Hack Cameras CCTV FREE
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Updated
Aug 6, 2024 - Python
Hack Cameras CCTV FREE
Surveillance Perspective Human Action Recognition Dataset: 7759 Videos from 14 Action Classes, aggregated from multiple sources, all cropped spatio-temporally and filmed from a surveillance-camera like position.
detect the no of people every second entering building gate. #person-detection
Fight Detection From Surveillance Cameras by fine-tuning a PyTorch Pretrained Model
Detects the abnormal behaviors of passengers on a ship so we can prevent accidents from occurring
Construction of a lumbar weapon detection system through CCTV cameras with the help of artificial intelligence neural network (YOLO_v5), which has been trained by the private dataset of Pashtaw.
A real-time human counter that uses HOG and SVM. Developed as project for the Computer Vision course at Sapienza University of Rome (2021-22)
This is a facerecognition model made using python. It mainly gets a face img as a input and identifies that face in a video.
Access Public CCTV Cameras Easily.
Detects firearms in real-time from CCTV videos, highlighting them within bounding boxes for immediate attention
detect objects from cctv camera
This project addresses the escalating challenge of gun violence through the development of an advanced gun detection system.
Synthetically Generated Surveillance Perspective Human Action Recognition Dataset: 6901 Videos from 10 action classes, made by a 3D Simulation, all cropped spatio-temporally and filmed from a surveillance-camera like position.
Textile Detection from CCTV Surveillance videos
An indigenous system design for anomaly detection from CCTV camera feed
Custom Objct Detection : Training and Testing
This is the repository of Team Incognito - SE3. This contains all the source code to build the FireProtector applications.
Violence recognition in streaming video using Transfer Learning and MoViNets. The project leverages state-of-the-art deep learning techniques to create an efficient and accurate violence detection system.
This project aims to develop a real-time face mask detection and classification system using computer vision techniques.
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