Pytorch gun detection. Training code, dataset and trained weight file available.

Pytorch gun detection Detect guns in photos and in videos using Yolov3. Sep 17, 2024 · This project implements real-time weapon detection using the YOLOv3 (You Only Look Once) object detection model. Contribute to manhminno/Gun-Detection-In-Photos-Videos development by creating an account on GitHub. Gun to scene and gun to object are the two types of gun occlusion. We created a A low-powered, affordable gunshot detection system for urban areas using machine learning - gunshot-detection/PyTorch-PANNs. Inference on still images and videos, transfer learning on custom datasets, and serialization of models to files are just a few of Detecto's features. Neural Network model for image detection Chapter 1: Introduction The project begins with the import of essential libraries such as Torch, TorchVision, Matplotlib, and Torch's neural network modules. As incidents of violence continue to rise globally, there is an urgent need for effective surveillance technologies that can quickly identify potential threats. e. The main idea of this library is to make training, validation and inference with PyTorch's object detection models as simple as possible. Also included is the code that I used for recognition and accuracy scoring on holdout data, which consisted of 579 gunshot A real-time weapon detection system for security surveillance that identifies firearms and distinguishes them from harmless objects. May 12, 2025 · The underlying machine learning models are often built using frameworks like TensorFlow or PyTorch. （For own study and reference others' implementation --- welcome to pull issues 😳） Aims at helping Policemen to identify a potentially dangerous situation like a person holding a deadly weapon and is trained especially for detection of the presence of GUNS in an image. Includes YOLO, SSD, and Faster Learn to run YOLOv5 for real-time object detection on NVIDIA Jetson devices using Docker. Contribute to wolfworld6/Pytorch-Retinaface-Mask-Detection development by creating an account on GitHub. Special thanks to the PyTorch community whose Model Zoo and Model Examples were used in generating these model archives. PyTorch, a deep - learning framework, provides a flexible and efficient platform to implement and train SSD A PyTorch implementation of Single Shot MultiBox Detector from the 2016 paper by Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang, and Alexander C. This is the third in a series of tutorials I'm writing about implementing cool models on your own with the amazing PyTorch library. Nov 5, 2024 · Develop a real-time object detection tool using PyTorch that identifies objects in live video feeds, suitable for applications in environments such as: Retail: Customer movement analytics Real-time object detection using YoloV1 in PyTorch on video and webcam feed. Pytorch-Segmentation-Detection is a library for image segmentation and object detection with reported results achieved on common image segmentation/object detection datasets, pretrained models and scripts to reproduce them. cfg to yolo-obj. The models internally resize the images so that they have a minimum size of 800. Basic knowledge of PyTorch, convolutional neural networks is assumed. Notifications You must be signed in to change notification settings Fork 31 Jun 5, 2023 · Weapon detection (WD) provides early detection of potentially violent situations. scaling in Depth, Width and Resolution dimensions) to achieve state-of-the-art accuracy with lower FLOPS and less parameters than models that scale a single dimension. Building object detection skeletons in real-time is a complex task that requires a deep understanding of computer vision, machine learning, and software engineering. Apr 1, 2024 · Crimes caused by guns or knives are very common in many places, especially in places where gun laws do not exist. This repository is my reproduction of classical object detection in pytorch. We also introduce a light Nov 14, 2025 · Object detection is a fundamental task in computer vision, with applications ranging from autonomous driving to surveillance systems. Each model is published separately. cfg with the same content as in yolov3. cfg#L696 yolov3. May 12, 2021 · Children exposed to gun-related violence, whether they are victims, perpetrators, or witnesses, can experience negative psychological effects over the short and long terms. Learn to run YOLOv5 for real-time object detection on NVIDIA Jetson devices using Docker. Weapon detection Open Data provides quality image datasets built for training Deep Learning models under the development of an automatic weapon detection system. It supports detection from images, videos, or real-time webcam input. Jul 23, 2020 · Source image by Hanns Adrian Böhme on Unsplash Traffic sign detection with YOLOv4 Colab Notebook for training YOLOv4 with custom dataset (traffic signs) Outline Introduction Why YOLOv4? Data preparation Training with Colab Predict with YOLOv4 Conclusion I. Training code, dataset and trained weight file available. Nov 14, 2025 · Object detection is a fundamental task in computer vision, aiming to identify and localize objects within