Helmet detection using yolov8. The model was trained and evaluated using Google Colab.
Helmet detection using yolov8 Firstly Dec 1, 2024 · Object detection technology enables real-time monitoring of helmet-wearing workers, overcoming manual limitations. In recent years, computer vision-based safety helmet detection systems have This study lays the groundwork for the development of a robust and generalizable automated helmet detection system using YOLOv8. We present the Automatic Helmet Detection System, a CNN model trained on image dataset that can detect motorbikes as well as riders wearing helmets. 4 per 100,000 full-time equivalent workers). In International Conference on Intelligence of Things 339 Oct 19, 2021 · In fact, Helmet detection is a special case of Object detection, their purpose is to identify the type of object and the location information contained in it . To identify such violations, automatic helmet detection systems have been proposed and implemented using computer vision techniques. - GitHub - brlivsky/helmet-detection-yolo: We present the Automatic Helmet Detection System, a CNN model trained on image dataset that can detect motorbikes as well as riders wearing helmets. The script then saved the annotated Jun 20, 2023 · Ensuring safety in the workplace is crucial to the wellbeing of workers and the success of organizations. Output: Bounding boxes for Helmets, no-helmet, and license plates. Our work involves replacing the backbone network of the original YOLOv8 algorithm and designing appropriate data augmentation methods, with other adjustments about training strategies. Dataset Insights. Visualize the detections using Supervision. In recent years, computer vision-based safety helmet detection systems have Helmet and vest detection systems ensure worker safety in high-risk professions like construction, mining, and law enforcement. The system uses OpenCV and pre-trained YOLOv3 weights to identify helmets in uploaded images, displaying the results with bounding boxes and confidence scores. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pt file. For data augmentation, the mosaic data augmentation method is employed, which generates many tiny targets . There is a high accident rate within the field [1]. module is a residual feature learning module that enriches the gradient flow Automatic Helmet Detection for Bike Riders using Surveillance Videos in real-time deep-learning artificial-intelligence image-recognition helmet-detection yolov8 Welcome to the Helmet Detection project! This repository contains code for detecting helmets in images using the Ultralytics YOLOv8 model. Object detection: The system accurately detects and classifies helmets and license plates Jul 2, 2021 · ⛑️⚒️ Custom object detection for PPE Detection of Construction Site Workers. To address this challenge, we propose YOLOv8s-SNC, an improved YOLOv8 algorithm for robust helmet detection in industrial scenarios. utilized a single-stage object detection model, YOLOv8, for detecting helmets in real-time. Digital images are Jul 30, 2024 · Improved YOLOv8 safety helmet wearing detection network(CBS modules are used to extract the initial features. This notebooks Helment_Detection_YOLOv5-Jupyter. Meanwhile, the Enhanced Helmet Wearing Detection Using Improved YOLO Algorithm Liuai Wu, Nannan Lu, Xiaotong Yao, and Yong Yang Abstract—To address the accuracy limitations of existing safety helmet detection algorithms in complex environments, we propose an enhanced YOLOv8 algorithm, called YOLOv8-CSS. 999 and utilized a single-stage object detection model, YOLOv8, for detecting helmets in real-time. 29 October 2024 Apr 13, 2023 · To identify such violations, automatic helmet detection systems have been proposed and implemented using computer vision techniques. Prerequisites Before you begin, ensure you have met the following requirements: This project detects individuals not wearing helmets and identifies vehicle license plates using a custom-trained YOLOv8 model. Keywords: Object detection · Construction safety · Helmet detection · Computer vision 1 Introduction The construction industry is considered to be one of the most dangerous industries. This project focuses on enhancing construction site safety through real-time detection of safety gear such as helmets and vests worn by workers, as well as detecting the presence of a person. In many suburbs, urban areas and locals across the globe there is a disconcerting surge in motorcycle accidents has become increasingly evident. in Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023. The objective of this project is to detect helmets in images and videos using the YOLOv8 object detection algorithm. The script was designed to take a folder path as input and detect helmets in all the images and videos contained within that folder. 