Yolov8 export openvino. The final step is exporting the trained model to OpenVINO™ IR to accelerate model inference on any Intel™ device. In addition, we provide the FP32 and INT8 model accuracy calculation methods, introduce OpenVINO Benchmark App for performance Train with YOLOv8 and export to OpenVINO™ IR YOLOv8 is a well-known model training framework for object detection and tracking, instance segmentation, image classification, and pose estimation tasks. ) Multiple format and platform support Easily export trained models to most common formats (ONNX, OpenVINO, CoreML, etc. Export. We need to specify --include openvino parameter for exporting. 最初に、この記事で紹介しているサンプルコードのリポジトリーを Nov 12, 2023 · Python CLI. This command is using the pip package Nov 12, 2023 · 探索Ultralytics 的导出功能。了解导出格式、IOSDetectModel 并通过示例尝试导出。 Nov 12, 2023 · ベンチマーク結果は、YOLOv8 モデルをOpenVINO 形式にエクスポートすることの利点を明確に示している。 様々なモデルやハードウェアプラットフォームにおいて、OpenVINO フォーマットは、同等の精度を維持しながら、推論速度の点で一貫して他のフォーマット Nov 12, 2023 · ultralytics. Our ultralytics_yolov8 fork contains implementations that allow users to train image regression models. An example use case is estimating the age of a person. As for discrepancy i have mentioned the versions of nncf, openvino also i created a new virtualenv where onnx, openvino packages were installed using Autoupdate ( requirements: Ultralytics requirement ['openvino-dev>=2023. export(format='onnx') YOLOv8 可用的导出格式如下表所示。. - Download and prepare a dataset. Transform images into actionable insights and bring your AI visions to life with ease using our cutting-edge platform and user-friendly Ultralytics App. 196 onnx==1. YOLOv8である。. 27 🚀 Python-3. 0 openvino-dev==2023. 管理员身份打开vipm. pt and a different dataset but the output shape after Openvino optimisation remains the same. tools import mo from openvino. This example demonstrates how to deploy the Yolov8 full series model using the OpenVINO™ C# API 3. The locations of the keypoints are usually represented as a set of 2D [x, y] or 3D [x, y, visible May 30, 2023 · Introduction. YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object Mar 10, 2023 · In order to move a YOLO model to GPU you must use the pytorch . export () function allows for converting your trained model into a variety of formats tailored to diverse environments and performance requirements. YOLOv8 models can be loaded from a trained checkpoint or created from scratch. As the result, directory with name yolov5m_openvino_model will be created with following content: Jan 10, 2023 · YOLOv8 is the latest family of YOLO based Object Detection models from Ultralytics providing state-of-the-art performance. The tutorial consists of the following steps: - Prepare the PyTorch model. The TensorFlow Lite or TFLite export format allows you to optimize your Ultralytics YOLOv8 models for tasks like object detection and image classification in edge Label and export your custom datasets directly to YOLOv8 for training with Roboflow Automatically track, visualize and even remotely train YOLOv8 using ClearML (open-source!) Free forever, Comet lets you save YOLOv8 models, resume training, and interactively visualize and debug predictions #Pytorch模型转换为Onnx模型 python from ultralytics import YOLO model = YOLO('yolov8s. Nota. Open yolov8n. It provides simple CLI commands to YOLOv8 classification/object detection/Instance segmentation/Pose model OpenVINO inference sample code - openvino-book/yolov8_openvino Aug 5, 2023 · Explanation of the above two commands. Some common YOLO export settings include the format of the exported model file (e Label and export your custom datasets directly to YOLOv8 for training with Roboflow Automatically track, visualize and even remotely train YOLOv8 using ClearML (open-source!) Free forever, Comet lets you save YOLOv8 models, resume training, and interactively visualize and debug predictions Feb 22, 2022 · YOLOv5 v6. Experience seamless AI with Ultralytics HUB ⭐, the all-in-one solution for data visualization, YOLOv5 and YOLOv8 🚀 model training and deployment, without any coding. Exporting YOLOv8 models to TorchScript is crucial for moving from research to real-world applications. まだ詳細な技術情報は公開されていないが、GitHubにはPythonプロジェクトが登録されている。. YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and 三、OpenVINO工具包的安装. export(format="openvino", dynamic=False, half=True) det_model represents the YOLOv8 object detection model. 