Depth-Anything
finagg
Depth-Anything | finagg | |
---|---|---|
6 | 17 | |
5,941 | 390 | |
- | - | |
8.0 | 8.0 | |
25 days ago | 18 days ago | |
Python | 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.
Depth-Anything
-
Video generation models as world simulators
Depth estimation improved a lot as well e.g. with Depth-Anything [0]. But those are mostly relative depth instead of metric. Also when even converted to metric they still seems have a lot of pointclouds at the edges that have to be pruned - visible in this blog [1]. Looks like those models trained on Lidar or Stereo depthmaps that has this limitations. I think we don't have enough clean training data for 3d unless we maybe train on synthetic data (then we can have plenty, generate realistic scene in Unreal Engine 5 and train on rendered 2d frames)
[0] https://github.com/LiheYoung/Depth-Anything
[1] https://medium.com/@patriciogv/the-state-of-the-art-of-depth...
-
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Very interesting work! More details here: https://depth-anything.github.io/
It seems better overall and per parameter than current work, with relative and absolute measurement.
Is there any research people are aware of that provides sub-mm level models? For 3D modeling purposes? Or is "classic" photogrammetry still the best option there?
- FLaNK Stack 29 Jan 2024
finagg
-
This Week In Python
finagg – A Python package for aggregating and normalizing historical data from popular and free financial APIs
- FLaNK Stack 29 Jan 2024
- Show HN: Finagg – free and nearly unlimited financial data
-
[D] Website to get historical price for agriculture commodities?
This is certainly a weird place to ask this question. That being said, you should explore the FRED API. Here's my project that implements most of it in Python: https://github.com/theOGognf/finagg The walkthrough shows you how to find what you're looking for
-
Fundamental Data Sources
I created a Python package exactly for this. https://github.com/theOGognf/finagg. It aggregates historical fundamental data for whatever tickers you specify or from a subset of tickers. Let me know what you think
-
Is accurate quarterly earnings data availible?
This package https://github.com/theOGognf/finagg already implements the complete SEC EDGAR REST API (disclaimer: I'm the author), and the archive-based API is in the works. I suggest you give it a go using the latest version off GitHub
-
Sunday Daily Thread: What's everyone working on this week?
I've got some time set aside to implement a (file based) SEC EDGAR API described in this issue https://github.com/theOGognf/finagg/issues/43
- finagg: NEW Data - star count:107.0
What are some alternatives?
ZoeDepth - Metric depth estimation from a single image
pyautoenv - Automatically activate and deactivate Python environments as you move around the file system.
Weaviate - Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
sql-to-kml - Format SQL query results into a KML file.
plombery - Python task scheduler with a user-friendly web UI
usepython - Run Python scripts in a Pyodide service worker
bytewax - Python Stream Processing
java-snapshot-testing - Facebook style snapshot testing for JAVA Tests
internet-speed-test - An Internet Speed Test built on Python's Turtle module
uuid-utils - Python bindings to Rust UUID
pong-wars
pyodide - Pyodide is a Python distribution for the browser and Node.js based on WebAssembly