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alert-generation-on-detection-of-suspicious-activity-using-transfer-learning

ADAG (Activity Detector and Alert Generator) aims to take real-time videos from CCTV as an input and pass it to the CNN model created with the help of transfer learning and detect ‘Shoplifting’, ‘Robbery’ or ’Break-In’ in the store and notify it to the owners as soon as it occurs. Finally the main motive is to provide a system that detects suspicious activities without human intervention and generates alert, thus making a huge revolution in today’s surveillance system.

anomaly-detection-in-time-series-datasets

This is project made for one of the subjects at Warsaw University of Technology. Its aim is to detect anomaly in time series data.

apitest

awesome

😎 Awesome lists about all kinds of interesting topics

darknet

Convolutional Neural Networks

farmfresh-demo

fraction_object2

framfresh-demo

hellopython

html-homepage

imageai

A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities

imutils

A series of convenience functions to make basic image processing operations such as translation, rotation, resizing, skeletonization, and displaying Matplotlib images easier with OpenCV and Python.

json-api

json-server

llm-qa-bot

ls-frontend

multispanqa

paddledetection

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

python-programming-exercises

100+ Python challenging programming exercises

raspberrypi-facedetection-mtcnn-caffe-with-motion

MTCNN with Motion Detection, on Raspberry Pi with Love

react-creating-a-table1

react-datetime

A lightweight but complete datetime picker react component.

react-firebase-login

React Firebase Login Example

react-homepage1

real-time-event-detection-for-video-streams

Designed and implemented Computer Vision pipeline for Video Stream object detection and classification. This Real-Time classifier used YOLO, MobileNet, and OpenCV to detect cars and classify their type and colour. The evaluation of the video was compared with a ground truth file which our pipeline which we calculated F1-Scores. The system scored 94%, 85%, and 90% for the detection of cars, classification of car type, and classification of car colour respectively.

real-world-anomaly-detection-in-surveillance-videos-pytorch

Real-world Anomaly Detection in Surveillance Videos- pytorch Re-implementation

resume

MY Resume

resume_service

skeleton-based-action-recognition

This repository provides implementation of a baseline method and our proposed methods for efficient Skeleton-based Human Action Recognition.

ttnet-real-time-analysis-system-for-table-tennis-pytorch

Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)