an image. EfficientNet is an architecture that takes advantage of compound scaling (i. Built using deep learning (Faster R-CNN with PyTorch) and OpenCV. Early detection of crime is critical to public safety. SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection - sgrvinod/a-PyTorch-Tutorial-to-Object-Detection YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite. - pclubiitk/model-zoo Dec 1, 2021 · The present work leads to an analysis of real-time video frames from public places where guns or pistols are not allowed and the quickly response or prevention of a crime is needed. The perfect guide for someone looking to try PyTorch for the first time or new to object detection. Nowadays Gun-related violence threatens our most fundamental human right that is the right to life. Contribute to KRBAI-Vision-UB/Yolov5-Object-Detection development by creating an account on GitHub. PyTorch, a popular deep learning framework, provides an ideal platform for implementing and A structured training framework built on PyTorch Lightning specifically designed for Fake Audio Detection research. Apr 13, 2025 · A real-time weapon detection system built with Flask, YOLOv8, and OpenCV, designed for surveillance and security applications. A brief summary of our dataset and model was recently presented at the 2019 Asia-Pacific Signal and Information Processing About [CVPR 2024] Official RT-DETR (RTDETR paddle pytorch), Real-Time DEtection TRansformer, DETRs Beat YOLOs on Real-time Object Detection. This Android application is designed to perform live object detection using the YOLOv8 machine learning model. Object detection is a fundamental task in computer vision that is a combination of identifying objects within an image and localizing them by drawing a bounding box around them. Apr 11, 2023 · The implementation of the gun detection algorithm using YOLOv7 offers a powerful and efficient solution for detecting guns in real-time video feeds, with high accuracy and minimal false positives. cfg#L783 change [filters=255] to filters= (classes + 5)x3 in the 3 [convolutional TorchVision Object Detection Finetuning Tutorial # Created On: Dec 14, 2023 | Last Updated: Sep 05, 2025 | Last Verified: Nov 05, 2024 For this tutorial, we will be finetuning a pre-trained Mask R-CNN model on the Penn-Fudan Database for Pedestrian Detection and Segmentation. This project is a Machine Learning–based URL classification system that detects whether a website is: Malicious / Phishing or Legitimate (Safe). This project processes live video feeds to detect weapons (e. The process began with the collection of a diverse dataset containing images of various types of firearms and other weapons. Jun 29, 2021 · A recently created Github repository - The deeplite-torch-zoo package is a collection of popular CNN model architectures and benchmark datasets for PyTorch framework. This implementation is primarily designed to be easy to read and simple to modify. Contribute to PoojaWani03/Fire-and-gun-object-detection-on-pytorch development by creating an account on GitHub. A real-time weapon detection system for security surveillance that identifies firearms and distinguishes them from harmless objects. This application uses a custom-trained YOLOv8 model to detect weapons, specifically guns, in images and videos, and presents results via an interactive Streamlit interface. Step-by-step guide with Docker image setup and testing. YOLOv11: How to Train for Object Detection on a Custom Dataset Object detection is one of the most exciting and widely-used applications of deep learning and computer vision, and YOLO (You Only Look Once) has been a revolutionary model in this field. In this tutorial, we will guide you through the process of Contribute to PoojaWani03/Fire-and-gun-object-detection-on-pytorch development by creating an account on GitHub. Module for classifying hand-written digits from the MNIST dataset. The Single Shot MultiBox Detector (SSD) is a popular and efficient object detection algorithm that can achieve real - time performance while maintaining high accuracy. This is a class project as part of EE046211 - Deep Learning course @ Technion. 84–88 (2017) Gun Detection in Surveillance Videos using Deep Neural Networks JunYi Lim , Md Istiaque Al Jobayery, Vishnu Monn Baskarany, Joanne MunYee Lim , KokSheik Wongy and John Seez In this project we attempt to use a YOLOv5 model to detect weapons in various scenarios. This is a PyTorch Tutorial to Object Detection. The system is designed to detect various weapons such as knives, guns, and bombs using a pre-trained YOLOv3 model. For example, after 2000 iterations you can stop training, and later just copy yolo-obj_2000. Itamar Ginsberg • Alon Nemirovsky Weapon Detection with Transfer Learning Background Dataset Weapon detection Open Data provides quality image datasets built for training Deep Learning models under the development of an automatic weapon detection system. Weapons datasets for image classification and object detection tasks are described and can be downloaded below. Number of studies show that handheld gun is the primary weapon used for various crimes like break-in, robbery, shoplifting, and rape. 0, and Keras for