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Source channel @githubtrending · Post #14949 · Jul 12

#jupyter_notebook#darknet#pytorch#scaled_yolov4#yolor#yolov3#yolov4#yolov7 YOLOv7 is a powerful tool for detecting objects in images and videos. It is fast, accurate, and can work well on devices with limited power, making it useful for real-time applications like self-driving cars and surveillance systems. YOLOv7 uses advanced techniques like Feature Pyramid Networks to detect objects of different sizes and can handle complex scenes with overlapping objects. This makes it beneficial for users who need quick and precise object detection in various environments. https://github.com/WongKinYiu/yolov7

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djangoproject

@djangoproject · Post #132 · 09/01/2016, 02:47 PM

https://bit.ly/coroutines At Open Source Bridge and #PyGotham in 2015, and at SCALE14x, I demonstrated that you can code a Python 3 #async framework in under an hour. I start the demo by writing a callback-based async framework, built on non-blocking sockets and a simple event loop. Then I adapt the framework to use generator-based #coroutines, which are cleaner than callbacks but still more efficient than threads for async I/O.