0' 'nncf>=2. 2 openvino==2023. The ideal format depends on your model's intended operational context, balancing speed, hardware constraints, and ease of This notebook is open with private outputs. 您可以直接对导出的模型进行预测或验证,即 yolo predict model Aug 2, 2023 · Welcome to the fourth video in our new series! Join Nicolai Nielsen as he shows you how to export your custom-trained Ultralytics YOLOv8 model and run live i Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost performance and flexibility. It streamlines AI development and integration of deep learning in domains like 该解决方案分为 4 个简单步骤:. pt format=openvino After convert, you will get yolov8n. 4. 5. Nov 12, 2023 · Once your model is trained and validated, the next logical step is to evaluate its performance in various real-world scenarios. YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and Mar 1, 2024 · A Guide on YOLOv8 Model Export to TFLite for Deployment Deploying computer vision models on edge devices or embedded devices requires a format that can ensure seamless performance. この記事では、YOLOv8 物体検出モデルの高速化に注目します。. 为获得良好的模型推理加速,并更方便的部署在不同的硬件平台上,接下来我们首先将YOLO v8模型转换为OpenVINO IR模型格式。YOLOv8提供了用于将模型导出到不同格式(包括OpenVINO IR格式)的API。model. Steps to convert from PyTorch yolov8 model into OpenVINO. Important Note:--input_shape must be provided and match the img shape used to export ONNX model. See Docker Quickstart Guide. py scripts support multiple model formats for conversion. Export settings for YOLO models refer to the various configurations and options used to save or export the model for use in other environments or platforms. onnx and best_dynamic_bs. 4 please check this notebook. The export to TFLite Edge TPU format feature allows you to optimize your Ultralytics YOLOv8 models for high-speed and low-power inferencing. 本综合指南旨在指导您了解模型导出的细微差别,展示如何实现最大的兼容性和性能 May 3, 2023 · Train YOLOv8 model and export it to OpenVINO™ model. In this post we will walk through the process of deploying a YOLOv8 model ( ONNX format) to an Amazon SageMaker endpoint for serving inference requests, leveraging OpenVino as the ONNX execution provider. import numpy as np. Nov 12, 2023 · YOLOv8 Os testes de referência abaixo foram executados pela equipa Ultralytics em 4 formatos de modelos diferentes, medindo a velocidade e a precisão: PyTorch, TorchScript, ONNX e OpenVINO. 0 onnxruntime==1. pip install -r requirements. OpenVINO™ toolkit is an open source toolkit that accelerates AI inference with lower latency and higher throughput while maintaining accuracy, reducing model footprint, and optimizing hardware use. The following notebook snippet demonstrates how to convert the model using the export method: # export model to OpenVINO format out_dir = det_model. Nov 12, 2023 · You can simply run all tasks from the terminal with the yolo command. YOLOv8 是 Ultralytics 公司基于 YOLO 框架,发布的一款面向物体检测与跟踪、实例分割、图像分类和姿态估计任务的 SOTA 模型工具套件。. 15. What a thrilling time it was at YOLO Vision 2023 (YV23), where groundbreaking ideas merged seamlessly with cutting-edge technology! One of the keynotes saw Software Evangelist at Intel, Adrian Boguszewski, take the stage to share his insights on revolutionizing queue management using Ultralytics YOLOv8 and Intel's OpenVINO. Watch: Ultralytics Modes Tutorial: Benchmark. NNCF provides samples that demonstrate the usage of compression Search before asking I have searched the YOLOv8 issues and found no similar bug report. Jul 21, 2023 · Writing YOLOv8 Object Detection Model Inference Program with OpenVINO™ Python API Open yolov8n. runtime import Core. YOLOv8 Component Export Bug terminal output Ultralytics YOLOv8. Nov 12, 2023 · 导言. Nov 12, 2023 · TFLite,ONNX,CoreML,TensorRT Export TFLite,ONNX,CoreML,TensorRT Export 目录 开始之前 格式 基准 Colab Pro V100 GPU Colab Pro CPU 导出训练有素的YOLOv5 模型 导出模型使用示例 OpenCV DNN 推断 C++ 推断 TensorFlow. You switched accounts on another tab or window. またもや新たなYOLOが登場した。. import matplotlib. bin (12. I have searched the YOLOv8 issues and found no similar bug report. We will start by setting up an Amazon SageMaker Studio domain and user profile, followed by a step-by-step notebook walkthrough. You can disable this in Notebook settings. Watch: Mastering Ultralytics YOLOv8: CLI. The keypoints can represent various parts of the object such as joints, landmarks, or other distinctive features. 