img2dataset
DeepViewAgg
img2dataset | DeepViewAgg | |
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13 | 4 | |
3,264 | 215 | |
- | - | |
7.1 | 4.8 | |
3 days ago | 9 months ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
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img2dataset
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OpenAI sued for web scraping from millions of internet users in order to train ChatGPT
Lmao, no it doesn't. As we can see, their downloader uses very obscure "no ai" headers (which can be disabled, so its useless). They only claim it respects "robots.txt" because the google crawler respects it, if a site changes their robots.txt rules they don't remove it from their dataset, that is not "respecting". https://github.com/rom1504/img2dataset
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Who kept the bots out? Stopping content being harvested by AI
The particular tool mentioned in the Vice article is Img2dataset, and right now, it doesn't pay attention to the robots.txt file, the normal mechanism you can use to dissuade well behaved bots from indexing your content. However, it does respect a new HTTP header directive, X-Robots-Tag: noai (and also noindex, though that's an existing and already well-known part of the robots.txt standard).
- AI used photographer’s photos for training, then slapped him with an invoice
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An AI Scraping Tool Is Overwhelming Websites with Traffic
The established norm is that scrapers have to download robots.txt and support the standard robots.txt features, notably including `Crawl-Delay` which sets a rate limit. This is the established standard by which websites tell scrapers what the rules are for scraping them.
This tool is scraping sites, it has webmasters reporting actual disruption, it doesn't have robots.txt support. When people complained (eg in https://github.com/rom1504/img2dataset/issues/48), the author's stance was basically "PRs welcome". It looks like a third party recently contributed a PR to make it respect robots.txt (https://github.com/rom1504/img2dataset/pull/302), albeit without `Crawl-Delay` support, which is not merged yet.
I have seen the same thing with other recent AI tools (eg https://github.com/m1guelpf/browser-agent/issues/2) and I think it's important to defend the robots.txt convention and nip this in the bud. If a bot doesn't make a reasonable effort to respect robots.txt and it causes disruption, it's a denial-of-service attack and should be treated as such. No excuses.
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Please make this tool “opt-in” by default
//First sentence unchanged
Websites can pass the http headers `X-Robots-Tag: noai`, `X-Robots-Tag: noindex` , `X-Robots-Tag: noimageai` and `X-Robots-Tag: noimageindex` By default img2dataset will ignore images with such headers.
//Then pull up the policy link first
To understand why image creators and artists may choose to specify such headers for their images, and choose to actively not consent to their images being collected, see [AI use impact](https://github.com/rom1504/img2dataset#ai-use-impact).
AI training would not be possible without the contribution of artists, and it is the recommendation of this tool's authors that you should respect their communicated wishes. However, if you have a legitimate reason to bypass these headers, to disable this behavior and download all images, you may pass --disallowed_header_directives '[]'
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- Img2dataset: Turns large sets of image URLs to an image dataset
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Stable Attribution
it's not remembering pixels. for it to do that, it would have to have the pixels stored somewhere. It does not.
The laion 5b dataset is in the neighborhood of 220TB. (1) That is how much storage space you need to remember the pixels.
The stable diffusion 1.5 checkpoint is 7gb. (2)
1 https://github.com/rom1504/img2dataset/blob/main/dataset_exa...
2 https://huggingface.co/runwayml/stable-diffusion-v1-5/tree/m...
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Stability AI plans to let artists opt out of Stable Diffusion 3 image training
AI Bots do not respect these flags anyways
- Rule
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A Stable Diffusion prompt changes its output for the style of 1500 artists
You can download it here:
https://github.com/rom1504/img2dataset/blob/main/dataset_exa...
You probably would want to stop after getting the metadata, unless you have 240TB available for the images :)
More details and links to dataset explorers here: https://laion.ai/blog/laion-5b/
DeepViewAgg
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[R] [CVPR 2022 Oral] Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation
Code for https://arxiv.org/abs/2204.07548 found: https://github.com/drprojects/DeepViewAgg
- [R] [CVPR2022 Oral] Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation
- [CVPR 2022 Oral] Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation
What are some alternatives?
chitra - A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model Deployment.
torch-points3d - Pytorch framework for doing deep learning on point clouds.
google-images-download - Python Script to download hundreds of images from 'Google Images'. It is a ready-to-run code!
MonoScene - [CVPR 2022] "MonoScene: Monocular 3D Semantic Scene Completion": 3D Semantic Occupancy Prediction from a single image
dalle-mini - DALL·E Mini - Generate images from a text prompt
Pointnet_Pointnet2_pytorch - PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
docarray - Represent, send, store and search multimodal data
LAVIS - LAVIS - A One-stop Library for Language-Vision Intelligence
stable-diffusion - A latent text-to-image diffusion model
transfiner - Mask Transfiner for High-Quality Instance Segmentation, CVPR 2022
browser-agent - A browser AI agent, using GPT-4
CapDec - CapDec: SOTA Zero Shot Image Captioning Using CLIP and GPT2, EMNLP 2022 (findings)