Human detection github. com/fnrvjsn/one-piece-wano-arc-anime-episode.
As we can see that there are so many new technological advancements happening such as biometric authentication in our smart phones for face detection, adult content filtering, hand gesture recognition is a modern way of human computer interaction i. All python scripts performing detection, pose and segmentation using the YOLOv8 model in ONNX. 7. OpenCV Human Detection using HOG descriptor. A simple python script to capture live video as input, detect human faces, blur them and display the output with blurred or censored faces. The method achieves 90. A human detection system is developed on Matlab and FPGA: The 130x66 RGB pixels of static input image was attracted features and classified with/without human by using Histogram of Oriented Gradient (HOG) and Support Vector Machine (SVM) algorithm, respectively. tsv: Each row corresponds to one argument Argument ID: The unique identifier for the argument Other human detection from drone image using deeplearning - yadhukm07/human_detection. It is a bottom-up approach therefore, it first detects the keypoints belonging to every person in the image, followed by assigning those key-points to a distinct person. xml Human detection in videos The objective of the project is to show human presence in a given Youtube video (e. Dataset for "Human Being Detection from UWB NLOS Signals: Accuracy and Generality of Advanced Machine Learning Models" Topics Posenet converts an image of a human into a mere skeleton which captures its position and movement over time, but discards any precisely identifying features and the original camera image. The program uses HOG and LBP features to detect human in images. To associate your repository with the human-detection Oct 2, 2021 · humans_counter. - hernanrazo/human-voice-detection Such samples might have affected the accuracy of the model. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. Human Detection using HOG as descriptor and Linear SVM as classifier, detector using sliding window scans image pyramid, finally, apply NMS(non-maximum suppression) to remove redundant and overlapping bounding boxes. Considering today’s lifestyle, people just sleep forgetting the benefits sleep provides to the human body. "Real-time human detection for robots using CNN with a feature-based layered pre-filter. To compute the HOG (Histograms of Oriented Gradients) feature from an input image and then classify the HOG feature vector into human or no-human by using a 3-nearest neighbor (NN) classifier. Clone the github repository into the local system by using the below command- In our paper we use a dataset of over 21,000 human annotations of generated text to show that humans can be trained to improve at detection and that certain genres influence generative models to make different types of errors. Applications based on Wi-Fi CSI (Channel state information), such as indoor positioning, human detection - qqq-tech/esp-csi-human-detection Detects Pedestrians in images using HOG as a feature extractor and SVM for classification - vinay0410/Pedestrian_Detection data_utils. Main purpose was comparing 3 pretrained models for speed and accuracy. To associate your repository with the human-detection Developed a real-time social distancing system with YOLOv3 and SSD for human detection, OpenCV for video processing, and Perspective transformation for bird's-eye view. ├── 0-elephant-detection-only # This prototype has elephant detection feature only. Provides some applications using CSI data, including RainMaker cloud reporting and human activity detection. I also set model. First, use the HOG feature only to detect humans. 2) Frame level detection of unusual activities In a minimum-distance matrix, the smaller the value of an element, the less likely an unusual activity is to occur in the respective block. Motivation - Why do we need to detect the key-points of the human body? Motion sensing technology is increasingly deployed in many applications where human detection is reqired such as gaming, security and military. Monitoring movements are of high interest in determining the activities of a person and the attention of a person. The Fall Detection algorithm fits well with the Ambianic framework of privacy preserving AI for home monitoring and automation. It detects facial coordinates using FaceNet model and uses MXNet facial attribute extraction model for extracting 40 types of facial attributes. Stage 1 (Human Detection) A real-time human detector using Faster RCNN Inception V2 COCO model , implemented using Python. Soon, this technique took it's way to the detection of other objects. Background substraction and Human Detection. The following diagram illustrates the overall system architecture. semantic-segmentation people-detection human-segmentation Contribute to Andreylive/UAV-human-detection development by creating an account on GitHub. Welcome to the YOLOv8 Human