Computer Vision and Deep Learning, with detailed coverage of OpenCV4 and example code. It contains 170 images with 345 instances of pedestrians, and we will use it to illustrate how to use the new features A real-time weapon detection system for security surveillance that identifies firearms and distinguishes them from harmless objects. Detecto is also built on top of PyTorch, allowing an easy transfer of models between the two libraries End-to-End Object Detection with Transformers. Real-Time Detection Transformer (RTDetr) is a cutting-edge object detection framework that combines the power of transformers with the need for real - time performance. Model Description Silero VAD: pre-trained enterprise-grade Voice Activity Detector (VAD). The official and original Caffe code can be found here. The main objective of this project is to design and implement an advanced system for the autonomous detection of firearms and knives. PyTorch, a popular deep learning framework "Join Caterpillar's Cat Digital team in Chennai — build generative AI & digital-twin solutions that power modern manufacturing. Develop Deep Learning Applications with Google Colaboratory - on the free Tesla K80/Tesla T4/Tesla P100 GPU - using Keras, Tensorflow and PyTorch. A simple Python project using YOLOv5x and PyTorch to perform real-time object detection on images. In this paper, we present a novel gun and weapon detection system using the YOLOv8 (You Only Look Once) object detection model. A Realtime ML model for weapon detection through webcam. Currently, there are hardly any high quality / modern / free / public voice activity detectors except for WebRTC Voice Activity Detector (link). Using a series of YOLOv4 object detection algorithms, we demonstrated experiments on our dataset, achieving 0. With this course, learn PyTorch, TensorFlow 2. This framework provides a modular, scalable approach to training and evaluating FAD models. The system processes video input, highlights detected weapons with bounding boxes, and can extract frames containing weapons for further analysis. Identifying the precise location of a gunshot—or getting as close as humanly possible—is crucial for saving lives and ensuring public safety Oct 23, 2024 · This research paper presents the development of an AI model utilizing YOLOv8 for real-time weapon detection, aimed at enhancing safety in public spaces such as schools, airports, and public transportation systems. Create file yolo-obj. Threat violence is a modern human rights issue. - therealomm/Malicious-URL-detection-using-REsMLP Jul 23, 2025 · This article discusses about YOLO (v3), and how it differs from the original YOLO and also covers the implementation of the YOLO (v3) object detector in Python using the PyTorch library. Although many algorithms were implemented, only YOLOv8 was selected for further experiments. Created by GunDetectionProject. Set up a Python development environment and install essential libraries like PyTorch, OpenCV, Flask, and MQTT for building your detection system. Training Yolo v3: 1. Gunshot Detection in Targets: An Object Detection Benchmark This repository is dedicated to comparing and benchmarking state-of-the-art Convolutional Neural Networks (CNNs) for detecting gunshot holes in various surfaces and materials. - Manish8798/Weapon-Detection-with-yolov3 Jul 31, 2022 · Detecting Weapons using Deep Learning Model Weapon Detection Violence committed with guns puts a significant impact on public, health, psychological, and economic costs. Temporal Action Detection with Structured Segment Networks Project Website Note: We have released MMAction, a full-fledged action understanding toolbox based on PyTorch. 🔥 🔥 🔥 Pytorch版本的Retainface, 用于人脸和口罩检测. May 13, 2024 · Gun and weapon detection is a challenging task that has a wide range of applications in security, surveillance, and law enforcement. Enterprise-grade Speech Products made refreshingly simple (see our STT models). A real-time weapon detection web application developed as a group project for the Image Processing and Computer Vision (IPCV) course at IIIT Lucknow. weights from Detect guns in photos and in videos using Yolov3. Explore and run machine learning code with Kaggle Notebooks | Using data from multiple data sources The pre-trained models for detection, instance segmentation and keypoint detection are initialized with the classification models in torchvision. In NanoDet-Plus, we propose a novel label assignment strategy with a simple assign guidance module (AGM) and a dynamic soft label assigner (DSLA) to solve the optimal label assignment problem in lightweight model training. The system combines transfer learning, RESTful API architecture, and containerization to create a production-ready object detection service capable of identifying and localizing firearms in digital images. Aug 1, 2019 · Weapon detection and localization results obtained by using Yolov3 [15] Warsi et al. [15] proposed a system for visually detecting the presence of a firearm in real-time video surveillance. Mar 20, 2025 · Step-by-step guide on building YOLOv11 model from scratch using PyTorch for object detection and computer vision tasks. Gunshot Detection Systems: Acoustic gunshot detection systems use arrays of microphones to detect the sound of gunfire. 