9, beta2 = 0. Workers in transportation and material moving occupations and construction and extraction occupations accounted for nearly half of all fatal occupational injuries (47. The objective of this research is to enhance the precision of existing helmet violation detection techniques, which are typically reliant on manual inspection Oct 16, 2023 · In the experiment, only using the manually labeled ground truths of daytime data, Faster R-15 CNN obtained 82. The main contributions of this paper are as follows: (1) Developing a real-time helmet violation detection system that utilizes YOLOv8, data augmentation methods, and DCGANs for image generation that is able to perform accurate detections despite varying weather and light conditions. YOLOv8 utilizes a fully convolutional neural network, comprising two major components: the backbone and the head, incorporating a Welcome to the Helmet and License Plate Detector project! This project utilizes YOLOv8, Flask, and OpenCV to detect helmets on people's heads and license plates on vehicles in images or real-time video streams. 5350–5358. Detect Helmets with Yolo v8. Resize input images or video frames. Follow these steps: Open the Google Colab notebook. Helmet Detection using YOLO V8 Feb 21, 2024 · Formula for Momentum — By Ilya Sutskever Million dollar question: Which algorithm to use in practice? Adam seems to be more or less the default choice now ( beta1 = 0. The system employs the Helmet Detection using YOLOv8 with training using your own custom dataset in real-time - 1amsahil/Helmet-Detection-using-YOLO-v8 This project detects individuals not wearing helmets and identifies vehicle license plates using a custom-trained YOLOv8 model. May 10, 2024 · In this study, we introduce an innovative methodology for the detection of helmet usage violations among motorcyclists, integrating the YOLOv8 object detection algorithm with deep convolutional generative adversarial networks (DCGANs). This repo contains notebook for PPE Detection using YoloV8. Apr 16, 2024 · An improved YOLOv8 safety helmet wearing detection network Safety helmet detection at construction sites using YOLOv5 and YOLOR. Apr 12, 2024 · The confusion matrices (Figure 3) delineate the performance of various YOLOv8 models on an object detection task across six classes: person, vest, blue helmet, red helmet, white helmet and yellow helmet. For data Jun 1, 2023 · Request PDF | On Jun 1, 2023, Krunal Patel and others published Safety Helmet Detection Using YOLO V8 | Find, read and cite all the research you need on ResearchGate Aug 31, 2024 · Harnessing object detection capabilities facilitated by the YOLOv8 algorithm and performing text recognition using EasyOCR, we have engineered a solution that can reliably detect motorcycles, interpret helmet status, and read license plates in real-time from video streams. Follow the instructions in the notebook to upload the dataset, install necessary libraries, and run the training and prediction code. YOLOv8, known for its real-time object Load the pre-trained YOLOv8 model for helmet detection. Inference: Real-time detection of helmets, non-helmets, turbans, and license plates. Its ability to detect objects in real-time makes it well-suited for The system uses advanced computer vision techniques and OCR to detect helmets and license plates in real-time. But you will not find a 'Cyclist with helmet' class, rather separate classes like 'person', 'bike' or 'helmet'. 2023. In the past, intelligent system like DPM uses the sliding window method [ 5 ] for object detection: the sliding window slides evenly on the image, in every position the system will For the development of the detection model, we utilized a single-stage object detection model, YOLOv8 [3], for detecting helmets in real-time. This project detects individuals not wearing helmets and identifies vehicle license plates using a custom-trained YOLOv8 model. By leveraging the YOLOv8 object detection algorithm, we Dec 19, 2024 · The existing coal mine safety helmet detection method has problems such as low detection accuracy, susceptibility to environmental impact, poor real-time performance, and a large number of parameters. In the eld of helmet detection, opting for an anchor-free YOLOv8 model circumvents the issues associated with xed sizes and ratios inherent in traditional anchoring methods, which is particularly In an era embarked by technological advancements, enhancing the efficiency of law enforcement processes is crucial for maintaining public safety. The model is trained to detect helmets, the absence of helmets, and license plates. Based on the YOLOv5 repository by Ultralytics. Safety helmet monitoring has become a popular topic in recent years as a result of the success in the field of image processing. Helmet and Seatbelt Detection Project This project is designed to detect helmets and seatbelts from a image input using YOLOv8 models. Ensuring safety in the workplace is crucial to the wellbeing of workers and the success of organizations. Real-time detection of Personal Protective Equipment (PPE) including helmets, safety vests, gloves, and safety glasses. The proposed method introduces the SPD-Conv module to preserve feature 4,764 workers died on the job in 2020 (3. Jul 27, 2024 · Download Citation | On Jul 27, 2024, Sandip Desai and others published Helmet and Number Plate Detection using YOLOv8 | Find, read and cite all the research you need on ResearchGate utilized a single-stage object detection model, YOLOv8, for detecting helmets in real-time. During the exploration phase, it was observed that the datasets exhibit data imbalance, showcasing varying counts between images depicting helmets and those without helmets. The latest version of the You Only Look Once (YOLO) object detection model, YOLOv8, offers significant advancements over its predecessors. Wearing safety helmets can effectively reduce the risk of head injuries for construction workers in high-altitude falls. Aug 11, 2024 · Car Damage Detection Using Python, YOLOv8, and OpenCV. Mar 11, 2024 · Training Losses The overall training progress of the YOLOv8 model for helmet detection displays good trends across several domains (figure 1). Jul 3, 2024 · The third step is upon person detection, which uses the cropped image as the input, and then continues to use predict persons. Safety helmets protect workers from head injuries caused by falling objects, electric shocks, and other hazards. In order to address the low detection accuracy of existing safety helmet detection algorithms for small targets and complex environments in various scenes, this study proposes an improved safety helmet detection algorithm based on YOLOv8, named YOLOv8n-SLIM-CA. In an era embarked by technological advancements, enhancing the efficiency of law enforcement processes is crucial for Jun 29, 2021 · In this paper, we propose an automatic helmet detection of motorcyclists method using an improved YOLOv5 detector which integrates the triplet attention. Pass frames through the YOLOv8 model to detect helmets. Accurate and efficient detection of safety helmets plays a pivotal role in ensuring occupational safety and compliance with safety protocols. Real-time implementation of such systems is crucial for traffic Experimental results indicate that the detection performance of the YOLOv8n-SLIM-CA algorithm has been enhanced not only in general scenarios of real-world applicability but also in complex backgrounds and for small targets at long distances. Sep 4, 2024 · It is of profound significance to detect whether cyclists wear helmets to protect their personal safety and maintain road traffic safety. Usage Guide for Helmet Detection Using YOLOv8. YOLOv8 is the latest state-of-the-art object detection model that has demonstrated high accuracy and speed in real-world applications. 7 Real-time Multi-Class Helmet Violation Detection Using Few-Shot Data Sampling Technique and YOLOv8 The paper [ 1 ] created by Armstrong Aboah, Container Wang, Ulas Bagci, and Yaw AduGyamfi, tackles the vital test of helmet violation detection by integrating a couple shot data sampling technique with the YOLOv8 model. Supports both video streams and static images for versatile usage. The safety of construction site personnel is highly dependent on the adherence of personal protective equipment (PPE) wearing. The objective is to minimize parameters and This project aims to detect helmets and recognize number plates in images using the YOLOv8 model. The Helmet Detection System is an innovative project aimed at enhancing road safety through the automated detection of helmet compliance among motorcyclists. Implementation Approach: After the first model successfully detected motorcycles in the original images, we relied on the coordinates of the bounding boxes to extract those motorcycles. The goal is to identify and segment helmets within the input data, which can be valuable for safety applications, such as industrial settings or sports. Firstly, we introduce C2f-GhostDynamicConv as a powerful tool. The next objective it's to detect not only the helmets but also the people who puntually are unprotected, creating a warning This paper presents a comprehensive study on "Helmet and Number Plate Detection using YOLOv8," focusing on developing an intelligent system to automate the monitoring of traffic rule violations, ultimately enabling efficient challan generation and improving road safety. Krunal Patel Associate Professor & Head of which is a one-stage object detection model. One essential aspect of workplace safety is the use of safety helmets in hazardous environments. Future research directions include: Enriching the Indian Helmet Detection Dataset with a larger and more diverse set of images will further enhance the model’s generalizability and ability to handle various real The wearing of safety helmet directly affects the life safety of workers in the construction site or production workshop, and it is of great significance for the supervision of workers’ helmet wearing. Improved YOLOv8 safety helmet wearing detection network(CBS modules are used to extract the initial features. The YOLO object detection model processes video frames to identify objects such as individuals wearing helmets, riders, and vehicle number plates. This initiative brings together Arduino, Python, and AI object detection to create an intelligent security system. Detection: Post-training, the trained YOLOv8 model is deployed to perform helmet detection on new images or video streams. Building upon this foundation This project utilizes the YOLOv8 (You Only Look Once) deep learning model to perform helmet segmentation in images or videos. This project seamlessly analyzes live video streams and images to ensure safety compliance by detecting helmets. ; Number Plate Recognition: Employs Tesseract OCR to extract and recognize text from number plates for easy identification of vehicles. Utilizes the YOLO object detection algorithm for accurate and efficient detection. This project is set up in a Colab notebook for ease of use and demonstrates how to utilize YOLOv8 for object detection tasks. Generate a CSV file containing the detection labels and results. The existing literature on helmet detection systems is reviewed, revealing a range of methodologies, accuracies, and limitations in current approaches. The model was trained and evaluated using Google Colab. First, the convolutional block attention mechanism (CBAM) is applied to improve the CSPDarkNet53 Safety Helmet Detection using YOLO V8 Dr. This paper proposes an improved YOLOv8n safety helmet detection model, YOLOv8-ADSC, to enhance the performance of Jan 1, 2024 · improved safety helmet detection algorithm based on YOLOv8, named YOLOv8n-SLIM-CA. Oct 28, 2024 · Armstrong Aboah, Bin Wang, Ulas Bagci, and Yaw Adu-Gyamfi. In the construction sector, computer vision technology is extensively employed to detect and monitor the correct usage of helmets by workers. The project workflow involves loading the pre-trained YOLOv8 model, resizing input frames, passing them through the model for object detection, visualizing the detections, and storing the results in annotated images and a CSV file. The application allows users to upload an image and detect helmets in real-time. May 4, 2024 · In various industrial and construction settings, the proper use of safety helmets is fundamental to the well-being of workers. Then the fourth step is Helmet And Non-Helmet Detection using improved YOLOv8 algorithm, namely YOLOv8-SS2 as a. pip install ultralytics roboflow opencv-python Download the datasets: Follow the instructions above to download the helmet and PPE datasets using Roboflow. Real-time multi-class helmet violation detection using few-shot data sampling technique and yolov8. We should therefore come up with an algorithm that not only Safety Helmet Detection of Workers in Construction Site using YOLOv8 Abstract: The safety of construction workers is a paramount concern in the modern construction industry. Data Annotation: Images annotated using LabelImg in YOLO format. 1 December 2024; Creating a Garbage Detection Project in Python using YOLO. Dec 3, 2024 · The use of safety helmets in industrial settings is crucial for preventing head injuries. The C2f. - GitHub - ChiefIvan/Yolo-Model: A real-time helmet detection system powered by YOLOv8. It uses computer vision techniques to analyze real-time camera feeds and instantly alerts authorities when a violation is detected. ipynb shows training on your own custom objects by example of Helmet Detection. The development and evaluation of a real-time YOLOv5 Deep Learning model for detecting riders and passengers on motorbikes, identifying whether the detected person is wearing a helmet and the applicability of DL models to accurately detect helmet regulation violators even in challenging lighting and weather conditions are demonstrated. In the face of increasing two-wheeler usage and the persistent issue of riders neglecting helmet compliance, this paper proposes a groundbreaking Real-Time Helmet Detection System with Vehicle Number Extraction. [11] Romuere Silva, Kelson Aires, Thiago Santos, Kalyf Abdala, Rodrigo Veras, and André Soares. Like YOLOv5, YOLOv8 also uses anchor boxes, which are The use of helmets is crucial for safeguarding the lives of construction workers. Automatic detection of motorcyclists without helmet. One of the main advantages of YOLOv8 is its ability to detect objects on the preprocessed dataset using the YOLOv8 architecture. Hyperparameters are optimized by fine-tuning the model on a pre-trained YOLOv8 model, utilizing methods like transfer learning. module is a residual feature learning module that enriches the gradient flow of the model through cross-layer connections, resulting in a neural network module with a stronger feature representation capability. The method consists of two stages: motorcycle detection and helmet detection, and can effectively