Detection Beginner's Repository – your entry point into the exciting world of object detection! This repository is tailored for beginners, providing a straightforward implementation of YOLOv8 for human detection in images and videos. In this project we have worked on the problem of human detection,face detection, face recognition and tracking an individual. . Triggs in their research paper - "Histograms of Oriented Gradients for Human Detection, CVPR, 2005". I propose a human detection and tracking scheme based on the pre-trained Histogram of Oriented Gradients (HOG) Descriptor and Linear Support Vector Machine (SVM) included in the OpenCV library. YOLOv8 re-implementation for human detection using PyTorch. The following models are packaged together into a downloadable model bundle: Pose detection model: detects the presence of bodies with a few key pose landmarks. # Capture a frame from the Pi Camera. student's amazing ongoing work (with very high modularity): efficient_online_learning for autonomous driving! 💥 This is a ROS-based online learning framework for human classification in 3D LiDAR scans, taking advantage of robust multi-target tracking to avoid the need for data annotation by a human expert. Aug 6, 2024 · The first model detects the presence of human bodies within an image frame, and the second model locates landmarks on the bodies. A. Next, combine the HOG feature with the LBP feature to form an augmented feature (HOG-LBP) to detect human. A OpenMMLAB toolbox for human pose estimation, skeleton-based action recognition, and action synthesis. The real-time human face detection and blurring was performed using the OpenCV module. Deserno}, title = {{Multi-camera, multi-person, and real-time fall detection using long short term memory}}, volume = {11601}, booktitle = {Medical Imaging 2021: Imaging Informatics for Healthcare, Research, and Applications}, organization = {International Society for This repository contains the code for Human Face Landmark Detection using Landmark Guided Face Parsing (LaPa) dataset. └── 3 DaisyKit is an easy AI toolkit with face mask detection, pose detection, background matting, barcode detection, face recognition and more. tsv: Each row corresponds to one argument Argument ID: The unique identifier for the argument Conclusion: Conclusion text of the argument Stance: Stance of the Premise towards the Conclusion; one of "in favor of", "against" Premise: Premise text of the argument labels-<split>. Real-time human detection and tracking camera using YOLOV5 This project implements a real time human detection via video or webcam detection using yolov3-tiny algorithm. Contribute to hiromaily/go-human-detection development by creating an account on GitHub. Implemented using PyTorch and Librosa. This is a ROS package developed for object detection in camera images. About. Social relations: Estimate spatial relations between people via coherent motion indicators. Contribute to cloor/Human-detection-ros development by creating an account on GitHub. This is still a work in progress and I am continuously updating. classes = [0], but if you want all classes in the model to be predicted and box plots drawn, you should change it to model. Binary classification problem that aims to classify human voices from audio recordings. ├── 2-elephant-detection-with-tensorflow-lite # This prototype has elephant detection only with TensorFlow Lite Model. It carefully examines each frame and looks for objects that exhibit little to no movement over a significant duration. The serialised files of test and training data are provided in the folder ‘pickled files’. To associate your repository with the human-pose-detection Human detection program for Inria Person Dataset. py to detect and display the human count. open-source beginner-project human-detection yolov8 yolov8n. The Motionless Object Detection Algorithm plays a crucial role in identifying stationary suspicious objects within the video. The focus of attention of a person can be approximately estimated finding the head orientation . And when user selects, the last option of detecting through camera, user need to open the Camera, using OPEN CAMERA button, As soon as camera opens, detection process will start. - with NCNN, OpenCV, Python wrappers python machine-learning mobile embedded computer-vision deep-learning deployment neural-network cpp vulkan face-detection object-detection barcode-detection no-code Multi-View Operating Room (MVOR) dataset consists of synchronized multi-view frames recorded by three RGB-D cameras in a hybrid OR during real clinical interventions. # Get the name of the class based on the class id from the output. Final Year college Face Detection Project with Project PPDM (PPDM: Parallel Point Detection and Matching for Real-Time Human-Object Interaction Detection) - Liao, Yue and Liu, Si and Wang, Fei and Chen, Yanjie and Qian, Chen and Feng, Jiashi ; PMN (Pose-based Modular Network for Human-Object