datasaurus
squirrel-datasets-core
| datasaurus | squirrel-datasets-core | |
|---|---|---|
| 1 | 2 | |
| 11 | 43 | |
| - | - | |
| 7.2 | 2.3 | |
| 7 months ago | 8 months ago | |
| TypeScript | Python | |
| Apache License 2.0 | Apache 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.
datasaurus
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Is supervised learning dead for computer vision?
And let’s talk about development speed. By using text prompts to interact with your images, you can whip up a computer vision prototype in seconds. It’s fast, it’s efficient, and it’s changing the game.
So, what do you all think? Are we moving towards a future where foundational models take the lead in computer vision, or is there still a place for training models from scratch?
P.S. Shameless plug: I’ve been working on this open-source platform called Datasaurus https://github.com/datasaurus-ai/datasaurus) that taps into the power of vision-language models. It’s all about helping engineers get the insights they need from images, fast. Just wanted to share some thoughts and start a conversation. Let’s talk about the future of computer vision!
squirrel-datasets-core
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[P] Squirrel: A new OS library for fast & flexible large-scale data loading
Have a look at this tutorial to learn how to convert to messagepack by using Spark.
What are some alternatives?
ai-health-assistant - An open source AI health assistant
squirrel-core - A Python library that enables ML teams to share, load, and transform data in a collaborative, flexible, and efficient way :chestnut:
LLaVA - [NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
uda - Unsupervised Data Augmentation (UDA)
deeplake - Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai
podium - Podium: a framework agnostic Python NLP library for data loading and preprocessing
Segment-Everything-Everywhere-
obsidian-ava - Quickly format your notes with ChatGPT in Obsidian
Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]