[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-80893":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":8,"htmlUrl":8,"language":9,"languages":8,"totalLinesOfCode":8,"stars":10,"forks":11,"watchers":12,"openIssues":13,"contributorsCount":13,"subscribersCount":13,"size":13,"stars1d":12,"stars7d":14,"stars30d":15,"stars90d":13,"forks30d":13,"starsTrendScore":16,"compositeScore":17,"rankGlobal":8,"rankLanguage":8,"license":18,"archived":19,"fork":19,"defaultBranch":20,"hasWiki":21,"hasPages":19,"topics":22,"createdAt":8,"pushedAt":8,"updatedAt":23,"readmeContent":24,"aiSummary":25,"trendingCount":13,"starSnapshotCount":13,"syncStatus":26,"lastSyncTime":27,"discoverSource":28},80893,"taubenturret","MLWeber\u002Ftaubenturret","MLWeber",null,"Python",42,5,1,0,4,8,3,44.13,"GNU General Public License v3.0",false,"main",true,[],"2026-06-12 04:01:30","# taubenturret\n\nControl software for the [TaubenTurret system](https:\u002F\u002Fmakerworld.com\u002Fde\u002Fmodels\u002F2801562-taubenturret-automated-pigeon-deterrent): An automated, computer vision driven water turret system for targeted pigeon deterrence.\n\n## Demo & Screenshots\n\n\u003Cp align=\"center\">\n  \u003Cimg src=\"assets\u002Fdemo.gif\" alt=\"Turret firing at a target\" width=\"60%\">\n\u003C\u002Fp>\n\u003Cp align=\"center\">\n  \u003Cimg src=\"assets\u002Fui_live.png\" alt=\"Web Interface - Live View\" width=\"49%\">\n  \u003Cimg src=\"assets\u002Fui_recordings.png\" alt=\"Web Interface - Recordings\" width=\"49%\">\n\u003C\u002Fp>\n\n## Features\n* **Automated Targeting:** Uses a Raspberry Pi Camera to detect motion, triggering an external AI object detection API to identify pigeons.\n* **Pan\u002FTilt Control:** Calculates 3D physical angles from 2D pixel coordinates to smoothly aim the watergun via PWM-controlled servos.\n* **Web Interface:** Includes a built-in FastAPI web UI for viewing the live MJPEG stream, manual firing, and browsing recorded video clips.\n* **Auto-Recording:** Captures and saves `.mp4` video events whenever motion is detected.\n\n## Hardware Requirements\n* 3D models and hardware list available [on makerworld](https:\u002F\u002Fmakerworld.com\u002Fde\u002Fmodels\u002F2801562-taubenturret-automated-pigeon-deterrent).  \n\n## Software Dependencies\n* Python 3.9+ \n* `make` and `uv` for environment management.\n* An active external object detection backend API: [taubenturret-backend](https:\u002F\u002Fgithub.com\u002FMLWeber\u002Ftaubenturret-backend) \n* Required Python packages: `fastapi`, `uvicorn`, `opencv-python` (`cv2`), `numpy`, `requests`, and `picamera2`.\n\n## Configuration\nFirst, create your local environment configuration file by copying the provided template:\n```bash\ncp .env.example .env\n```\nBefore running the system, make sure your properties in the `.env` file are set up correctly. Important settings to verify:\n* **Webserver Auth:** `WEBSERVER_USERNAME`, `WEBSERVER_PASSWORD`, and `WEBSERVER_PORT`.\n* **AI Endpoint:** `DETECTOR_API_URL` to point to your external detection API.\n* **Hardware Tuning:** Validate your `SERVO_PAN_*`, `SERVO_TILT_*`, and `WG_*` constants to ensure your servos don't over-rotate and the watergun relay timings are safe.\n* **Storage:** Ensure `RECORD_DIRECTORY` points to a valid path where the Pi can save video files.\n\n## Installation\nUse the provided `Makefile` to quickly set up the environment and install dependencies:\n```bash\nmake setup\nmake install\n```\n\n## Usage\nStart the main control loop by running:\n```bash\nmake run\n```\nOnce running, you can access the dashboard by navigating to `http:\u002F\u002F\u003Craspberry-pi-ip>:\u003Cwebserver-port>` in your browser and logging in with your HTTP Basic Auth credentials.\n","TaubenTurret 是一个基于计算机视觉的自动化水炮系统，用于针对性地驱赶鸽子。其核心功能包括使用树莓派摄像头检测运动，并通过外部AI对象检测API识别鸽子；通过PWM控制的伺服电机实现平移\u002F倾斜控制，精准瞄准目标；内置FastAPI Web界面，支持实时视频流查看、手动触发水炮以及浏览录制的视频片段；自动记录并保存检测到运动时的视频事件。该项目适合需要减少鸽子干扰的户外场所，如阳台、屋顶等。采用Python 3.9+开发，依赖于OpenCV、NumPy等库，并要求配置一个外部对象检测后端API以完成整个系统搭建。",2,"2026-06-11 04:02:42","CREATED_QUERY"]