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Shubham Vishwakarma's Projects

android-yolo icon android-yolo

Real-time object detection on Android using the YOLO network with TensorFlow

android-yolo-v2 icon android-yolo-v2

Android YOLO real time object detection sample application with Tensorflow mobile.

apps-android-commons icon apps-android-commons

Upload pictures from Android to Wikimedia Commons. Looking for volunteers! Come say hi at https://groups.google.com/d/forum/commons-app-android and install at https://play.google.com/store/apps/details?id=fr.free.nrw.commons

conversations icon conversations

Conversations is an open source XMPP/Jabber client for the Android platform

darkflow icon darkflow

Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices

deeplearning.ai-summary icon deeplearning.ai-summary

This repository contains my personal notes and summaries on DeepLearning.ai specialization courses. I've enjoyed every little bit of the course hope you enjoy my notes too.

hubism icon hubism

This is a open source android project for Hackfest 2017 called "hubISM", which serves as a solution to all the daily life problems of IIT(ISM) students. The app is being made to be usable in even in offline mode. The app follows an open-source approach for further development in addition to what the team does itself. The app would consist of these features - 1.Detailed map of IIT(ISM) Dhanbad including all the departments , lecture halls , event locations , labs & places of interest. 2.Detailed timetable for all the courses. (Currently for only first year) 3.Contacts containing photo & contact details of all the faculty and other important persons. 4.MIS hyperlink to directly access features such as attendence, grade sheet (Currently will open in external browser window) 5.Academic calender will include all the vacations, exam dates & other important dates. 6.Clubs - this featute consist of a brief introduction of every presently active club in IIT(ISM) Dhanbad with thier logos (Further plan is to include posts made on their Facebook page available at a single place will be known as "Club Feed").

keras-yolo2 icon keras-yolo2

Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).

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