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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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#miaospeed#dev版 #4.3.2 ✅同步Miaospeed 4.3.1 ✅更新Clash内核 Clash v1.13.0 ✅修复STUN无法传参问题 ✅ipv6 stack 读取问题 ✅默认 ipv6 检测脚本换为更激进的[2606:4700:4700:.1111] ✅增加一个新的动态测速文件方式, DYNAMIC:ALL (欢迎提交测速文件地址) ❌尝试更新Clash.META内核失败,保留原本的版本

#miaospeed#release#v4.3.3 ✅同步Miaospeed 4.3.1 ✅更新Clash内核 Clash v1.13.0 ✅修复STUN无法传参问题 ✅PING和UDP的DNS预解析 ✅ipv6 stack 读取问题 ✅默认 ipv6 检测脚本换为更激进的[2606:4700:4700:.1111] ✅增加一个新的动态测速文件方式, DYNAMIC:ALL (欢迎提交测速文件地址) ✅Miaoko传入STUN或pingAddress无法解析自动切换Miaospeed内置地址 地址:https://github.com/moshaoli688/miaospeed/releases/tag/v4.3.3