0 API interface with multiple references to OpenVino ™ C++API implementation, therefore it is closer to the C++API when used, which will be more friendly to friends who are familiar with using the C++API. Here you see that the output has an output0 name, it also has a form of tensor of float numbers and a shape of this output is [1,84,8400] which means that this is a single 84x8400 matrix, that nested to a single array. AIxBoard で OpenVINO™ ツールキットを使用して YOLOv8 分類モデルのデプロイメントと評価を行ってみましょう。. 0'] not found, attempting AutoUpdate Mar 1, 2024 · Developed by the creators of PyTorch, TorchScript is a powerful tool for optimizing and deploying PyTorch models across a variety of platforms. pt (6. convert_model(model_path) #fp32_parh为vino Nov 20, 2023 · Here are the python libraries I am using: ultralytics==8. 0 API. from ultralytics import YOLO. We will use the YOLOv8 nano model (also known as yolov8n) pre-trained on a COCO dataset, which is available in this repo. I’ll explain these commands in a straightforward manner: !pip install -q 'openvino-dev>=2023. 1 - TensorRT, TensorFlow Edge TPU and OpenVINO Export and Inference This release incorporates many new features and bug fixes (271 PRs from 48 contributors) since our last release in October 2021. engine. 1. This is what happens when I export as the onnx format: Now this is what happens when I export as the engine format: Feb 7, 2024 · Feb 7, 2024. pt') # load a custom trained model # Export the model model. 9. Reload to refresh your session. Learn about exporting formats, IOSDetectModel, and try exporting with examples. You signed out in another tab or window. Jun 23, 2023 · Amazon Deep Learning AMI. Module class, initialized by a state dictionary with model weights. Syntax Train Predict Val Export Special. In inverse chronological order: Label and export your custom datasets directly to YOLOv8 for training with Roboflow Automatically track, visualize and even remotely train YOLOv8 using ClearML (open-source!) Free forever, Comet lets you save YOLOv8 models, resume training, and interactively visualize and debug predictions Dec 16, 2023 · 04 Writing YOLOv8 Object Detection Model Inference Program with OpenVINO™ Python API. Leveraging the previous YOLO versions, the YOLOv8 model is faster and more accurate while providing a unified framework for training models for performing. - Validate the original model. Use Forward Slashes: Alternatively, you can May 3, 2023 · 导出训练好的YOLOv8模型,并用OpenVINO部署在英特尔硬件平台上,也非常方便,下面依次介绍: 第一步 :准备YOLOv8的OpenVINO推理程序开发环境。 请基于本文范例代码仓提供的requirements. onnx. How i can get my 4 detected keypoints with bbox. 然后使用命令:. onnx using Netron, as shown in the figure below. This information can help users choose Feb 8, 2023 · 第二步: 将模型转换为OpenVINO IR格式. You signed in with another tab or window. Formats. Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost performance and flexibility. py and PyTorch Hub YOLOv8 DeGirum Regression Task. - Prepare and run optimization pipeline. Prepare dataset; Convert dataset with Datumaro; Train with YOLOv8 and export to OpenVINO™ IR YOLOv8 is a well-known model training framework for object detection and tracking, instance segmentation, image classification, and pose estimation tasks. Convert YOLOv8n. Nov 5, 2023 · Search before asking. e @try_export. pt") model. vip 】开始安装,安装过程会自动安装OpenVINO驱动包;. txt文件,通过一行命令完成开发环境安装。 