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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！

I want to build a ChatGPT-style application that works exclusively with images and imposes no built-in content filters. The core capability is image analysis, specifically object detection and recognition, with an immediate focus on identifying people and faces in any photo a user uploads. You’re free to choose the tech stack, but I expect modern computer-vision frameworks—think PyTorch, TensorFlow, or a YOLO-family model—backed by a concise, well-documented API so the system can later expand into other tasks such as classification or captioning if I choose. Fast, server-side inference is important; cloud GPU deployment or an optimized on-prem setup is acceptable as long as latency stays low. Please include: • A clean front-end where users drop an image and i...

I want a small, self-contained Python program that opens my webcam, runs a YOLO pre-trained model, and draws labeled bounding boxes around the usual everyday items—person, bottle, mobile phone, etc.—whenever they appear in the frame. Please write it in clear, well-commented code that leans on OpenCV (cv2) for video capture and display. You’re free to pull the model weights from any reliable public source as long as setup remains simple (a short and one-step download script are perfect). Deliverables • A runnable demo script that starts the webcam and shows real-time detection • All source files, neatly organised, including a brief README explaining environment setup, how to launch the app, and where to place or fetch the YOLO weights • A short ...

I need a straightforward desktop application built in Python that can spot two key classes—Person and Mobile—in a sample video and draw clear bounding boxes with the class name over each detection. This is purely for demonstration and learning, so the implementation should stay clean and easy to read, ideally relying on OpenCV together with a pre-trained YOLO model (v5, v8, or any recent weight file you are comfortable with). How the app should behave • Load a local MP4 (or similar) sample video. • Run real-time inference frame-by-frame, highlighting every detected person or mobile phone. • Display the processed video in a simple desktop window; no fancy UI is needed beyond the live frame and the FPS readout. • Keep all dependencies to standard libr...

Hi, I am looking for a basic AI object detection demo. Requirement: - Detect common objects like person, bottle, mobile, etc. - Should work using webcam or sample video - Output should show bounding boxes with object names This is mainly for learning/demo purpose, so it doesn't have to be very advanced. Preferred: - Python with OpenCV or any simple framework - Basic explanation of how it works Deliverables: - Working demo (video or live) - Source code - Short explanation Budget is limited, but if work is good, I may come back with more tasks. Thank you.