{"id":13627591,"url":"https://github.com/t0mer/deepstack-trainer","last_synced_at":"2025-04-15T00:29:42.853Z","repository":{"id":46568734,"uuid":"363251545","full_name":"t0mer/deepstack-trainer","owner":"t0mer","description":"deepstack trainer is a Flask powerd, easy to use web app, hepls us to train and test Deepstack AI","archived":false,"fork":false,"pushed_at":"2025-01-26T22:30:43.000Z","size":2731,"stargazers_count":25,"open_issues_count":5,"forks_count":2,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-03-28T12:21:17.633Z","etag":null,"topics":["deepstack","docker","face-detection","face-recognition","fastapi","home-assistant","home-automation","machine-learning","object-detection","python"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/t0mer.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2021-04-30T20:27:15.000Z","updated_at":"2025-01-26T22:30:47.000Z","dependencies_parsed_at":"2024-04-16T11:05:34.367Z","dependency_job_id":null,"html_url":"https://github.com/t0mer/deepstack-trainer","commit_stats":null,"previous_names":[],"tags_count":8,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/t0mer%2Fdeepstack-trainer","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/t0mer%2Fdeepstack-trainer/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/t0mer%2Fdeepstack-trainer/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/t0mer%2Fdeepstack-trainer/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/t0mer","download_url":"https://codeload.github.com/t0mer/deepstack-trainer/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248983459,"owners_count":21193571,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["deepstack","docker","face-detection","face-recognition","fastapi","home-assistant","home-automation","machine-learning","object-detection","python"],"created_at":"2024-08-01T22:00:36.044Z","updated_at":"2025-04-15T00:29:42.821Z","avatar_url":"https://github.com/t0mer.png","language":"Python","readme":"*Please :star: this repo if you find it useful*\n\n\u003cp align=\"left\"\u003e\u003cbr\u003e\n\u003ca href=\"https://www.paypal.com/paypalme/techblogil?locale.x=he_IL\" target=\"_blank\"\u003e\u003cimg src=\"http://khrolenok.ru/support_paypal.png\" alt=\"PayPal\" width=\"250\" height=\"48\"\u003e\u003c/a\u003e\n\u003c/p\u003e\n\n\n\n# DeepStack Trainer\n[DeepStack](https://deepstack.cc/) is an AI server that empowers every developer in the world to easily build state-of-the-art AI systems both on premise and in the cloud. The promises of Artificial Intelligence are huge but becoming a machine learning engineer is hard. DeepStack is device and language agnostic. You can run it on Windows, Mac OS, Linux, Raspberry PI and use it with any programming language.\n\nDeepStack’s source code is available on GitHub via [https://github.com/johnolafenwa/DeepStack](https://github.com/johnolafenwa/DeepStack/)\n\n[DeepStack Trainer](https://github.com/t0mer/deepstack-trainer) is a [FastAPI](https://fastapi.tiangolo.co) powerd web application that helps us train and test Deepstack AI easelly as possible.\n\n## Features\n- Face Registring.\n- Test face recognition.\n- Test scene recognition.\n- Test object detection.\n- Gallery page, display all uploaded images (For traning only).\n\n## Components used in Deepstack Trainer\n- [FastAPI](https://fastapi.tiangolo.com/) - For running web server\n- [materializecss](https://materializecss.com/) - For web forms\n- [sweetalert2](https://sweetalert2.github.io/) - For alerts and messages\n\n# Installation\n#### Deepstack Installation\nIn order to use Deepstack Trainer we need to install Deepstack.\nWe can do that by running the following command:\n\n```docker run -e VISION-FACE=True -v localstorage:/datastore -p 80:5000 deepquestai/deepstack```\n\nBasic Parameters:\n* -e VISION-FACE=True This enables the face recognition APIs.\n* -v localstorage:/datastore This specifies the local volume where deepstack will store all data.\n* -p 80:5000 This makes deepstack accessible via port 80 of the machine.