Interaction Detection) - Liang, Zhijun and Liu, Junfa and Guan, Yisheng and Rojas, Juan More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. This is a Human Attributes Detection program with facial features extraction. Contribute to vibhorkrishna/S. The default is 65. Reload to refresh your session. Follow their code on GitHub. Apr 18, 2023 · Raspberry Pi Human Detection. The pickled machine learning model file and the test data file is required for the detection. Based on the human’s physical activity, the stress levels of the human being are detected and analyzed here. Contribute to rupy/HumanDetection development by creating an account on GitHub. Used Euclidean distance for accurate distance measurement, categorizing individuals into high, low, and no-risk groups for monitoring in public areas and workplaces. Contribute to idiap/human-detection development by creating an account on GitHub. classes = None. You only look once (YOLO) is a state-of-the-art, real-time object detection system. ) Enumeration Plot(Human Count Vs. We introduce a contrastive weakly supervised training loss that aims to jointly associate spatiotemporal regions in a video with an action and object vocabulary and encourage temporal continuity of the visual appearance of moving objects as a form of self Train with rotation augmented COCO person keypoints dataset for more robust person detection in a variant of angle pose. If you have any questions or suggestions, please do not hesistate to contact me. This repository implements a solution to the problem of tracking moving people in a low-quality video. This method has been proposed by N. Contribute to insung3511/human-detection development by creating an account on GitHub. py: The building blocks of human detection algorithm. Human action recognition is a well-studied problem in computer vision and on the other hand action quality assessment is researched and experimented comparatively low. " Learn more Footer 💥 Please check my Ph. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even This is a human detection mode that uses Intel RealSense D435 Camera and ROS Kinetic/Melodic. YOLO is a object detection algorithm which stand for You Only Look Once. fall-detection yolov7-pose YOLOv8 re-implementation for person detection using PyTorch Installation conda create -n YOLO python=3. We can split this project into two parts : Human: AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gaze Tracking, Gesture Recognition This includes a novel method to measure the quality of the actions performed in Olympic weightlifting using human action recognition in videos. Jul 14, 2020 · More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. There are pre-trained models that detect humans and/or human parts (face, upper,etc) but they are not applicable to these data (big number of false positives). A human violence detection & classification system using recurrent neural networks(RNN). - cam-n/human-detection-hog-svm Human: AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gaze Tracking, Gesture Recognition - vladmandic/human This Computer Vision algorithm based system is meant to make an approximate detection of the movement of human beings and counting the number of human within a particular sample of visual data using Deep Learning and OpenCV-python where the core library of HOG descriptor was written in C. Group tracking: Detection and tracking of groups of people based upon their social relations. This repository contains a Python script for person detection and tracking using the YOLOv3 object detection model and OpenCV. e. AVA , HOIs (human-object, human-human), and pose (body motion) actions Action Genome [Website] , action verbs and spatial relationships CAD120 [Paper] , [Website] 人体关键点检测Human Keypoints Detection. Stress Level Detection Using Physiological Parameters “Humidity – Temperature – Step count – Stress levels” represents the titles for Stress-Lysis. This project implements a Python program for Human Detection in an image using the YOLOv8 algorithm. Project Link - Human-Body Skeleton Detection using OpenCV. Aug 1, 2023 · In this tutorial, we have built a camera recorder application with human detection using Python and OpenCV. It first performs Haselich's clustering technique to detect human candidate clusters, and then applies Kidono's person classifier to eliminate false detections. It uses a state-of-the-art object detector YOLOv7 for detecting people in a frame, and fuses these robust detections with the bounding boxes of previously tracked people using the neural network version of SORT called DeepSORT tracker. This repository is the implementation of an automatic human hazard detection model based on a human posture. You signed out in another tab or window. Tech stack: Human detection More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. The development exercise deals with the design and development of a perception module for the new product line of Acme Robotics – warehouse management robots (WMR), for carrying the goods from one place to another in a workspace shared by humans. YOLOv8 re-implementation for person detection using PyTorch Installation conda create -n YOLO python=3. We provide camera calibration parameters, color and depth frames, human bounding boxes, and 2D/3D pose annotations. palm and hand detection & tracking for intelligent human In this section, we are going to demonstrate a walkthrough on building and deployment of a Real-time Human Detection and tracking system using Yolov5 model and Arduino UNO cards. Human Falling Detection. 