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\n \n $\"LayerWatch\"$ \n \n

\n\n

LayerWatch

\n\n

\n AI-powered 3D print monitoring, failure detection, and timelapse video generation for Bambu Lab printers through Home Assistant.\n

\n\n

\n GitHub ·\n Documentation ·\n Releases\n

\n\n---\n\n## Why LayerWatch?\n\nLayerWatch uses AI vision to watch your Bambu Lab print through a Home Assistant camera and detect failures early:\n\n- Spaghetti and failed extrusion\n- Clogging or severe material buildup\n- Print or support displacement\n- Nozzle collisions\n- Unknown or uncertain print states\n\nThe same captured frames can also be encoded into a timelapse video automatically.\n\n## Features\n\n- Works with Bambu Lab printers through Home Assistant\n- Uses an existing Home Assistant camera entity\n- AI anomaly detection with OpenAI-compatible vision endpoints\n- Trigger by layer change or fixed time interval\n- Shared capture pipeline for AI analysis and timelapse video\n- Automatic MP4 encoding with built-in FFmpeg defaults\n- Home Assistant persistent notifications\n- Optional Bark push notifications\n- Optional Home Assistant-controlled lighting for night captures\n- Automatic data retention and cleanup\n- Chinese and English web interface\n- No RTSP, go2rtc, webhook, or image host configuration required\n\n## Supported Architectures\n\n```text\nlinux/amd64\nlinux/arm64\nlinux/arm/v7\n```\n\n## Quick Start\n\nNo source checkout or compilation is required.\n\n```bash\nmkdir -p \"$HOME/layerwatch/data\"\n\ndocker run -d \\\n --name layerwatch \\\n --restart unless-stopped \\\n --pull always \\\n -p 19091:19091 \\\n -v \"$HOME/layerwatch/data:/app/data\" \\\n -e TZ=Asia/Shanghai \\\n zhf883680/layerwatch:latest\n```\n\nOpen the web interface:\n\n```text\nhttp://:19091\n```\n\nGo to **Settings** and configure:\n\n- Home Assistant URL and long-lived access token\n- Camera, current-layer, and optional print-status entities\n- AI endpoint, API key, model, and maximum calls per print\n- Layer or interval trigger mode\n- Automatic light control with configurable pre-capture delay\n- Home Assistant and Bark notifications\n\nConfiguration and data are preserved in:\n\n```text\n$HOME/layerwatch/data/config.yaml\n$HOME/layerwatch/data/monitor.db\n$HOME/layerwatch/data/frames/\n$HOME/layerwatch/data/videos/\n$HOME/layerwatch/data/events/\n```\n\n## Screenshots\n\n### AI Analysis\n\n[![AI Analysis](https://raw.githubusercontent.com/zhf883680/LayerWatch/main/img/ai-analysis.png)](https://github.com/zhf883680/LayerWatch)\n\n### Timelapse\n\n[![Timelapse](https://raw.githubusercontent.com/zhf883680/LayerWatch/main/img/timelapse.png)](https://github.com/zhf883680/LayerWatch)\n\n### Settings\n\n[![Settings](https://raw.githubusercontent.com/zhf883680/LayerWatch/main/img/settings.png)](https://github.com/zhf883680/LayerWatch)\n\n## Update\n\n```bash\ndocker pull zhf883680/layerwatch:latest\ndocker rm -f layerwatch\n```\n\nRun the same `docker run` command again. The mounted data directory is preserved.\n\n## Docker Tags\n\n```text\nzhf883680/layerwatch:latest\nzhf883680/layerwatch:main\nzhf883680/layerwatch:vX.Y.Z\nzhf883680/layerwatch:sha-\n```\n\n## AI Cost\n\nUsing the example pricing for `qwwen-3.7-flash`:\n\n- Normal input: CNY 0.2 per million tokens\n- Cache-hit input: CNY 0.02 per million tokens\n- Output: CNY 0.8 per million tokens\n\nAt an estimated 30 AI calls per 3D print, the estimated AI cost is approximately:\n\n```text\nCNY 0.0098 per print\n≈ 0.98 Chinese cents\n```\n\nSee the complete calculation in the [GitHub documentation](https://github.com/zhf883680/LayerWatch#ai-费用估算).