Скачать или смотреть Make YOLO do object detection faster with Multiprocessing

This tutorial is a brief introduction to multiprocessing in Python. At the end of this tutorial, I will show how I use it to make TensorFlow and YOLO object detection to work faster.

What is multiprocessing? Multiprocessing refers to the ability of a system to support more than one processor at the same time. Applications in a multiprocessing system are broken into smaller routines that run independently. The operating system allocates these threads to the processors improving the performance of the system.

Why multiprocessing? Consider a computer system with a single processor. If it is assigned several processes at the same time, it will have to interrupt each task and switch briefly to another, to keep all of the processes going.

However, the default Python interpreter was designed with simplicity in mind and has a thread-safe mechanism, the so-called "GIL" (Global Interpreter Lock). In order to prevent conflicts between threads, it executes only one statement at a time (so-called serial processing, or single-threading). This is how our usual Python script works, we do tasks linearly...

In this tutorial, we will see how we can spawn multiple subprocesses to avoid some of the GIL's disadvantages.

Text version tutorial: https://pylessons.com/YOLOv4-TF2-mult...
Full video playlist:    • Yolo v3 Introduction to object detection w...  
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