Script to read frames from the camera using multithreading Python
This package provides a video system for django, allowing admin users to upload videos and have them displayed on the site.
Streaming live python OpenCV or Pillow frame to HTML locally and remotely using Redis, Flask, and NodeJs server.
基于实时的视频流,利用图像识别功能,自动检测视频中的运动物体。包括后端数据处理和前端 web 页面实时显示结果, 广泛应用在小区入侵监测,智能家居的安防,老人智能看护等领域; 加入人脸识别系统，结合其他的智能产品，实现高度自动化的物联网自动化运行环境。同时支持异常图像上传至云服务器,可以配合手机APP,实现全方位,实时监控的目的。
后端+前端+算法模型，机器学习项目 demo。Flask + vue + ML, full stack machine learning project construction.
LiveGBS国标(GB28181)流媒体服务软件： 提供用户管理及Web可视化页面管理； 提供设备状态管理，可实时查看设备是否掉线等信息； 实时流媒体处理，PS（TS）转ES； 设备状态监测、云台控制、录像检索、回放； 提供RTSP、RTMP、HTTP-FLV、HLS等多种协议流输出； 对外提供服务器获取状态、信息，控制等HTTP API接口；支持语音对讲；支持云端录像；TCP、UDP两种方式信令传输以及UDP、TCP被动、TCP主动三种视频流传输方式；
DEEP LEARNING BASED SECURITY SURVEILLANCE MONITORING SYSTEM WITH REAL-TIME WHATSAPP,EMAIL,SMS ALERTS.
The current forest surveillance systems methods consume a lot of resources and are less efficient, not reliable and require a constant human presence whose tasks can be easily automated using new technology. To solve these problems we propose an autonomous surveillance system which uses object detection to identify specified animals. It is capable of monitoring forest fires, intruders, wildlife etc, all at once and alerts the concerned officials immediately and precisely. It has a hybrid object detection system using HAAR and Backpropagation neural network algorithms which can be used to train and detect animals and predict from the data obtained respectively. This helps in detecting various unwanted visitors, dangerous animals, or restricted tools into the forest. The system can not only store the video feed but can also determine population , track a specific animal or human and sends the pictures to your email directly along with real-time video monitoring via the internet which allows the users to monitor from anywhere in the world and sends instant alerts to your phone via an SMS even in remote areas in case of emergencies, and it stores all the data in a repository. We can control the system using a windows app which allows us to select which animals to be detected by the camera modules and their alert levels along with other settings and also provides a detailed analysis on various things like forest fires, animal population, trespassed areas etc, to users in simple charts. It is a smart, automatic, modular system which is cheap and easily expandable.
