{"id":20688674,"url":"https://github.com/realkushagrakhare/zeisshackathondemo","last_synced_at":"2026-04-13T05:44:14.086Z","repository":{"id":74147708,"uuid":"118445188","full_name":"realkushagrakhare/ZeissHackathonDemo","owner":"realkushagrakhare","description":"The repository contains the demo code for the Zeiss Hackathon 2017 and was completed in collaboration with Utkarsh Agrawal, Pranav Aggarwal, Pranav Kedia and Rachit Jain","archived":false,"fork":false,"pushed_at":"2018-01-23T00:11:50.000Z","size":5769,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-02-08T00:41:40.051Z","etag":null,"topics":["bag-of-words","iot","machine-learning","mapbox","mapbox-android-sdk","microscope","raspberry-pi-3","remote-shell","smartcity","unity3d","vr","zeiss","zeisshack"],"latest_commit_sha":null,"homepage":null,"language":"C#","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/realkushagrakhare.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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,"publiccode":null,"codemeta":null}},"created_at":"2018-01-22T10:57:11.000Z","updated_at":"2019-01-07T10:39:56.000Z","dependencies_parsed_at":null,"dependency_job_id":"5173d3ae-bf82-4688-b0ff-7fa34afda3e8","html_url":"https://github.com/realkushagrakhare/ZeissHackathonDemo","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/realkushagrakhare%2FZeissHackathonDemo","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/realkushagrakhare%2FZeissHackathonDemo/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/realkushagrakhare%2FZeissHackathonDemo/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/realkushagrakhare%2FZeissHackathonDemo/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/realkushagrakhare","download_url":"https://codeload.github.com/realkushagrakhare/ZeissHackathonDemo/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":242951171,"owners_count":20211572,"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":["bag-of-words","iot","machine-learning","mapbox","mapbox-android-sdk","microscope","raspberry-pi-3","remote-shell","smartcity","unity3d","vr","zeiss","zeisshack"],"created_at":"2024-11-16T23:06:35.034Z","updated_at":"2025-12-24T05:29:02.552Z","avatar_url":"https://github.com/realkushagrakhare.png","language":"C#","funding_links":[],"categories":[],"sub_categories":[],"readme":"Team 21\n\nAbout:-\nThis project is aimed at Smart City solution to detect and  prevent various diseases/health hazards. We aim for various city sewers for this data. The collected data is then used by ML algorithms to predict the results. The final results are then sent to the VR for easy tracking of the results in real-time.\n\nIdle Working:-\nHere we get images from the microscope which are sent to the central server (for the prediction of results by ML algorithms) via a Raspberry Pi 3. These output images (by ML algorithm) are then sent to V.R for real time user-experience.\n\nFolders:-\nRemote Node :- This folder has been deployed with emulated microscope.  \nAnalysisMachine :- This folder is connected to the cloud(Microsoft Azure) . AnalysisMachine does image recognition using ‘Bag of Words’ and ‘SVM’. Dataset was for Marburg virus was taken from www.image-net.org\nVR :- This folder is related to VR. This app is made in Unity 3D using MapBox APIs and VR SDK.\n\nLibraries used:-\nAzure SDK, Android SDK, Unity 3D.\nPython:- paramiko, opencv, sklearn\nWindows:- Zeiss Labscope , Bitvise SSH server (These 2 in total is emulated microscope.)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frealkushagrakhare%2Fzeisshackathondemo","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frealkushagrakhare%2Fzeisshackathondemo","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frealkushagrakhare%2Fzeisshackathondemo/lists"}