Vehicle detection dataset free download. The provided dataset is a sample of real-time data collected from around 30 different four-wheeled vehicles over a span of four months. It consists of hours of traffic scenarios recorded with a variety of sensor modalities, including high-resolution RGB, grayscale stereo cameras, and a 3D laser scanner Jul 30, 2021 · Top Open Datasets for Autonomous Driving Projects. VEDAI: "Vehicle Detection in Aerial Imagery: A small target detection benchmark". read () gray = cv2. Classes are typically at the level of Make, Model, Year, e. The project also provides code and instructions for running the model on different platforms and evaluating the results. Check out our latest dataset release of Perception Object Assets, which includes 31k unique perception object Dec 31, 2021 · 1 bus's found. Therefore, the proposed method is composed of three deep neural networks: Feature Network Sep 27, 2022 · To reduce the false detection rate of vehicle targets caused by occlusion, an improved method of vehicle detection in different traffic scenarios based on an improved YOLO v5 network is proposed. Indian Vehicle dataset for Detection,Classification problems. For your convenience we’ve divided them into several categories, e. 8 GB) Download: Night Test Set (2. The videos are recorded at 25 frames per seconds (fps), with 4 days ago · 06:10. The dataset is captured from a stereo rig mounted on a car, with a resolution of 640 x 480 (layered), and a framerate of 13–14 FPS. The Rawseeds Project: Indoor and outdoor datasets with GPS, odometry, stereo, omnicam and laser measurements for visual, laser-based SemanticKITTI. Datasets were constructed by logging CAN traffic via the OBD-II port from a real vehicle while message injection attacks were performing. Kenk and 1 other authors Download PDF Abstract: Recently, self-driving vehicles have been introduced with several automated features including lane-keep assistance, queuing assistance in traffic-jam, parking assistance and crash avoidance. Our CarDD contains 4,000 high-resolution car damage images with over 9,000 wellannotated instances of six damage categories (examples are shown in Figure 1). ret, frames = cap. Using this Dataset. CHAIN_APPROX_NONE) The code above finds all the contours in the entire image and keeps them in the variable ‘ contours’. Download 12416 free images labeled with bounding boxes for object detection. Citation. Refresh. Udacity generously provided a balanced dataset with the following characteristics: ~ 9K images of vehicles Refresh. The goal is to accurately locate and track the lane markings in real-time, even in challenging conditions such as poor lighting, glare, or complex road Download scientific diagram | Examples of different datasets for fast vehicle detection. Part 1 to Part 4 together contain 200,000 images (50,000 x 4) and Part 5 has 13,714 images. The field of machine learning is changing rapidly. in 3D Object Representations for Fine-Grained Categorization. Download scientific diagram | The number of each category vehicle in the XDUAV dataset and the UAVDT dataset. The ONCE dataset consists of 1million LiDAR scenes and 7 million corresponding camera images. Data collection occurs at varying frequencies: OBD data is recorded at a rate of 1Hz, equating to one record per second, while accelerometer data is sampled at a higher frequency of 25Hz, resulting in 25 data points per second. To address this issue, this paper proposes a vision-based vehicle detection and counting system. KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute) is one of the most popular datasets for use in mobile robotics and autonomous driving. The dBehaviourMD is a contribution of annotations from Intel®. You are working on a self-driving car. It has been trained on the PASCAL VOC 2007/2012 object detection image sets, as well as the KITTI 2D object detection set for self-driving vehicles. For creating the output video from frames or images, we need cv2. Oct 30, 2023 · The IEEE dataset included co-collected multispectral-LiDAR, hyperspectral imagery, and high-resolution RGB imagery. 6 GB) Oct 31, 2023 · A Novel Dataset for CCTV Traffic Camera based Accident Analysis. This project is a Keras implementation of Faster-RCNN. Our aim is to resolve the lack of public data for research about automatic spatio-temporal annotations for traffic safety in the roads. Roboflow has free tools for each stage of the computer vision pipeline that will streamline your workflows and supercharge your productivity. In order to facilitate object detection and localization, every parking space in the images is annotated with a bounding box mask. The dataset consists of images of parking spaces along with corresponding bounding box masks. Install Microsoft's Visual Object Tagging Tool (VoTT) Annotate images; Training. 