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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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The 2ndDim: That was I talking about!

@The2ndDim · Post #1506 · 07/28/2021, 08:18 PM

#WantThis#SBC#RaspberryPi https://www.youtube.com/watch?v=huAKEbyPcBc https://forum.radxa.com/t/introduce-the-radxa-zero/6550 有点厉害 性能吊打树莓派ZeroW 可惜视频只走MicroHDMI CPU: AmLogic S905Y2 (4核心 Cortex-A53 1.8 GHz, 12nm制程) GPU: Mali G31 MP2 RAM: LPDDR4 512MB/1GB/2GB/4GB 存储: 板载eMMC 5.1 8/16/32/64/128GB + MicroSD扩展 HDMI: Micro HDMI, HDMI 2.1, 4K@60 HDR 硬件解码: H265/VP9 decode 4Kx2K@60 无线: WiFi4/BT4 或 WiFi5/BT5 USB: 1x USB 2.0 Type C OTG (数据+供电), 1x USB 3.0 Type C host GPIO: 40Pin GPIO, ADC/UART/SPI/PWM 其他: Crypto Engine, 支持外置天线, 一个硬件按钮 系统: 目前有 Android 9, TwisterOS (基于Armbian的Ubuntu 20.04分支), Manjaro, EmuELEC