63 mAP. Fire and Gun detection using yolov3 in videos as well as images. In: Proceedings of the 7th International Conference on Computer and Communication Technology, pp. YOLOv8 (You Only Look Once version 8) is known for its real-time object detection capabilities, and this app brings that functionality to Android devices. cfg#L610 yolov3. The models expect a list of Tensor [C,H,W], in the range 0-1. Nov 24, 2024 · Learn how to build a robust object detection model using PyTorch and OpenCV in this hands-on guide. latest for weapon detection. The models are grouped under different datasets and different task types such as classification, object detection, and segmentation. Gun violence remains a critical concern. Apr 11, 2023 · The implementation of the gun detection algorithm using YOLOv7 offers a powerful and efficient solution for detecting guns in real-time video feeds, with high accuracy and minimal false Oct 23, 2024 · To create an effective weapon detection model using YOLOv8, a comprehensive approach was undertaken. Sep 1, 2022 · A handheld gun detection using faster r-cnn deep learning. Berg. 572 open source Automatic-Rifle-Bazooka-Grenad images plus a pre-trained Weapons Detection model and API. Contribute to Mohsin-424/Deep-Learning-PyTorch development by creating an account on GitHub. If you live in Python, PyTorch, and edge AI — apply by Nov 27. 1 day ago · In computer vision, many tasks—such as edge detection, optical character recognition (OCR), or training lightweight models—do not require color information. Refer example for more details on Nov 5, 2019 · Understand and apply PyTorch’s Dataset & DataLoader to train an Object Detector with your own COCO formatted data This repository contains the training code I used to build a classifier which can take an audio recording of a gunshot and recognize the gun used among 18 different gun models. Using the YOLOv8 (You Only Look Once) framework and transfer learning techniques, we seek to improve security effectiveness through continuous, real-time surveillance. ” This model is designed to perform object detection tasks with a focus on achieving real-time performance while maintaining high accuracy. streaming computer-vision cctv-cameras surveillance pytorch transfer-learning pretrained-models pretrained-weights 3dcnn pytorch-cnn pytorch-implmention resnet-18 finetuning cctv-detection fight-detection Updated on Feb 10, 2022 Jupyter Notebook We'll also need pytorch, and torchvision, as well as clone the torchvision GitHub repository to use the training and evaluation utilities provided for the Torchvision Object Deteciton Tutorial that we are using to train a basic object detection model. It includes implementation for SSN as well as other STOA frameworks for various tasks (action classification, temporal action detection, and spatial-temporal action detection). , guns, knives, suspicious objects), logs detections in a database, sends instant alerts via a web interface A real-time weapon detection system for security surveillance that identifies firearms and distinguishes them from harmless objects. Contribute to facebookresearch/detr development by creating an account on GitHub. Jul 14, 2024 · Unlock the power of real-time object detection using PyTorch! Learn to create fast, accurate models for real-world applications. ipynb at master · AnanthVivekanand Apr 13, 2020 · Learn how to train an EfficientDet object detection model using a custom dataset in this comprehensive guide. YOLOv5 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection, instance segmentation and image classification tasks. Reference Relevant source files This page provides external resources, related projects, academic references, and community links that informed the development of this fire detection system. It analyzes website URLs using feature extraction, WHOIS data, Google search results, HTML content patterns, and a trained deep learning or ML model (PyTorch/SKLearn). cfg) and: change line batch to batch=64 change line subdivisions to subdivisions=8 change line classes=80 to your number of objects in each of 3 [yolo]-layers: yolov3. Utilizing pre-trained object detection networks, you can detect and recognize 90 common objects that your computer vision application will “see” in everyday life. Introduction A while ago, I wrote a tutorial on training YOLOv3 with a custom dataset (gun detection) using the free GPU provided by Contribute to PoojaWani03/Fire-and-gun-object-detection-on-pytorch development by creating an account on GitHub. Despite deep learning (DL) algorithms and sophisticated closed-circuit television (CCTVs), detecting weapons is In this video I show you a super comprehensive step by step tutorial on how to use yolov8 to train an object detector on your own custom dataset!Code: https: A collection of tutorials on state-of-the-art computer vision models and techniques. Contribute to gowrishgalaxy/Retinal_blindness_detection_Pytorch-master development by creating an account on GitHub. Jul 27, 2022 · To achieve real-time faster performance and better detection accuracy, YOLOv4 is fine-tuned, and the preset