2012 Tesla Model S or 2012 BMW M3 coupe. from publication: A Feature-Enhanced Anchor-Free Network for UAV Vehicle Detection To this end, we contribute with Car Damage Detection (CarDD), the first public large-scale dataset designed for vision-based car damage detection and segmentation. To collect data, you’ve mounted a camera to the hood of the car, which takes pictures of the road ahead every few seconds while you drive around. hybrid miles model vehicle efficiency + 4. " GitHub is where people build software. Currently, I don't have a detailed tutorial about it, but you can get some extra information in the OpenCV homepage, see Cascade Classif Welcome to the UA-DETRAC Benchmark Suite! UA-DETRAC is a challenging real-world multi-object detection and multi-object tracking benchmark. Indeed, with the rapid development of deep neural networks, vision-based approaches for vehicle tracking by detection have significantly advanced compared to existing approaches. 2021: Camera, LiDAR: China: ONCE(One millioN sCenEs) dataset can be used for 3D object detection in the autonomous driving scenario. Introduced by Jonathan Krause et al. ai This dataset is an extremely challenging set of over 50,000+ original Vehicle images captured and crowdsourced from over 1000+ urban and rural areas, where each image is manually reviewed and verified by computer Dataset. Use heatmap to filter non-vehicle windows and draw bounding box around vehicles. Our repository of open image datasets consists of free public datasets for computer vision projects. The data were captured from an airborne platform at an altitude of 500 m, which gave a top-down view of cars in the imagery, as opposed to some other vehicle detection datasets that provide more of an angled view. This dataset is a subset of the Open Images Dataset. For example, G1 has images of highways during the day with only one car in them. This dataset contains crime data as far back as the year 1921. data. Download scientific diagram | Beijing Institute of Technology (BIT)-Vehicle dataset. This sub-dataset was built to perform driver behaviour recognition tasks. To associate your repository with the license-plate-detection topic, visit your repo's landing page and select "manage topics. About Dataset. To run the Docker container, run the following command: bash scripts/start_api. The annotations are licensed by Google LLC under CC BY 4. detectMultiScale (gray, 1. It contains temporal annotations of activities related to distraction. Different driving environments: highway and urban. This dataset represents the location and characteristics of major (Part 1) crimes against persons such as homicide, shooting, robbery, aggravated assault, etc. In the last decade, we have seen notable progress in object detection in natural imagery; however, such development has been sluggish for airborne imagery, not only due to large-scale variations and Aug 12, 2020 · Download a PDF of the paper titled DAWN: Vehicle Detection in Adverse Weather Nature Dataset, by Mourad A. # output. To this end, we contribute with Car Damage Detection (CarDD), the first public large-scale dataset designed for vision-based car damage detection and segmentation. However, due to the different sizes of vehicles, their detection remains a challenge that directly affects the accuracy of vehicle counts. The PKLot dataset contains 12,416 images of parking lots extracted from surveilance Open Dataset – Waymo. Tools. Jul 14, 2022 · This dataset has a collection of 383 raw images of Indian vehicles in different illumination conditions using Infrared Day/Night Camera. Dataset. Roboflow provides a great guide on creating a license plate and vehicle object detection model. LISA Traffic light dataset: Download: Day Train Set (12. ai This dataset is an extremely challenging set of over 50,000+ original Vehicle images captured and crowdsourced from over 1000+ urban and rural areas, where each image is manually reviewed and verified by computer Feb 27, 2023 · Deep learning-based classification and detection algorithms have emerged as a powerful tool for vehicle detection in intelligent transportation systems. And in the end, we will display the frames VEDAI is a dataset for Vehicle Detection in Aerial Imagery, provided as a tool to benchmark automatic target recognition algorithms in unconstrained environments. Use the YOLOv7 PyTorch export. 