Jan 14, 2023 · 暇つぶしに、興味を引いた DNNアプリを *Interpに移植して遊んでいる。. " GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. We will use the YOLOv7 tiny model pre-trained on a COCO dataset, which is available in this repo. 2. - Validate the converted model. NNCF is designed to work with models from PyTorch, TensorFlow, ONNX and OpenVINO™. yolo export Nov 12, 2023 · The benchmarks provide information on the size of the exported format, its mAP50-95 metrics (for object detection, segmentation and pose) or accuracy_top5 metrics (for classification), and the inference time in milliseconds per image across various export formats like ONNX, OpenVINO, TensorRT and others. In this guide, we'll walk you through converting your 导出 YOLOv8-Seg OpenVINO™ IR 模型. setup. 双击并运行【 virobotics_lib_openvino-1. from ultralytics import YOLO # Load a model model = YOLO('yolov8n. - Compare performance of the FP32 and quantized models. 训练模型的最终目的是将其部署到实际应用中。. Model Input: 1280x1280x3. The user can train models with a Regress head or a Regress6 head; the first Jun 15, 2023 · Neural Network Compression Framework (NNCF) (which you mentioned that you are doing it now) I converted the yolov8-pose model with 4 keypoints into openvino int8 format using this. In this guide, we'll walk you through how to convert your models to the NCNN format, making it easier for your models to perform well on various mobile and embedded devices. - Convert the PyTorch model to OpenVINO IR. OpenVINO is also represented among supported formats. ) an run them on various platforms, from CPUs to GPUsrting Yolov8 + DeepSort for Object Detection and Tracking; mikel-brostrom's ultralytic, which is used in ref work 3; How to list available cameras OpenCV/Python; How to wget files from Google Drive; I recommend to use ultralytics==8. It provides simple CLI commands to train, test, and export a model to OpenVINO™ Intermediate Representation (IR). ; YOLOv8 Component. Generally, PyTorch models represent an instance of the torch. It adds TensorRT, Edge TPU and OpenVINO support, and provides retrained models at --batch-size 128 with new default one-cycle linear LR scheduler. Where TASK ( optional) is one of [ detect, segment, classify] MODE ( required) is one of [ train, val, predict Label and export your custom datasets directly to YOLOv8 for training with Roboflow Automatically track, visualize and even remotely train YOLOv8 using ClearML (open-source!) Free forever, Comet lets you save YOLOv8 models, resume training, and interactively visualize and debug predictions Nov 12, 2023 · Pose estimation is a task that involves identifying the location of specific points in an image, usually referred to as keypoints. YOLOv5 now officially supports 11 different formats, not just for export but for inference (both detect. May 6, 2022 · Note: This article was created with OpenVINO 2022. 0'. txt. Sep 20, 2022 · In this article, we will introduce how to use OpenVINO TM 2022. TorchScript, part of the PyTorch framework, helps make this transition smoother by allowing PyTorch Label and export your custom datasets directly to YOLOv8 for training with Roboflow Automatically track, visualize and even remotely train YOLOv8 using ClearML (open-source!) Free forever, Comet lets you save YOLOv8 models, resume training, and interactively visualize and debug predictions Making Generative AI More Accessible for Real-World Scenarios . exe设置为管理员启动,如下图(安装完成后请记得改回). 1. 视频捕捉: 利用标准视频流或实时馈送采集实时数据。. Example. pyplot as plt. 3. 部署: 从单板计算机到企业硬件,使用OpenVINO Ultralytics HUB. pt into OpenVINO xml model via command: yolo export model=yolov8n. Install python, and install ultralytics: pip install ultralytics. pt') # load an official model model = YOLO('path/to/best. js 网络浏览器推理 支持的环境 项目现状 Feb 17, 2023 · YoloV5 export. I have tried varying the export parameters and the image adjustments for feeding into the Openvino Runtime but I seem to always get the same result, it could also be in how I am processing the output. . YOLOv8 was reimagined using Python-first principles for the most seamless Python YOLO experience yet. nn. py. Ultralytics yolo commands use the following syntax: yolo TASK MODE ARGS. The YOLOv8 Regress model yields an output for a regressed value for an image. Batching might not supported for CPU Get Pytorch model¶. See AWS Quickstart Guide. This way, backslashes won’t be treated as escape characters. 