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Source channel @githubtrending · Post #15511 · Feb 20
#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
Search: #sequential
@djangoproject · Post #98 · 07/11/2016, 12:22 PM
https://docs.python.org/3/library/asyncio.html #asyncio #Asynchronous programming is more complex than classical “#sequential” programming: see the Develop with asyncio page which lists common traps and explains how to avoid them. Enable the debug mode during development to detect common issues.
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@djangoproject · Post #153 · 09/03/2016, 08:20 PM
http://wla.berkeley.edu/~cs61a/fa11/lectures/streams.html In this chapter, we continue our discussion of real-world applications by developing new tools to process #sequential#data. In Chapter 2, we introduced a sequence interface, implemented in Python by built-in data types such as #tuple and #list. #Sequences supported two operations: querying their length and accessing an element by index. In Chapter 3, we developed a user-defined implementations of the sequence interface, the Rlist class for representing recursive lists. These sequence types proved effective for representing and accessing a wide variety of sequential #datasets.