0. More details about this dataset are avialable at our ECCV 2018 paper (also available in this github) 《Towards End-to-End . Explore and run machine learning code with Kaggle Notebooks | Using data from Car Object Detection. The dataset consists of 10 hours of videos captured with a Cannon EOS 550D camera at 24 different locations at Beijing and Tianjin in China. The vehicle orientation dataset is hosted on AWS S3 (Asia-pacific, Tokyo) bucket. Oct 25, 2018 · Download: Vehicle Detection Dataset. Dec 6, 2022 · Description: The Cars dataset contains 16,185 images of 196 classes of cars. Pixel Level Segmentation Based Drivable Road Region Detection and Steering Angle Estimation Method for Autonomous Driving on Automatic vehicle detection from aerial imagery is of interest for various applications such as traffic management, parking surveillance, urban planning and emission calculation. 1%, respectively, which is a Jan 1, 2020 · Vehicle detection is one of the widely used features by companies and organizations these days. This dataset is for non-commercial use only. Using a Canon EOS 550 camera, 10 hours of video were captured at 25 frames per second, and then the footage was processed. Download: Day Test Set (3. If you are benefited from this paper, please cite our paper as follows: Real-World Fuel Efficiency. We have provided convenient downloads in many formats including VOC XML, COCO JSON, Tensorflow Object Detection TFRecords, and more. On the other hand, G5 has images of crosswalks during the day or at night with multiple cars and license plates (LPs). world, inc 196 datasets • 122420 papers with code. It contains real traffic accident videos captured by dashcam mounted on driving vehicles, which is critical to developing safety-guaranteed self-driving systems. The images are divided almost 50-50 between training and scoring, with 8,144 Download Correctly Formatted Custom Data. Since the overall size of the dataset is quite big (~100GB), we have split the vehicle orientation dataset into five parts for convenience of users. Mar 5, 2020 · Drone-based vehicle detection aims at finding the vehicle locations and categories in an aerial image. : Computer vision task types. occurring within the City of Baltimore. contours, hierarchy = cv2. Now we will perform the vehicle detection and counting in a video. Downloads. The bounding box mask outlines the boundary of the parking space, marking its position and shape within the image. The data is divided into almost a 50-50 train/test split with 8,144 training images and 8,041 testing images. Our Car Accident Detection and Prediction (CADP) dataset consists of 1,416 video If the issue persists, it's likely a problem on our side. The Audi Autonomous Driving Dataset (A2D2) features over 41,000 labeled with 38 features. The proposed method uses the Flip-Mosaic algorithm to enhance the network’s perception of small targets. geospatial gis infrastructure streets traffic + 4. If the issue persists, it's likely a problem on our side. This paper presents detection and classification of Mar 30, 2022 · In this paper we present a vehicle detection and tracking method for traffic video analysis based on deep learning technology. The vehicles contained in the database, in addition of being small, exhibit different variabilities such as multiple orientations, lighting/shadowing changes, specularities or occlusions. To build the Docker image, run the following command: docker build -f dockerfile. More details about this dataset are avialable at our ECCV 2018 paper (also available in this github) 《Towards End-to-End License Plate Detection and Recognition: A Large Dataset and Baseline》. The UA-DETRAC data set contained 8,259 manually May 17, 2023 · The proposed model has been trained using the open-source dataset Crash Car Detection Dataset, and its produced precision, recall, and mAP are 93. To build and test your YOLO object detection algorithm follow the below steps: Image Annotation. 4 GB) Download: Night Train Set (0. Around 2. Dec 30, 2019 · Intelligent vehicle detection and counting are becoming increasingly important in the field of highway management. Vehicle Detection Using Deep Learning and YOLO Algorithm is a project by MaryamBoneh on GitHub that demonstrates how to detect and classify vehicles in images and videos. https: 82 papers with code • 11 benchmarks • 15 datasets. Annotate own dataset using Roboflow annotate - a self-serve image annotation tool built right into Roboflow. python yolo vehicle object-detection vehicle-tracking vehicle-detection vehicle-counting python-opencv detection-algorithm yolov3 yolo-vehicle-counter Download Dataset. No Active Events. FLIR_ADAS: Teledyne FLIR Free ADAS Thermal Dataset v2. VideoWriter () method. However, this task presents a significant challenge in terms of its practical implementation due to the absence of point cloud data from automotive-grade hybrid solid-state LiDAR, as well as the limitations regarding the generalization ability of data-driven The Stanford Cars dataset is developed by Stanford University AI Lab specifically to create models for differentiating car types from each other. Problem Statement. findContours(thresh. We extracted the in-vehicle data from KIA