等待几秒钟会出现如下界面,点击 Install Jun 15, 2023 · the input format expected by YOLOv8 for OpenVINO is in the format (3, H, W), where 3 denotes the three color channels (RGB) and H, W represent the height and width of the image, respectively. 本稿はその雑記&記録。. 1 Post-training Optimization Tool (POT) API for YOLOv5 Model INT8 quantization, to achieve model compression and inference performance improvement. See detailed Python usage examples in the YOLOv8 Python Docs. Train with YOLOv8 and export to OpenVINO™ IR YOLOv8 is a well-known model training framework for object detection and tracking, instance segmentation, image classification, and pose estimation tasks. Downloaded from ultralytics official website, specifically, it's YOLOv8n. 23MB). Nov 12, 2023 · For TensorRT export example (requires GPU) see our Colab notebook appendix section. The model give me the output (1, 17, 33600). Docker Image. Benchmark mode in Ultralytics YOLOv8 serves this purpose by providing a robust framework for assessing the speed and accuracy of your model across a range of export formats. Use Raw String Literal: Use a raw string literal by prefixing the file path with r. Label and export your custom datasets directly to YOLOv8 for training with Roboflow Automatically track, visualize and even remotely train YOLOv8 using ClearML (open-source!) Free forever, Comet lets you save YOLOv8 models, resume training, and interactively visualize and debug predictions Sep 7, 2023 · はじめに】. One way to achieve this is by using NumPy to stack the input into Label and export your custom datasets directly to YOLOv8 for training with Roboflow Automatically track, visualize and even remotely train YOLOv8 using ClearML (open-source!) Free forever, Comet lets you save YOLOv8 models, resume training, and interactively visualize and debug predictions Yolov8 training (link to external repository) Deep appearance descriptor training (link to external repository) ReID model export to ONNX, OpenVINO, TensorRT and TorchScript Evaluation on custom tracking dataset ReID inference acceleration with Nebullvm Experiments. 安装 ultralytics 和 openvino-dev 。. Although PyTorch is a great framework for AI training Sep 25, 2023 · @glenn-jocher the ONNX model file exists on the specified paths, there are two files best. 计数和警报: 对指定区域的客户进行计数,并在队列超过容量时触发警报。. YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost performance and flexibility. YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and setup. See docs here. See CPU Benchmarks. try_export(inner_func) YOLOv8 export decorator, i. To associate your repository with the yolov8 topic, visit your repo's landing page and select "manage topics. xml (227KB) and yolov8n. The input shape of the model is [1,3,640,640], and the output shape is [1,84,8400]. Start Label and export your custom datasets directly to YOLOv8 for training with Roboflow Automatically track, visualize and even remotely train YOLOv8 using ClearML (open-source!) Free forever, Comet lets you save YOLOv8 models, resume training, and interactively visualize and debug predictions Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost performance and flexibility. Export the trained model to OpenVINO™ IR# So far, we have been able to successfully train our YOLOv8 model by converting the dataset format using Datumaro and passing it to the Ultralytics YOLOv8 trainer CLI. The input shape of the model is [1,3,640,640], and Label and export your custom datasets directly to YOLOv8 for training with Roboflow Automatically track, visualize and even remotely train YOLOv8 using ClearML (open-source!) Free forever, Comet lets you save YOLOv8 models, resume training, and interactively visualize and debug predictions You signed in with another tab or window. from openvino. pt') result = model. 