dwc
Activeloop Hub
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dwc | Activeloop Hub | |
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3 | 31 | |
196 | 4,807 | |
1.5% | - | |
7.8 | 9.9 | |
22 days ago | over 1 year ago | |
Python | Python | |
Creative Commons Attribution 4.0 | Mozilla Public License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dwc
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Recommendations for self-hosted field guide
I'm a data librarian, so ideally the system would be built around the concept of collections, and support a solid metadata schema like Darwin Core.
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We are digitisers at the Natural History Museum in London, on a mission to digitise 80 million specimens and free their data to the world. Ask us anything!
With regards to longevity, when we're planning our infrastructure and how we're actually going to store our digital data we have to think in the long, long term (100+ years), much as we have to when considering how to store the physical specimens. Currently we manage our own data centre which stores all our collections and image data but we’re exploring cloud options currently. In terms of how we store the actual data, we try to map to well known standards and ontologies (such as Darwin Core - https://dwc.tdwg.org/) to ensure our data is interoperable with others and can be managed using community standards. On the Data Portal specifically, we use a versioning system to make sure that data is available long term, even if it’s been changed since it was originally made public (this happens regularly as taxonomists love to reclassify specimens!). This is particularly important when users cite our data using DOIs which should be persistent and always available.
Activeloop Hub
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[Q] where to host 50GB dataset (for free?)
Hey u/platoTheSloth, as u/gopietz mentioned (thanks a lot for the shout-out!!!), you can share them with the general public through uploading to Activeloop Platform (for researchers, we offer special terms, but even as a general public member you get up to 300GBs of free storage!). Thanks to our open source dataset format for AI, Hub, anyone can load the dataset in under 3seconds with one line of code, and stream it while training in PyTorch/TensorFlow.
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[D] NLP has HuggingFace, what does Computer Vision have?
u/Remote_Cancel_7977 we just launched 100+ computer vision datasets via Activeloop Hub yesterday on r/ML (#1 post for the day!). Note: we do not intend to compete with HuggingFace (we're building the database for AI). Accessing computer vision datasets via Hub is much faster than via HuggingFace though, according to some third-party benchmarks. :)
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[N] [P] Access 100+ image, video & audio datasets in seconds with one line of code & stream them while training ML models with Activeloop Hub (more at docs.activeloop.ai, description & links in the comments below)
u/gopietz good question. htype="class_label" will work, but querying doesn't support multi-dimensional labels yet. Would you mind opening an issue requesting that feature?
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Easy way to load, create, version, query and visualize computer vision datasets
Hi HN,
In machine learning, we are faced with tensor-based computations (that's the language that ML models think in). I've recently discovered a project that helps you make it much easier to set up and conduct machine learning projects, and enables you to create and store datasets in deep learning-native format.
Hub by Activeloop (https://github.com/activeloopai/Hub) is an open-source Python package that arranges data in Numpy-like arrays. It integrates smoothly with deep learning frameworks such as TensorFlow and PyTorch for faster GPU processing and training. In addition, one can update the data stored in the cloud, create machine learning pipelines using Hub API and interact with datasets (e.g. visualize) in Activeloop platform (https://app.activeloop.ai). The real benefit for me is that, I can stream my datasets without the need to store them on my machine (my datasets can be up to 10GB+ big, but it works just as well with 100GB+ datasets like ImageNet (https://docs.activeloop.ai/datasets/imagenet-dataset), for instance).
Hub allows us to store images, audio, video data in a way that can be accessed at lightning speed. The data can be stored on GCS/S3 buckets, local storage, or on Activeloop cloud. The data can directly be used in the training TensorFlow/ PyTorch models so that you don't need to set up data pipelines. The package also comes with data version control, dataset search queries, and distributed workloads.
For me, personally the simplicity of the API stands out, for instance:
Loading datasets in seconds
import hub ds = hub.load("hub://activeloop/cifar10-train")
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Easy way to load, create, version, query & visualize machine learning datasets
Hub by Activeloop (https://github.com/activeloopai/Hub) is an open-source Python package that arranges data in Numpy-like arrays. It integrates smoothly with deep learning frameworks such as Tensorflow and PyTorch for faster GPU processing and training. In addition, one can update the data stored in the cloud, create machine learning pipelines using Hub API and interact with datasets (e.g. visualize) in Activeloop platform (https://app.activeloop.ai/3)
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Datasets and model creation flow
Consider this
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[P] Database for AI: Visualize, version-control & explore image, video and audio datasets
Please take a look at our open-source dataset format https://github.com/activeloopai/hub and a tutorial on htypes https://docs.activeloop.ai/how-hub-works/visualization-and-htype
I'm Davit from Activeloop (activeloop.ai).
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The hand-picked selection of the best Python libraries released in 2021
Hub.
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What are good alternatives to zip files when working with large online image datasets?
What solution have you used that you like as a data scientist when working with large datasets? Any standard python API to access the data? Other solution? If anyone has used https://github.com/activeloopai/Hub or other similar API I'd be interested to hear your experience working with it!
What are some alternatives?
CKAN - CKAN is an open-source DMS (data management system) for powering data hubs and data portals. CKAN makes it easy to publish, share and use data. It powers catalog.data.gov, open.canada.ca/data, data.humdata.org among many other sites.
dvc - 🦉 ML Experiments and Data Management with Git
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