SOUL. Varying traffic conditions: light to dense traffic Paper: A General Active-Learning Framework for On-Road Vehicle Recognition and Tracking Jun 15, 2023 · Aiming at designing an algorithm managing the speed and accuracy of the detector in real-time vehicle detection, Zarei et al. The The vehicle data is stored in a two-column table, where the first column contains the image file paths and the second column contains the vehicle bounding boxes. The aerial images are now extensively used for many applications, especially in the area of intelligent transportation systems. ai This dataset is an extremely challenging set of over 50,000+ original Vehicle Device used : Captured using mobile phones in 2020-2022 Usage : Vehicle Detection, Automobile detection, Construction vehicle detection, Self This dataset could be used to create a vehicle and license plate detection object detection model. 0 (see Release Notes for more info) Hello everyone, An easy way to perform vehicle detection is by using Haar Cascades. world, inc2024 data. api -t ruhyadi/vehicle-detection-api:latest . from the available vehicle data set [45]. May 27, 2018 · Implement sliding-window technique to detect vehicles in an image. Nevertheless, it is still a challenge when the objects are hard to distinguish, especially in low light conditions. May 29, 2023 · The research and development of deep learning methods are heavily reliant on large datasets, and there is currently a lack of scene-rich datasets for synthetic aperture radar (SAR) image vehicle detection. g. A multi-type vehicle target dataset collected in different scenarios was set up. This project aims to count every vehicle (motorcycle, bus, car, cycle, truck, train) detected in the input video using YOLOv3 object-detection algorithm. We provide car-hacking datasets which include DoS attack, fuzzy attack, spoofing the drive gear, and spoofing the RPM gauge. Each frame had a resolution of 960*540 pixels. 14 proposed Fast-Yolo-Rec algorithm. odometry information) would be useful, and feel free to extend the dataset's scripts on Github. We present a novel dataset for traffic accidents analysis. Split the data set into a training set for training the detector and a test set for evaluating the detector. The project uses a YOLOv3 model trained on a custom dataset of car, truck, bus, and motorcycle images. This data set was captured predominantly in the Beijing-Tianjin-Hebei area. This dataset can be used for imge recognition and object detection for driver assistance systems, autonomous driving, etc. Researchers have made mount of efforts in this area and achieved considerable progress. The INRIA Person dataset is a dataset of images of persons used for pedestrian detection. See image data for more details. Image classification datasets; Object detection datasets; Segmentation datasets; Use cases. Furthermore, each image is available in We add 14 publicly available image datasets with real anomalies from diverse application domains, including defect detection, novelty detection in rover-based planetary exploration, lesion detection in medical images, and anomaly segmentation in autonomous driving scenes. Vehicle Detection and Counting Video and Output Video. 16,185 images and 196 classes of all the cars you'll ever dream of. SyntaxError: Unexpected token < in JSON at position 4. Contribute to mdhaisne/awesome-vehicle-datasets development by creating an account on GitHub. 1, 1) After this step, we will use the OpenCV to draw rectangles around the vehicles. The limitations of the number of high-quality labeled training samples makes the single vehicle detection methods incapable of accomplishing acceptable accuracy in road vehicle detection. Currently, most of the datasets available for vehicle detection algorithms are based on images of the global North. Produce a pipeline and generate video of results. Now, we can run the Docker container. Waymo is in a unique position to contribute to the research community, by creating and sharing some of the largest and most diverse autonomous driving datasets. 3 TB in total, A2D2 is split If the issue persists, it's likely a problem on our side. Download pre-trained weights; Train your custom YOLO model on annotated images; Inference. Nov 12, 2018 · A dataset with annotated objects is critical for understanding and implementing YOLO object detection. Further, Most of the car images in this dataset are of Chinese models. A new high definition highway vehicle dataset May 2, 2020 · Real-time object detection using YOLOv3 1. Create notebooks and keep track of their status here. booktitle = {Pattern Recognition - 40th German Conference, {GCPR} 2018, Stuttgart, Germany, September 10-12, 2018, Proceedings}, year = {2018} A topic-centric list of Vehicles datasets. To tackle this problem, we The lack of known freely available car detection datasets was the main motivation behind our research. sh. We needed a dataset for our research where we trained a YOLO object detection model that detects cars on aerial imagery. This is a report of city vehicles and actual MPG compared to EPA estimated MPG. The dataset resembles the Indian highway toll collection plazas. world's Admin for City of New York · Updated 2 years ago. View, compare, and download vehicle detection datasets at SourceForge Jan 1, 2021 · Download full-text PDF. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster. It can use VGG16, ResNet-50, or ResNet-101 as the base architecture. Note that this model requires YOLO TXT annotations, a custom YAML file, and organized directories. Next, we'll download our dataset in the right format. Use the rest for evaluation. If you consider our dataset useful, please cite the following. It can be used to train and test LP detectors, as the authors labeled the position of If the issue persists, it's likely a problem on our side. Detect objects in new images and videos This dataset consists of images of niche Indian Vehicle such as Autorikshaw, Tempo, trucks, etc. Jan 1, 2020 · The vehicle detection results using YOLOv4 trained on different aerial image datasets, (a) VEDAI, (b) DLR-MVDA, (c) COWC, (d) KIT-AIS, and (e) VAID. The training dataset for this project consisted of vehicle and non-vehicle images as per the following samples: Figure 1. CARL-D: A vision benchmark suite and large scale dataset for vehicle detection and scene segmentation. In this work, we present a new aerial image dataset, VAID (Vehicle Aerial Imaging from Drone), for the development and evaluation of vehicle Sep 16, 2020 · This dataset is open-source under MIT license. Person detection dataset; Face detection dataset We re-labeled the dataset to correct errors and omissions. It is observed that there is very little or no dataset available on these niche vehicles like autorickshaw, tempo, trucks, etc. Tagged. It empowers smart city traffic management and disaster rescue. It consists of: Three color video sequences captured at different times of the day and illumination settings: morning, evening, sunny, cloudy, etc. Jun 27, 2022 · Arbitrary-oriented vehicle detection via aerial imagery is essential in remote sensing and computer vision, with various applications in traffic management, disaster monitoring, smart cities, etc. (Journal of Visual Communication and Image Representation 2015) KAIST_rgbt: "Multispectral Pedestrian Detection: Benchmark Dataset and Baseline Add this topic to your repo. The dataset contains 97,942 labels across 11 classes and 15,000 images. Try V7 now. RETR_TREE,cv2. Datasets contain each 300 intrusions of message injection. from publication: An improved YOLOv2 for vehicle detection | Vehicle detection is one of the important Car Crash Dataset (CCD) is collected for traffic accident analysis. Access the dataset. 3: Stanford Cars Dataset [2] This dataset mainly focus on vehicle make and model. Second, we provide a rigorous review of both classical and latest vehicle detection methods, including machine vision-based, mmWave radar-based, LiDAR-based, and sensor fusion-based methods. It aids in building a model that can detect and classify various objects in images or videos. world's Admin for City of Bloomington, IN · Updated 3 years ago. It takes the path with extension as the first parameter; the second parameter is the codec for the output format, then we also need to pass frames per second and height and This dataset is collected by DataCluster Labs. 8 GB) Download: Tools and Description. Download: CVRR-HANDS 3D DATASET. Dataset with 32 projects 1 file 1 table. Read full-text. We do encourage new benchmarks, let us know if additional data (e. Python3. 143. Classes:carbikebicycletrucktempo travellerbusautonumber platestracktorvan. It contains 5502 scene images with 210 unique fine-grained labels of multiple vehicle types organized in a three Oct 25, 2017 · In this exercise, we build a vehicle detector by employing a conventional computer vision technique called Histogram of Oriented Gradients (HOG), combined with a machine learning algorithm called Support Vector Machines (SVM). For this, we will use the coordinates that we got while using the haar cascade. A2D2 Dataset. 169. Introduction The dataset consists of niche Indian vehicle images for classification and object detection. This dataset mostly contain images of Chinese models. We provide datasets which include DoS attack, fuzzy attack, impersonation attack, and attack free states. The data is split into 8,144 training images and 8,041 testing images, where each class has been split roughly in a 50-50 split. The images from left to right correspond to Nov 24, 2020 · The availability of commercial UAVs and low-cost imaging devices has made the airborne imagery popular and widely available. 