improve the precision and recall of helmet detection. Store the resulting annotated images. Explore and run machine learning code with Kaggle Notebooks | Using data from Construction Site Safety Image Dataset Roboflow Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. The proper enforcement of motorcycle helmet regulations is Helmet Detection: Detects whether a rider is wearing a helmet using YOLOv7, YOLOv8, and YOLOv9. A significant proportion of injuries and fatalities on construction sites are attributed to a lack of adherence to safety regulations, often resulting from the non Jun 19, 2024 · we propose a method based on adjusted YOLOv8 algorithm [14] for object detection of safety helmets. Real-time implementation of such systems is Model 2: Detect Helmet and LP using YOLOv8. Addressing the issues of high parameter values and sluggish detection speed in current safety helmet detection algorithms, a feature-enhanced lightweight algorithm, LG-YOLOv8, was introduced. Welcome to the Helmet Detection Using YOLOv8 project! This project utilizes the YOLOv8 model specifically trained for detecting helmets in images and videos. However, scholarly improvements prioritize accuracy, complicating the model and rendering it unsuitable for embedded devices with limited resources. This paper presents a comprehensive study on "Helmet and Number Plate Detection using YOLOv8," focusing on developing an intelligent system to automate the monitoring of traffic rule violations. Currently, there are three classical types of helmet detection algorithms: digital image processing, convolutional neural network (CNN), and Transformer. May 6, 2024 · How to detect a cyclist wearing a helmet? As discussed in the YOLO section above, Pre-trained versions of YOLOv8 can recognize up to 1000 classes out of the box (ImageNet). Even though a helmet is the most important safety gadget, people do not wear it. One essential aspect of workplace safety is the use of Jun 20, 2023 · Ensuring safety in the workplace is crucial to the wellbeing of workers and the success of organizations. The detection is performed using YOLOv8, a state-of-the-art object detection algorithm. Train the model: After downloading the datasets, train the YOLOv8 model using the commands provided for helmet and PPE detection. This module enhances feature extraction miniature target safety helmets, using a lightweight Ghost network model instead of the YOLOv8’s backbone, adopting Dyhead dynamic detection head, extracting features and spatial location Oct 26, 2022 · This study aims to develop an automated helmet detection system using the state-of-the-art YOLOv8 deep learning model to enhance safety monitoring in real-time. and comparatively fast for the recognition and localization in real-time helmet detection. One of the main advantages of YOLOv8 is its ability to detect objects Feb 29, 2024 · Real-time multi-class helmet violation detection using few-shot data sampling technique and yolov8. Traffic safety is a major global concern. E. However, helmet usage violations continue to be a significant problem. Due to the limitations of space, distance and cyclist movement, it is challenging to detect helmet-wearing accurately and quickly. Evaluate the detections using a confusion matrix. Helmet Violation Detection: This component of the project focuses on identifying motorcycle riders who are not wearing helmets. YOLOv8, known for its real-time object Helmet Detection using YOLOv5 training using your own dataset and testing the results in the google colaboratory. Factors such as dense personnel, varying lighting conditions, occlusions, and different head postures can reduce the precision of traditional methods for detecting safety helmets. Custom Model Training: Train a custom YOLOv8 model on head, helmet, person dataset to enhance detection accuracy for specific objects. 4 percent), representing 1,282 and 976 Aboah, A, Wang, B, Bagci, U & Adu-Gyamfi, Y 2023, Real-time Multi-Class Helmet Violation Detection Using Few-Shot Data Sampling Technique and YOLOv8. Below is a comprehensive guide on how to set up and use this project effectively. ipynb & Helment_Detection_YOLOv5-colab. Nov 6, 2024 · In the realm of construction site monitoring, ensuring the proper use of safety helmets is crucial. So, this paper proposes a Miner Helmet detection algorithm based on YOLO, abbreviated as MH-YOLO. However, traditional helmet detection methods often struggle with complex and dynamic environments. 84% as F-measure on the nighttime vehicle detection, while the proposed 16 method Sep 30, 2023 · code:- https://github. Follow the instructions in the notebook to upload the dataset, install necessary Nov 21, 2024 · A safety helmet is indispensable personal protective equipment in high-risk working environments. Helmet usage is a key factor in preventing head injuries and fatalities caused by motorcycle accidents. The code utilizes a pre-trained YOLOv8. Input: Images of motorcycles. This diversity simplifies the process of finding the most suitable model for your specific use case. Welcome to the fascinating world of helmet detection using the powerful YOLOv8 (You Only Look Once) object detection algorithm! 