25% accuracy in the RWF-2000 validation set with just 60k trainable parameters. # Initialize the Pi Camera and start capturing frames. py: Utlitiy functions used for serving the main functionality of the code. Aug 8, 2021 · More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. The HOG descriptor technique counts occurrences of gradient orientation in localized portions of an image - detection window, or region of interest (ROI). ipynb file. Pose landmarker model: adds a complete mapping of the Human detection & counting using OpenCV in Python is an exciting deep learning project in which OpenCV is used for standard image processing functions, along with the deep learning object detector elements (such as histogram of oriented gradients (HOG) + support vector machines (SVM) + Non-Maximum Suppression (NMS)) to analyze the number of people in a given area. ) More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. Because Coral devices run all the image analysis locally, the actual image is never streamed anywhere and is immediately discarded. The script processes a video stream or video file and detects and tracks people in real-time. Early research was biased toward human recognition rather than tracking. All important parts of the code are well documented with the comments and showcased on Github. 2 -c pytorch-lts pip install opencv-python==4. Human: AI-powered 3D Face Detection & Rotation Tracking Human Detection with an ESP32-cam AI Security Cam ESP32-cam(s) Initial plan was to connect a motion detector to an ESP32cam as a trigger to capture and send an image to a local MQTT broiker however given the amount of false-alarm a second ESP32-cam was repurposed to serve as a human detector which will send a signal to a WiFi connected ESP32 Human Stress Detection in and through Sleep by monitoring physiological data. A human violence detection & classification system using This project demonstrates the ability to detect and localize Human obstacles in 3 dimensional space utilizing a head mounted 3d Lidar. " _Robot and Human Interactive Communication (RO-MAN), 2016 25th IEEE International Symposiumon_ . In the following ROS package you are able to use YOLO (V3) on GPU and CPU. It specifically focuses on a project implementing Human Voice Pitch Detection techniques. D. Figure 2: Illustrative example of the results of the Human Detection program using YOLOv8. End users install an Ambianic Box to constantly monitor a fall risk area of the house. Version 2 - With Daisykit. YOLOV3 & Tensorflow object detection and report human movements in persian Yolov3 is an algorithm that uses deep convolutional neural networks to perform object detection. # Abnormal-Human-Activity-Detection With the increase in It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection. This project aims at weakly supervised human-object interaction detection in videos. Mar 20, 2024 · GitHub Gist: instantly share code, notes, and snippets. ├── 1-elephant-detection-with-alarm-and-email-alert # This prototype can detect elephants and send email alert. the Dior - Eau de Parfum commercial) by drawing bounding boxes around them on each frame. In this work, we present a novel joint head and human detection network, namely JointDet, which effectively detects head and human body simultaneously, aiming at handling issues that head detection is often trapped in more false positives and performance of human detector frequently drops dramatically in crowd scenes. faster-rcnn face-detection object-detection human-pose-estimation human-activity-recognition multi-object-tracking instance-segmentation mask-rcnn yolov3 deepsort fcos blazeface yolov5 detr pp-yolo fairmot yolox picodet human-motion-detection has 3 repositories available. After detection process gets completed or user manually completes it, two graph get plotted, 1. # Perform the object detection using the TFLite model. a GUI application, which uses YOLOv8 for Object Detection/Tracking, Human Pose Estimation/Tracking from images, videos or camera. The default is every 10th frame. Object Detection toolkit based on PaddlePaddle. Contribute to g4lb/camera-recorder-with-human-detection development by creating an account on GitHub. # Load the TFLite model and allocate the input and output tensors. I recently came across a paper ( Martinson, E. 64 pip install PyYAML