDE(2021) https://syncedreview.com/2021/12/24/deepmind-podracer-tpu-based-rl-frameworks-deliver-exceptional-performance-at-low-cost-173/ || 소스코드 : https://github.com/openai/glide-text2im
- [R][P] I made an app for Instant Image/Text to 3D using PointE from OpenAI
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"Teacher villainess, DreamWorks official character design sheet turnaround, studio, Best on Artstation, 4K HD, by Nate Wragg"
The bolded part is a reference to the publicly released version of OpenAI's GLIDE, which is the predecessor of DALL-E 2. OpenAI didn't release the GLIDE model(s) trained on human faces.
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Trying to remember the name of an upscaler. I thought it was Glide XL or something.
OpenAI's GLIDE text2im https://github.com/openai/glide-text2im
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It just struck me that text diffs do *not* require the image-generating prompt as a starting point, and my mind is blown to pieces.
If I can stop wasting my time playing video games for a while, I might work on getting the Dalle-2 open-source predecessor (GLIDE) to work. Also can't wait for this to be released, I have so many uses for it!
- [D] Making text-to-image even better - GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models, a 5-minute paper summary by Casual GAN Papers
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Dall-E 2
A few comments by someone who's spent way too much time in the AI-generated space:
* I recommend reading the System Card that came with it because it's very through: https://github.com/openai/dalle-2-preview/blob/main/system-c...
* Unlike GPT-3, my read of this announcement is that OpenAI does not intend to commercialize it, and that access to the waitlist is indeed more for testing its limits (and as noted, commercializing it would make it much more likely lead to interesting legal precedent). Per the docs, access is very explicitly limited: (https://github.com/openai/dalle-2-preview/blob/main/system-c... )
* A few months ago, OpenAI released GLIDE ( https://github.com/openai/glide-text2im ) which uses a similar approach to AI image generation, but suspiciously never received a fun blog post like this one. The reason for that in retrospect may be "because we made it obsolete."
* The images in the announcement are still cherry-picked, which is therefore a good reason why they tested DALL-E 1 vs. DALL-E 2 presumably on non-cherrypicked images.
* Cherry-picking is relevant because AI image generation is still slow unless you do real shenanigans that likely compromise image quality, although OpenAI has likely a better infra to handle large models as they have demonstrated with GPT-3.
- Glide-Text2Im
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AI-generated photos of European flags
The flags were generated using Glide. You can try it out yourself in Google Colab
- New AI technique that lets you generate images from text. Now better than ever!
What are some alternatives?
dalle-mini - DALL·E Mini - Generate images from a text prompt
DALL-E - PyTorch package for the discrete VAE used for DALL·E.
glide-text2im-colab - Colab notebook for openai/glide-text2im.
latent-diffusion - High-Resolution Image Synthesis with Latent Diffusion Models
pixray
DALLE2-pytorch - Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
improved-diffusion - Release for Improved Denoising Diffusion Probabilistic Models
disco-diffusion
v-diffusion-pytorch - v objective diffusion inference code for PyTorch.
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
diffusion - Denoising Diffusion Probabilistic Models