roadmap
DBoW2
roadmap | DBoW2 | |
---|---|---|
11 | 2 | |
187 | 824 | |
1.1% | - | |
1.7 | 0.0 | |
10 months ago | over 2 years ago | |
C++ | ||
- | GNU General Public License v3.0 or later |
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.
roadmap
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Embeddings: What they are and why they matter
In case anyone is interested, Heroku finally released pgvector support for Postgres yesterday: https://github.com/heroku/roadmap/issues/156
Pgvector is an extremely excellent way to experiment with embeddings in a lightweight way, without adding a bunch of extra infrastructure dependencies.
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11 Years of Hosting a SaaS
(I work at Heroku) Do you have more details on what sucks? Anything we're not already tracking to fix in our public roadmap? https://github.com/heroku/roadmap/issues
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Is there any updates as to when Heroku will support IPv6?
"GitHub - heroku/roadmap: This is the public roadmap for Salesforce Heroku services." https://github.com/heroku/roadmap
- Introducing Our New Low-Cost Plans [Heroku]
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Heroku - If I have a paid dyno can I keep my free ones? (using paid for production, using free for dev and staging)
You can upvote here to try get a version of free back - https://github.com/heroku/roadmap/issues/51
- Let’s try and make free come back
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Heroku Free Tier
I proposed this -> https://github.com/heroku/roadmap/issues/51 on the Heroku roadmap - hopefully to bring back some sort of free trial environment. Please take a look an upvote if you agree:
- Heroku make their development roadmap public on GitHub
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Heroku's Next Chapter
The public roadmap is a good idea but highlights how stale the product has become. https://github.com/heroku/roadmap/issues Only now researching adding Cloud Native Build Packs and HTTP2.
This will reaffirm for many the sense that Heroku is being dismantled from within. Feature sunsetting and removal of a free on-ramp doesn't help.
If you're looking for a production alternative to Heroku checkout Northflank.
https://northflank.com
DBoW2
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Embeddings: What they are and why they matter
Not quite the same application, but in computer vision and visual SLAM algorithms (to construct a map of your surrounding using a camera) embedding have become the de-facto algorithm to perform place-recognition ! And it's very similar to this article. It is called "bag-of-word place recognition" and it really became the standard, used by absolutely every open-source library nowadays.
The core idea is that each image is passed through a feature-extractor-descriptor pipeline and is 'embedded' in a vector containing the N top features. While the camera moves, a database of images (called keyframes) is created (images are stored as much-lower dimensional vectors). Again while the camera moves, all images are used to query the database, something like cosine-similarity is used to retrieve the best match from the vector database. If a match happened, a stereo-constraints can be computed betweeen the query image and the match, and the software is able to update the map.
[1] is the original paper and here's the most famous implementation: https://github.com/dorian3d/DBoW2
[1]: https://www.google.com/search?client=firefox-b-d&q=Bags+of+B...
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[D] Fastest SIFT Descriptors Matching with Database of SIFT Descriptors
This library is the most widely used bag of words implementation. Which is the standard for feature retrieval. There might be more advanced methods but you gotta do it yourself. It can also be used with non-sift descriptors. https://github.com/dorian3d/DBoW2
What are some alternatives?
cgm-remote-monitor - nightscout web monitor
faiss - A library for efficient similarity search and clustering of dense vectors.
piku - The tiniest PaaS you've ever seen. Piku allows you to do git push deployments to your own servers.
supabase - The open source Firebase alternative.
flyctl - Command line tools for fly.io services
telekinesis - Control Objects and Functions Remotely
Dokku - A docker-powered PaaS that helps you build and manage the lifecycle of applications
vectordb - A minimal Python package for storing and retrieving text using chunking, embeddings, and vector search.
create-t3-app - The best way to start a full-stack, typesafe Next.js app
llm-cluster - LLM plugin for clustering embeddings
superfly-flyctl
marqo - Unified embedding generation and search engine. Also available on cloud - cloud.marqo.ai