pip install tqdm arguments-<split>. Y development by creating an account on GitHub. Step 2: Prepare a data set for Human Scream detection The whole data set of this project is divided into two classes one is a positive class which includes around 2000 human screams to train the model and another is a negative class which includes around 3000 negative sounds which are not considered as a scream. If not found, label as Unknown. The system consists of two parts first, human detection, and secondly tracking. Deepgaze is a library for human-computer interaction, people detection and tracking which uses Convolutional Neural Networks (CNNs) for face detection, head pose estimation and classification. Topics deep-learning keras rnn violence-detection yolov3 reccurent-neural-network More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. It is impossible to train a good detector for humans or human parts. [4] Yolo v4, v3 and v2 for Windows and Linux, github / yolov4-tiny 학습 코드는 여기걸 참고 [5] AVA Dataset Processing for Person Detection, github / Person detection용 학습데이터 얻는 방법 (이걸로 DB를 구축함). According to NCRB, 2. ; main. Repo for CVPR2021 paper "QPIC: Query-Based Pairwise Human-Object Interaction Detection with Image-Wide Contextual Information" - hitachi-rd-cv/qpic Smart Human Activity Detection Using YOLO. Whether you're currently taking the course or simply curious about applying DSP to analyze human voice signals, this project provides a valuable hands-on experience. Aug 9, 2021 · More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. The detected clusters are tracked by using Kalman filter with a contant velocity model. The backend server processes the images using YOLOv5 to detect humans and sends the result back to the client as a base64 encoded HTML file with server-side rendering. Human Detection is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. time) and; 2. Download Human Detection app source code on GitHub A camera recorder with human detection AI project. Problems: few images, occlusions. ; human_detector. The project propose a solution for remote monitoring and analysis, suitable an aerial vehicle - Suspicious activity detection through video analysis, primarily for human pose detection using visual features. For actions recognition used data from Le2i Fall detection Dataset (Coffee room, Home) extract skeleton-pose by AlphaPose and labeled each action frames by hand for training ST-GCN model. In this project, we developed a video analysis system that can detect events of human falling. csv file. connect_rainmaker demonstrates capturing CSI data and uploading it to Espressif's RainMaker cloud platform. C. Real-time human detection and tracking camera using YOLOV5 This paper presents a novel end-to-end framework with Explicit box Detection for multi-person Pose estimation, called ED-Pose, where it unifies the contextual learning between human-level (global) and keypoint-level (local) information. Contribute to sturkmen72/C4-Real-time-pedestrian-detection development by creating an account on GitHub. Our project is capable of detecting a human and its face in a given video and storing Local Binary Pattern Histogram (LBPH) features of the detected faces. 64 pip install PyYAML pip install tqdm Cascade Training, HOGs + SVM one of the basic techniques for human detection. The --continuous flag will examine the entire clip for human detections. 8 conda activate YOLO conda install pytorch torchvision torchaudio cudatoolkit=10. Contribute to ZhangHandi/human_detection_demo development by creating an account on GitHub. SharpAI yolov7_reid is an open source python application leverages AI technologies to detect intruder with traditional surveillance camera. This is due to the lack of datasets… Histogram of oriented gradients (HOG) is a feature descriptor used to detect objects in computer vision and image processing. Source code is here It leverages Yolov7 as person detector, FastReID for person feature extraction, Milvus the local vector database for self-supervised learning to identity unseen person, Labelstudio to host image locally and for further usage such as . OpenPose represents the first real-time multi-person system to jointly detect human body, hand, facial, and foot keypoints (in total 135 keypoints) on single images. On the other hand, we can say that there are unusual activities in t consecutive frames if a higher value exists in the minimum-distance matrix. People tracking: Efficient tracker based upon nearest-neighbor data association. You switched accounts on another tab or window. 5. Contribute to PanJinquan/Human-Keypoints-Detection development by creating an account on GitHub. Real-time human detection and tracking camera using YOLOV5 Human skin detection plays a key role in human-computer interactions. 