5,device='xyz') Share. OpenVINO™ C# API 3. Get PyTorch model¶. Os testes de referência foram efectuados em GPUs Intel Flex e Arc, e em CPUs Intel Xeon com precisão FP32 (com o half=False argumento). Explore the exporter functionality of Ultralytics. input shape : [1,3,640,640] output shape: [1,6,8400] import cv2. Improve this answer. Bạn có thể xuất sang bất kỳ định dạng nào bằng cách sử dụng format lập luận, tức là format='onnx' hoặc format='engine'. Question looking to migrate the Yolo nano model to any of these three, is it possible? pls let us know if there is some solution Addit Nov 12, 2023 · As outlined in the Ultralytics YOLOv8 Modes documentation, the model. You can also explicitly run a prediction and specify the device. Then methods are used to train, val, predict, and export the model. Hướng dẫn từng bước về xuất của bạn YOLOv8 Các mô hình sang định dạng khác nhau như ONNX . 💡 ProTip: Export to TensorRT for up to 5x GPU speedup. Outputs will not be saved. YOLOv5 now officially supports 11 Label and export your custom datasets directly to YOLOv8 for training with Roboflow Automatically track, visualize and even remotely train YOLOv8 using ClearML (open-source!) Free forever, Comet lets you save YOLOv8 models, resume training, and interactively visualize and debug predictions Nov 12, 2023 · Có sẵn YOLOv8 Định dạng xuất có trong bảng dưới đây. to syntax like so: model = YOLO("yolov8n. May 13, 2023 · YOLOv8 has a single output, which is a first item of the outputs object. to('cuda') some useful docs here. Aug 9, 2023 · 1. model. 首先用命令 :. If you want to know how to use the old API of OpenVINO 2021. pt format=openvino. 2. YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and Mar 1, 2023 · I tried using yolov8s. To achieve this format, the input needs to be permuted before passing it into the model. 7 torch-2. 146 to train your YOLOv8 model for this repo, since ref work [3] and [4] are modified based this version Mar 13, 2024 · The TensorFlow Lite Edge TPU or TFLite Edge TPU model format is designed to use minimal power while delivering fast performance for neural networks. Object Detection, Instance Segmentation, and; Image Classification. I cant understand this output. Ultralytics YOLOv8 中的导出模式为将训练好的模型导出为不同格式提供了多种选择,使其可以在各种平台和设备上部署。. 16. Bug. 客户 检测: 利用YOLOv8 进行准确高效的客户检测。. 11. These settings can affect the model's performance, size, and compatibility with different systems. 1MB) in yolov8n_openvino_model folder. YOLOv5 inference is officially supported in 11 formats: 💡 ProTip: Export to ONNX or OpenVINO for up to 3x CPU speedup. Are you ready to take your object detection models to the next level? In this tutorial, we'll walk you through the process of converting, exporting, and opti YOLOv8 supports all YOLO versions, even those of competitors (Google MobileNet etc. それを Elixirで動かし This will create the OpenVINO Intermediate Model Representation (IR) model files (xml and bin) in the directory models/yolov5_openvino which will be available in the host system outside the docker container. 安装前请将labview. This This prepares the model for use with the OpenVINO toolkit. predict(source, save=True, imgsz=320, conf=0. exporter. 1+cu121 CPU (12th Gen Intel Core (TM) i7-12650H) rt-detr Mar 1, 2024 · The export to NCNN format feature allows you to optimize your Ultralytics YOLOv8 models for lightweight device-based applications. YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and This release incorporates new features and bug fixes (271 PRs from 48 contributors) since our last release in October 2021. Search before asking I have searched the YOLOv8 issues and discussions and found no similar questions. 0. runtime import serialize #model_path为onnx模型路径 model = mo. export负责模型转换。 YOLOv8 モデルをOpenVINO™用に最適化することで、Ultralytics 、ユーザーがビデオ分析、スマートシティ、次世代リテールなどのアプリケーションを開発している場合でも、より高速なだけでなく、より効率的なAI推論を楽しむことができます。 Neural Network Compression Framework (NNCF) provides a suite of post-training and training-time algorithms for neural networks inference optimization in OpenVINO™ with minimal accuracy drop. export(format='onnx') #yolov8原生转换 #onnx模型转vino模型(xml) from openvino. xk ry zn cm qy pq sf nx az yu