\n\nWe can also install Deepstack using docker-compose:\n```\nversion: \"3.7\"\nservices:\n  deepstack:\n    image: deepquestai/deepstack:latest\n    restart: unless-stopped\n    container_name: deepstack\n    ports:\n      - \"80:5000\"\n    environment:\n      - TZ=Asia/Jerusalem\n      - VISION-FACE=True\n      - VISION-DETECTION=True\n      - VISION-SCENE=True\n    volumes:\n      - ./deepstack:/datastore\n```\n\n#### Deepstack Trainer Installation\nDeepstack Trainer installation is very easy using docker-compose:\n```\nversion: \"3.7\"\nservices:\n  deepstack_trainer:\n    image: techblog/deepstack-trainer\n    container_name: deepstack_trainer\n    privileged: true\n    restart: always\n    environment:\n      - DEEPSTACK_HOST_ADDRESS=\n      - DEEPSTACK_API_KEY=\n      - MIN_CONFIDANCE=\n    ports:\n      - \"8080:8080\" \n    volumes:\n      - ./deepstack-trainer/db:/opt/trainer/db #Database storing the uploaded photos data (Filename, Person name, Date).\n      - ./deepstack-trainer/uploads:/opt/trainer/photos/uploads #Phisical path for storing the images\n      \n```\n\nBasic Parameters:\n* DEEPSTACK_HOST_ADDRESS - Deepstack API Url (http://localhost:5000)\n* DEEPSTACK_API_KEY - If your Deepstack API is token protected enter your token here or alse leave blank\n* MIN_CONFIDANCE - Minimum Confidence level to identify object or face (Default is 0.70)\n\n\n## Working with Deepstack Trainer\nAfter the docker is up and running, open your browser and navigate to your Deepstack Trainer url. you will be able to see four tabs:\n* Face Learning (Registring).\n[![Face Registring](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/teach%20face.png?raw=true \"Face Registring\")](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/teach%20face.png?raw=true \"Face Registring\")\n\n* Face Recognition\n[![Face Recognition](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/face%20recognition.png?raw=true \"Face Recognition\")](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/face%20recognition.png?raw=true \"Face Recognition\")\n\n* Object Detection\n[![Object Detection](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/object%20detection.png?raw=true \"Object Detection\")](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/object%20detection.png?raw=true \"Object Detection\")\n\n* Scene Detection\n[![Scene Detection](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/scene%20detection.png?raw=true \"Scene Detection\")](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/scene%20detection.png?raw=true \"Scene Detection\")\n\n* Photo Gallery\n[![Scene Detection](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/gallery.png?raw=true \"Scene Detection\")](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/gallery.png?raw=true \"Scene Detection\")\n\n# Integrations and Community\nThe DeepStack ecosystem includes a number of popular integrations and libraries built to expand the functionalities of the AI engine to serve IoT, industrial, monitoring and research applications. A number of them are listed below\n\n* [HASS-DeepStack-Object](https://github.com/robmarkcole/HASS-Deepstack-object)\n* [HASS-DeepStack-Face](https://github.com/robmarkcole/HASS-Deepstack-face)\n* [HASS-DeepStack-Scene](https://github.com/robmarkcole/HASS-Deepstack-scene)\n* [DeepStack with Blue Iris - YouTube video](https://www.youtube.com/watch?v=fwoonl5JKgo)\n* [DeepStack with Blue Iris - Forum Discussion](https://ipcamtalk.com/threads/tool-tutorial-free-ai-person-detection-for-blue-iris.37330/)\n* [DeepStack on Home Assistant](https://community.home-assistant.io/t/face-and-person-detection-with-deepstack-local-and-free/92041)\n* [DeepStack-UI](https://github.com/robmarkcole/deepstack-ui)\n* [DeepStack-Python Helper](https://github.com/robmarkcole/deepstack-python)\n* [DeepStack-Analytics](https://github.com/robmarkcole/deepstack-analytics)\n* [DeepStackAI Trigger](https://github.com/danecreekphotography/node-deepstackai-trigger)\n","funding_links":["https://www.paypal.com/paypalme/techblogil?locale.x=he_IL"],"categories":["Projects by main language"],"sub_categories":["python"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ft0mer%2Fdeepstack-trainer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ft0mer%2Fdeepstack-trainer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ft0mer%2Fdeepstack-trainer/lists"}