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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 #610 · 02/25/2020, 12:32 PM

来自群友 @ilemonrain 的投稿 HostProvider: Netfront(HongKong) Specification: 4 vCore | 4096M RAM | 128G SAN HDD Network: 1T @ 96Mbps Looking glass: 202.81.237.1 Price: 80HKD/Month #HK#Netfront#HKIX Proxmox虚拟化架构,实际virt-what检测结果为 hyperv+qemu https://paste.ubuntu.com/p/Vb8JWjxYfs/