3- Run the codes in the human-detection. This repository implements Yolov3 using TensorFlow You signed in with another tab or window. Collaborated with SNU HIS LAB. The pre-trained MobileNetv2 is used for the task in the TensorFlow framework. We’ve learned how to record video from the camera, detect humans using YOLO, and The camera module takes photos at a specified interval and sends the images to the backend server. [3] tensorflow-yolov4-tflite, github / 이걸 참고해서 Darknet 모델을 tensorflow lite 모델로 바꿈. palm and hand detection & tracking for intelligent human Multi-modal detection: Multiple RGB-D & 2D laser detectors in one common framework. Monitoring the movements of a human being raised the need for tracking. Advanced Deep Learning Algorithm for Human Detection Using YOLOv3 - DarkkSorkk/RealTime-HumanDetection-YOLOv3 Pretrained YOLO deep learning model to detect objects - mike98465/Human_Detection Welcome to the YOLOv8 Human Detection Beginner's Repository – your entry point into the exciting world of object detection! This repository is tailored for beginners, providing a straightforward implementation of YOLOv8 for human detection in images and videos. , and V. @inproceedings{Taufeeque2021MulticameraMA, author = {Mohammad Taufeeque and Samad Koita and Nicolai Spicher and Thomas M. Real-Time Human Detection Using Contour Cues. , we can control our system by showing our hands in front of webcam and More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. I've implemented the algorithm from scratch in Python using pre-trained weights. Dec 23, 2023 · To associate your repository with the human-scream-detection topic, visit your repo's landing page and select "manage topics. py: Sample code to test the functionality of the human detection algorithm on a given folder of raw radimetry data in . It takes in a Point Cloud data and outputs the X, Y and Z coordinate of the detected Human in the field. To associate your repository with the human-detection Create a Data set frome a video. 97 million cases of crime recorded in year 2018. Capture a video from any Enviroment where humans or non hymans. (a) Input Image (b) YOLOv8 Detection Results. The --confidence n flag will adjust the confidence threshold that trips a detection alert to n. The system receives video as input, scans each frame of the video, and then creates 17 key-points for each individual, each of which corresponds to a position of that person's body parts in that frame. Jan 8, 2018 · More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. In this python project, we are going to build the Human Detection and Counting System through Webcam or you can give your own video or images. The method is quite simple to devise and has been first experimented for human detection (that is, pedestrians on roads). The default behavior is to stop after first detection. deep-learning pytorch action-recognition graph-convolutional-network skeleton-based-action-recognition This repository provides the codes and data used in our paper "Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art", where we implement and evaluate several state-of-the-art approaches, ranging from handcrafted-based methods to convolutional neural networks. Testing your OpenCV installation Object detection in video with deep learning and OpenCV - Real-time deep learning object detection results Bibliography & sources Introduction In this guide we will walk through all the steps needed to set up our machine so we can then apply real-time object detection using deep learning and OpenCV to work with About. 233, 2023. txt files. This model is based on Dalal-Triggs algorithm, which automatically detects pedestrians in images, and can be used for detection in both images and video Official repository for HOTR: End-to-End Human-Object Interaction Detection with Transformers (CVPR'21, Oral Presentation) - kakaobrain/hotr human detection by Open CV3. Note that the script currently runs on CPU, so the frame rate may be limited compared to GPU-accelerated implementations. You signed in with another tab or window. The --frames n flag sets the program to examine every nth frame. H. Yalla. you can get picture frome video by crop the single human or non human only pic you can crop picture by matlab code This is the GitHub repository associated with the paper Human Skeletons and Change Detection for Efficient Violence Detection in Surveillance Videos, published in Computer Vision and Image Understanding (CVIU), vol. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection. Figure 1: Input/Output of Object Detection task with the desired objects being Dog and Cat. This is a deep learning project on computer vision, which will help you to master the concepts and make you an expert in the field of Data Science. Detect and count Human in Video for Covid-19. g. showRT - human detection with visualization and tracking annotateData - annotate the human for training and save the result to csv file trainLaser – train the annotation with given csv file and save the result to boost. Dalal and B. tgrsr rslucf zybbpx ixwhhh yxarj rtwum vzvcwjf nsqdko nmni secv