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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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Host Testing and evaluation

@HostEvaluate · Post #873 · 11/06/2023, 02:41 PM

#megalayer#SJC Host Provider: MEGALAYER Location: San Jose Specification: E3-1230v3 | 8GB DDR3 RAM | 1T HDD | 30Mbps & 3xIPv4 | $15 / Mo 本来是 i3 的套餐,但是没货了 CPU 升到了 E3. 现在相似配置的 E3 要 30$。官网的测试 IP 只有香港的,这里就不贴了。有需要的话可以去 report 里面拿网关测,选的是优化网络。 硬盘 IO 有点脱节,除此之外性能倒是不错。回程路由三网走 CN2。流媒体基本上常见的能解锁的都解锁了。 https://paste.debian.net/hidden/97a264ad/ 流媒体报告 https://paste.debian.net/hidden/4949e4a2/ 测速报告: https://result.network-speed.xyz/r/1699017386_ABFJP7_GLOBAL.txt