\n\n## Environment Variables\n\n| Variable | Default | Description |\n| --- | --- | --- |\n| `TZ` | `UTC` | Container timezone |\n| `ADDR` | `:19091` | HTTP listening address |\n| `CONFIG_PATH` | `/app/data/config.yaml` | Configuration file path |\n| `DATA_DIR` | `/app/data` | Database, frames, videos, and alert images |\n| `FFMPEG_BINARY` | `ffmpeg` | FFmpeg executable path |\n\n## Source Code\n\nGitHub: [https://github.com/zhf883680/LayerWatch](https://github.com/zhf883680/LayerWatch)\n\nIf LayerWatch is useful to you, consider giving the repository a star.\n","has_starred","hub_user","immutable_tags_settings",{"_76":11,"_77":78},"enabled","rules",[79],".*","is_automated","permissions",{"_83":22,"_84":11,"_85":11},"read","write","admin","user","storage_size",1005671430,"orgData","recentTags",[92],{"_93":45,"_94":95,"_96":97,"_98":99,"_100":101,"_102":103,"_51":133,"_134":95,"_135":34,"_136":57,"_58":137,"_138":139,"_140":129,"_141":133,"_142":67,"_143":22},"content_type","creator",11251632,"digest","sha256:e69a051e3542fe6de488b7b54aab0249eee2adf19d2937e2554b652600e85235","full_size",59025655,"id",1303239017,"images",[104,120,126],{"_105":106,"_96":107,"_108":109,"_110":111,"_112":113,"_114":115,"_116":109,"_117":-5,"_118":99,"_64":67,"_119":-5},"architecture","amd64","sha256:20283a6e8a0b5cdaf33969a2063fde5fd3907c7a5182da96ca62ea5693fa392e","features","","last_pulled","2026-10-27T08:56:24.527947254Z","last_pushed","2026-09-12T12:20:08.235833493Z","os","linux","os_features","os_version","size","variant",{"_105":121,"_96":122,"_108":109,"_110":123,"_112":124,"_114":115,"_116":109,"_117":-5,"_118":125,"_64":67,"_119":-5},"arm64","sha256:065e31b274d74f03d14335f8601ea3af89f9f01d491a9e28d40af0f9995c9e30","2026-10-27T08:56:24.679476781Z","2026-09-12T12:20:07.819507663Z",57064160,{"_105":127,"_96":128,"_108":109,"_110":129,"_112":130,"_114":115,"_116":109,"_117":-5,"_118":131,"_64":67,"_119":132},"arm","sha256:f16e2fdaa4f49bd232ca02eaa2f90d957a563151ace40cefecfa4c58aec00ff4","2026-10-27T08:56:24.849632562Z","2026-09-12T12:20:08.571481197Z",47672161,"v7","2026-09-12T12:20:11.600525Z","last_updater","last_updater_username","media_type","latest","repository",32422582,"tag_last_pulled","tag_last_pushed","tag_status","v2","sbxKitMetadata","isPotentialSpam","isHubSbxKitsEnabled","showSbxRunInCloud","showSbxLogoOverride","sbxTrademarkText","displaySecurityMetadata","tagAttestations","tagsHaveAttestations",[],"selectedTag","attestationsUrl","routes/_layout.r.$namespace.$reponame.tags",{"_39":158,"_165":166,"_152":177,"_178":11},{"_41":159,"_43":160,"_46":47,"_48":49,"_50":11,"_51":52,"_53":54,"_55":161,"_58":36,"_33":34,"_59":60,"_61":45,"_62":63,"_64":65,"_66":67,"_68":-5,"_69":63,"_70":71,"_72":11,"_73":34,"_74":162,"_80":11,"_81":164,"_86":34,"_87":88},[],[45],[57],{"_76":11,"_77":163},[79],{"_83":22,"_84":11,"_85":11},"tags",{"_167":65,"_168":-5,"_169":-5,"_170":171},"count","next","previous","results",[172],{"_93":45,"_94":95,"_96":97,"_98":99,"_100":101,"_102":173,"_51":133,"_134":95,"_135":34,"_136":57,"_58":137,"_138":139,"_140":129,"_141":133,"_142":67,"_143":22},[174,175,176],{"_105":106,"_96":107,"_108":109,"_110":111,"_112":113,"_114":115,"_116":109,"_117":-5,"_118":99,"_64":67,"_119":-5},{"_105":121,"_96":122,"_108":109,"_110":123,"_112":124,"_114":115,"_116":109,"_117":-5,"_118":125,"_64":67,"_119":-5},{"_105":127,"_96":128,"_108":109,"_110":129,"_112":130,"_114":115,"_116":109,"_117":-5,"_118":131,"_64":67,"_119":132},[],"canDeleteTags","actionData","errors"]

Digest	OS/ARCH	Compressed size
20283a6e8a0b	linux/amd64	56.29 MB
f16e2fdaa4f4	linux/arm/v7	45.46 MB
065e31b274d7	linux/arm64	54.42 MB

zhf883680/layerwatch

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