#python#bytetrack#multi_object_tracking#oc_sort#sort
Trackers is a simple Python library (pip install trackers) for multi-object tracking that plugs into any detection model like YOLO. Use it via CLI on videos/webcams or in Python code with trackers like ByteTrack (top performer on MOT17/SportsMOT benchmarks) to add labels and trajectories. Evaluate with MOT metrics too. Benefit: Quickly add reliable object tracking to your computer vision projects for real-time apps like traffic or sports analysis, saving time on custom code.
https://github.com/roboflow/trackers
https://pypi.python.org/pypi/oauthlib
A generic, spec-compliant, thorough implementation of the #OAuth request-signing logic for python
OAuth often seems complicated and difficult-to-implement. There are several prominent libraries for handling OAuth requests, but they all suffer from one or both of the following:
They predate the OAuth 1.0 spec, AKA RFC 5849.
They predate the OAuth 2.0 spec, AKA RFC 6749.
They assume the usage of a specific HTTP request library.
OAuthLib is a generic utility which implements the logic of OAuth without assuming a specific HTTP request object or web framework. Use it to graft OAuth client support onto your favorite HTTP library, or provide support onto your favourite web framework. If you’re a maintainer of such a library, write a thin veneer on top of OAuthLib and get OAuth support for very little effort.
https://aaronparecki.com/2012/07/29/2/oauth2-simplified#others
OAuth 2 Simplified
Sun, Jul 29, 2012 9:30am -07:00
Many services such as #Facebook, #Github, and #Google have already deployed OAuth 2 servers, and deployed implementations win.
The #OAuth 2 spec itself leaves many decisions up to the implementor. Instead of describing all possible decisions that need to be made to successfully implement OAuth 2, this post makes decisions that are appropriate for most implementations.
This post is an attempt to describe OAuth 2 in a simplified format to help developers and service providers implement the protocol.