anchors trained on DIAT-Weapon annotated dataset. Explore everything from foundational architectures like ResNet to cutting-edge models like YOLO11, RT-DETR, SAM NanoDet is a FCOS-style one-stage anchor-free object detection model which using Generalized Focal Loss as classification and regression loss. g. For training guides and Oct 26, 2019 · Microphone Array-Based Direction of Arrival of Gunshot Detection . Our journal paper, "Deep multi-level feature pyramids: Application for non-canonical firearm detection in video surveillance" has been accepted by EAAI and can be found here. We use Transfer-Learning by performing additional training on a pre-trained network, using the new dataset, to achieve this task. Feb 12, 2025 · Introduction Object detection is a crucial aspect of computer vision, with applications in diverse fields such as self-driving cars, surveillance systems, and healthcare. We plan to use the EfficientNet architecture to detect guns in real-time. Converting RGB images to grayscale simplifies the input by reducing the number of channels from 3 (Red, Green, Blue) to 1 (intensity), which lowers computational costs and speeds up training. It takes an image as input and About Real-time object detection with ROS, based on YOLOv3 and PyTorch Readme BSD-3-Clause license Activity RT-DETR is an object detection model that stands for “Real-Time DEtection Transformer. This project implements an end-to-end computer vision pipeline for real-time weapon detection using deep learning. To propose a model for inclusion, please submit a pull request. Real time processing is another main problem in gun detection system that arises during detection. After each 100 iterations you can stop and later start training from this point. GitHub Gist: instantly share code, notes, and snippets. Pytorch implementation of RetinaNet object detection as described in Focal Loss for Dense Object Detection by Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He and Piotr Dollár. Gun violence is a daily tragedy that affects the lives of people Aug 1, 2022 · Where guns are commonly used for hunting, such as in the tropical forests of the Americas and Africa, acoustic detection can potentially provide a solution to this monitoring challenge. , guns, knives) in images or video streams. Contribute to Falcons-ai/weapons_detection_trainer_yolov8_open development by creating an account on GitHub. Oct 13, 2021 · Overview of Threat Detection Model We know that security is always a main concern in every area because of the rise in crime rates in crowded areas or in suspicious isolated areas. Contribute to jarif87/object-detection-notebooks development by creating an account on GitHub. 🚀 Detects multiple objects, displays bounding boxes, and saves output — fast, efficient, and begin Detect guns in photos and in videos using Yolov3. This project is a real-time weapon detection system utilizing OpenCV and YOLO (You Only Look Once) object detection framework. For information about the datasets used in this repository, see Dataset Sources. It defines a simple neural network architecture using PyTorch's nn. . Our approach focuses Nov 1, 2021 · Learn to train an object detector using PyTorch and Python. Jan 17, 2025 · Learn how to build object detection models using PyTorch and OpenCV for real-world applications. cfg (or copy yolov3. Jul 23, 2025 · Your All-in-One Learning Portal: GeeksforGeeks is a comprehensive educational platform that empowers learners across domains-spanning computer science and programming, school education, upskilling, commerce, software tools, competitive exams, and more. It serves as a gateway to further reading, alternative implementations, and complementary tools. Implementations of various Deep Learning models in PyTorch and TensorFlow. PyTorch Object Detection This is a wrapper library for the PyTorch object detection models. - sendeniz/yolov1-real-time-obj-detection To achieve real-time faster performance and better detection accuracy, YOLOv4 is fine-tuned, and the preset anchors trained on DIAT-Weapon annotated dataset. Aug 2, 2021 · In this tutorial, you will learn how to perform object detection with pre-trained networks using PyTorch. Aug 21, 2023 · Learn how to train YOLOX models for real-time object detection in PyTorch by creating a hand gesture detection model. This page lists model archives that are pre-trained and pre-packaged, ready to be served for inference with TorchServe. Train a custom YOLOv7 model to detect weapons from a dataset, enabling it to identify various types of weapons (e. 84–88 (2017) Gun Detection in Surveillance Videos using Deep Neural Networks JunYi Lim , Md Istiaque Al Jobayery, Vishnu Monn Baskarany, Joanne MunYee Lim , KokSheik Wongy and John Seez Pytorch implementation of RetinaNet object detection as described in Focal Loss for Dense Object Detection by Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He and Piotr Dollár. If you're new to PyTorch, first read Deep Learning Detecto is a Python package that allows you to build fully-functioning computer vision and object detection models with just 5 lines of code. cbj afxzezkjk ayarq crpwij ercfs okiw xxb qcq ohgvwh gzeucry haiwl cinu vyyw tjyq epzhykm