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I am looking for an experienced Computer Vision Engineer to build a robust c++ script that automatically detects and maps the scoring rings on a B27 shooting target from standard smartphone photos. "i want it in c++" The End Goal: Given a photo of a used B27 shooting target (taken at various angles and lighting conditions), the script must automatically correct the perspective, locate the target, and accurately identify/draw the scoring rings (X, 10, 9, 8, 7) so that bullet impacts can eventually be scored. The Challenges (Why this isn't a basic OpenCV tutorial): Bullet Holes: The paper is covered in bullet holes. Traditional edge detection (like finding the white rings using Canny/Hough) often fails because the bullet holes destroy the lines. Perspective Distortion: Photos ...
我正在搭建一套基于 YOLOv8 的垃圾分类演示,需要完整的软硬件方案: • 软 件 – 使用 Python + YOLOv8 训练/部署模型,能在普通电脑上直接运行; – 摄像头以 USB 方式接入树莓派,再把画面实时传输到电脑; – 识别目标包含:塑料、纸张以及易拉罐,模型应能在画面上框出目标并同时在终端输出中文文字描述(如“检测到易拉罐”); – 运行界面可为简单命令行或轻量 GUI,只要识别结果与文字描述同步显示即可; – 提供完整的源代码、模型权重、依赖清单与一键安装脚本。 • 硬 件 – 树莓派主板(任意 3/4/5 型号均可)+ 原厂摄像头模块; – 摄像头默认 USB 连接,可在本地测试无误后将整套硬件打包寄送给我(运费我承担)。 • 交付要求 1. 远程演示识别过程,确认三类垃圾均能被准确框选并输出文字; 2. 打包代码与文档(环境配置、使用说明、模型训练思路); 3. 寄送硬件并提供收件追踪号; 4. 收到设备后,如有环境差异需协助我本地跑通。 如果你熟悉树莓派、YOLOv8 和 Python 部署,并具备打包邮寄能力,期待与你合作!
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