🚀 In this comprehensive guide, we will walk you through the process of implementing helmet detection with utmost professionalism. Explore and run machine learning code with Kaggle Notebooks | Using data from Safety Helmet Detection Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. 12 November 2024; Detecting Rock-Paper-Scissors Sign using Python with YOLOv8. By employing YOLOv8, we aim to enhance safety protocols by automatically identifying and monitoring individuals wearing or not wearing helmets . Helmet-Detection-using-YOLO-v8 This project focuses on leveraging the capabilities of YOLOv8 for helmet detection in real-time scenarios. Aug 5, 2021 · This project implements a helmet detection system using YOLOv3 (You Only Look Once) and Streamlit. Contribute to karamih/Helmet_detection development by creating an account on GitHub. Deep learning (DL) is widely used in object detection tasks due to its ability to create features based on raw data. In order to address the low 2. In view of this, a novel You Only Look Once (YOLOv8) algorithm for helmet-wearing detection is suggested in this paper. List the Wearing safety helmets can effectively reduce the risk of head injuries for construction workers in high-altitude falls. It supports image, video, and real-time (webcam) input, and can be used for safety monitoring in areas like traffic enforcement. You can now support the channel directly through GPay (Google Pay)! H Welcome to the fascinating world of helmet detection using the powerful YOLOv8 (You Only Look Once) object detection algorithm! 🚀 In this comprehensive guide, we will walk you through the process of implementing helmet detection with utmost professionalism. Yet helmets stand as Jun 1, 2023 · A safety helmet detection system based on the You Only Look Once (YOLO) V8 algorithm, which is a state-of-the-art object detection algorithm that has shown superior performance in detecting small objects in real-time, is proposed. One of the main advantages of YOLOv8 is its ability to detect objects These datasets primarily facilitate the binary classification of helmet presence, categorizing images into "With helmet" and "Without helmet" classes. Nov 30, 2023 · Diverse Array of Pre-Trained Models: YOLOv8 provides a comprehensive selection of pre-trained models, catering to a spectrum of tasks and performance requirements. Data augmentation and Helmet Detection with YOLOv8 Welcome to the helmetDetection repository – a project leveraging YOLOv8 for detecting helmet-wearing individuals. Training: YOLOv8 model trained on labeled images. Constant improvements Aug 2, 2024 · Real-time object detection using the YOLOv8 model and OpenCV. YOLOv8 is a state-of-the-art object detection model that has been shown to achieve high accuracy and speed in real-world applications. . This paper presents a lightweight model enhancement approach rooted in YOLOv8. com/freedomwebtech/yolov8helmetdetectionsupport through donations. In this paper, for the current helmet wearing detection algorithm in the complex environment detection accuracy is not high, put forward a yolov8-based improved helmet detection algorithm Object detection system developed with deep learning techniques, capable to recognize if workers in construction areas are using their safety helmet in mandatory areas. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, June 2023. The dataset was custom-made and annotated using Roboflow. The system is developed using the Python programming language, leveraging the OpenCV library for image processing and the YOLO v8 (You Only Look Once) framework for real-time object detection. Over the course of 100 epochs, all three important The project involved creating a script for detecting helmets in images and videos using the YOLOv8 object detection algorithm. The Helmet Detection project Jan 7, 2025 · To address the significantly elevated safety risks associated with construction workers’ improper use of helmets and reflective clothing, we propose an enhanced YOLOv8 model tailored for safety Helmet Detection Based On Improved YOLO V8 Sahir Suma, ANOOP G L, MITHUN B N Helmet detection Christ University Survey Abstract: This paper presents an automated Helmet Detection system for two-wheeler riders in India, using the advanced YOLO v8 algorithm for improved road safety. 5 November 2024; Create a Number Detection System using Python and YOLOv8. We introduce a Coordinate Attention (CA) mechanism We use Google Colab to train the YOLOv8 model and perform predictions. The true labels are presented in rows, whereas the predicted labels are illustrated in columns. YOLOv8 to detect helmet violations. vysc fqhzw tyg yjcqoh yhqjkya klrgsiq hsvuapk wzntptf hpva vqyylu