1. @inproceedings{boxy2019, title={Boxy Vehicle Detection in Large Images}, author={Behrendt, Karsten}, Driving Datasets – Over 10 hours of driving data (LIDAR, camera frames and more) CMU Visual Localization Data Set: Dataset collected using the Navlab 11 equipped with IMU, GPS, Lidars and cameras. download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster. To address this issue and promote the development of SAR vehicle detection algorithms, we constructed the SAR Image dataset for VEhicle Detection (SIVED) using Ka, Ku, and X bands of data To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster. world; Terms & Privacy © 2024 data. The images contain one or two samples of a V ehicle Detection Data Set, Matlab Official Web Site. You should have the Docker image with the name ruhyadi/vehicle-detection-api:latest. Oct 31, 2023 · This dataset represents a very challenging set of images of vehicles of niche classes. Among 196 car classes covered by the Stanford Car dataset, 16,185 images have been collected from the rear of each car. Jul 22, 2013 · Last page update: 19/10/2016 Last version: 1. CCD is distinguished from existing datasets for diversified accident annotations, including environmental attributes The PKU dataset has almost 4,000 images categorized into five groups (G1-G5) that show different situations. 0 license. May 26, 2023 · Three-dimensional (3D) object detection based on point cloud data plays a critical role in the perception system of autonomous driving. cvtColor (frames, cv2. This is a dataset for vehicle detection. YOLO Object Detection Playground | 1000+ Videos. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. COLOR_BGR2GRAY) cars = car_cascade. Dec 30, 2022 · The previous fine-grained datasets mainly focus on classification and are often captured in a controlled setup, with the camera focusing on the objects. Dataset with 25 projects 10 files 2 tables. Residual Networks for Vehicle Detection. copy(),cv2. Unexpected token < in JSON at position 4. 8% and 98%, 96. 2: CompCar [4] In this dataset most of the images are extracted CCTV cameras. Explore and run machine learning code with Kaggle Notebooks | Using data from Vehicle Data Set. Loading About data. (a) KITTI dataset: we classify the vehicles into four categories of car, van, truck, and tram under Dataset Download and Paper(s) ONCE Dataset (One millioN sCenEs)- Huawei Corp. Some examples of labels missing from the original dataset: Stats. Traffic Signals GIS Data. Download: LISA Traffic Sign Dataset — Annotated Frames. You can find more details on dBehaviourMD in our ECCV Workshop 2020 paper. The dataset will be useful in developing intelligent models for applications such as automated toll collection, number plate detection and recognition, driverless vehicles, suspicious vehicle Open-source dataset for license plate detection and recognition, described in 《Towards End-to-End License Plate Detection and Recognition: A Large Dataset and Baseline》. In the future research, that model will be deployed on an edge device for car detection on drones or other UAVs. ->. As a critical component of this project, you’d like to first build a car detection system. SAR_vehicle_detection_dataset-> 104 SAR images for vehicle detection, collected from Sandia MiniSAR/FARAD SAR images and MSTAR images; ERA-DATASET-> A Dataset and Deep Learning Benchmark for Event Recognition in Aerial Videos; SSL4EO-S12-> a large-scale dataset for self-supervised learning in Earth observation Jun 15, 2022 · Now let’s find the contours in the detection zone of the above frame: # find contours. This technology uses computer vision to detect different types of vehicles in a video or real-time Aug 19, 2022 · The testing set contains 1,804 images in three video clips. Lane Detection is a computer vision task that involves identifying the boundaries of driving lanes in a video or image of a road scene. The Stanford Cars dataset consists of 196 classes of cars with a total of 16,185 images, taken from the rear. Jul 27, 2023 · First, we briefly describe tasks, evaluation criteria, and existing public datasets for vehicle detection in autonomous driving. vehicle detection datasets free download. They combined a new Yolo-based Feb 19, 2024 · The public UA-DETRAC data set was used to train the vehicle target detection model in this study. Select 60% of the data for training. This dataset is open-source under MIT license. Jun 1, 2022 · This dataset is mainly focuses on vehicle licence plate. INRIA Person Dataset. Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. We introduce the first Fine-Grained Vehicle Detection (FGVD) dataset in the wild, captured from a moving camera mounted on a car. be ol ng co hl rl hu bw vp yn