diff --git a/docs/README.md b/docs/README.md index 9b6df25..df1e554 100644 --- a/docs/README.md +++ b/docs/README.md @@ -1,6 +1,6 @@ --- -description: Learn how to install the Ultralytics package in developer mode and build/serve locally using MkDocs. Deploy your project to your host easily. -keywords: install Ultralytics package, deploy documentation, building locally, deploy site, GitHub Pages, GitLab Pages, Amazon S3, MkDocs documentation +description: Learn how to install Ultralytics in developer mode, build and serve it locally for testing, and deploy your documentation site on platforms like GitHub Pages, GitLab Pages, and Amazon S3. +keywords: Ultralytics, documentation, mkdocs, installation, developer mode, building, deployment, local server, GitHub Pages, GitLab Pages, Amazon S3 --- # Ultralytics Docs diff --git a/docs/SECURITY.md b/docs/SECURITY.md index a32fb4f..1126b84 100644 --- a/docs/SECURITY.md +++ b/docs/SECURITY.md @@ -1,6 +1,6 @@ --- -description: Ensure robust security with Ultralytics' open-source projects. We use advanced vulnerability scans and actively address potential risks. Your safety is our priority. -keywords: Ultralytics, security policy, Snyk, CodeQL scanning, security vulnerability, security issues, report security issue +description: Discover how Ultralytics ensures the safety of user data and systems. Check out the measures we have implemented, including Snyk and GitHub CodeQL Scanning. +keywords: Ultralytics, Security Policy, data security, open-source projects, Snyk scanning, CodeQL scanning, vulnerability detection, threat prevention --- # Security Policy diff --git a/docs/datasets/classify/caltech101.md b/docs/datasets/classify/caltech101.md index 82335ee..b6aa130 100644 --- a/docs/datasets/classify/caltech101.md +++ b/docs/datasets/classify/caltech101.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the Caltech-101 dataset, a collection of images for object recognition tasks in machine learning and computer vision algorithms. -keywords: Caltech-101 Dataset, Object recognition tasks, Ultralytics YOLO Docs, training, testing, code snippets & examples, machine learning, computer vision +description: Learn about the Caltech-101 dataset, its structure and uses in machine learning. Includes instructions to train a YOLO model using this dataset. +keywords: Caltech-101, dataset, YOLO training, machine learning, object recognition, ultralytics --- # Caltech-101 Dataset diff --git a/docs/datasets/classify/caltech256.md b/docs/datasets/classify/caltech256.md index 6f70f06..593831b 100644 --- a/docs/datasets/classify/caltech256.md +++ b/docs/datasets/classify/caltech256.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the Caltech-256 dataset, a broad collection of images used for object classification tasks in machine learning and computer vision algorithms. -keywords: Caltech-256, Dataset, Object Recognition, Image Classification, Convolutional Neural Networks, SVMs, YOLO, Deep Learning Models +description: Explore the Caltech-256 dataset, a diverse collection of images used for object recognition tasks in machine learning. Learn to train a YOLO model on the dataset. +keywords: Ultralytics, YOLO, Caltech-256, dataset, object recognition, machine learning, computer vision, deep learning --- # Caltech-256 Dataset diff --git a/docs/datasets/classify/cifar10.md b/docs/datasets/classify/cifar10.md index adfdb46..a7ecfd1 100644 --- a/docs/datasets/classify/cifar10.md +++ b/docs/datasets/classify/cifar10.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the CIFAR-10 dataset, a collection of images that are commonly used to train machine learning and computer vision algorithms. -keywords: CIFAR-10 dataset, YOLO model training, image classification, deep learning, computer vision, object detection, machine learning, convolutional neural networks, Alex Krizhevsky +description: Explore the CIFAR-10 dataset, widely used for training in machine learning and computer vision, and learn how to use it with Ultralytics YOLO. +keywords: CIFAR-10, dataset, machine learning, image classification, computer vision, YOLO, Ultralytics, training, testing, deep learning, Convolutional Neural Networks, Support Vector Machines --- # CIFAR-10 Dataset diff --git a/docs/datasets/classify/cifar100.md b/docs/datasets/classify/cifar100.md index d20abe9..50ebe28 100644 --- a/docs/datasets/classify/cifar100.md +++ b/docs/datasets/classify/cifar100.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the CIFAR-100 dataset, a collection of images that are commonly used to train machine learning and computer vision algorithms. -keywords: CIFAR-100 dataset, CIFAR-100 classes, CIFAR-100 structure, CIFAR-100 applications, CIFAR-100 usage, YOLO model training, machine learning, computer vision +description: Discover how to leverage the CIFAR-100 dataset for machine learning and computer vision tasks with YOLO. Gain insights on its structure, use, and utilization for model training. +keywords: Ultralytics, YOLO, CIFAR-100 dataset, image classification, machine learning, computer vision, YOLO model training --- # CIFAR-100 Dataset diff --git a/docs/datasets/classify/fashion-mnist.md b/docs/datasets/classify/fashion-mnist.md index c05d5f5..f1e6f7f 100644 --- a/docs/datasets/classify/fashion-mnist.md +++ b/docs/datasets/classify/fashion-mnist.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the Fashion-MNIST dataset, a large database of Zalando's article images used for training various image processing systems and machine learning models. -keywords: Fashion-MNIST, dataset, machine learning, image classification, convolutional neural networks, benchmarking, Zalando's article images +description: Learn how to use the Fashion-MNIST dataset for image classification with the Ultralytics YOLO model. Covers dataset structure, labels, applications, and usage. +keywords: Ultralytics, YOLO, Fashion-MNIST, dataset, image classification, machine learning, deep learning, neural networks, training, testing --- # Fashion-MNIST Dataset diff --git a/docs/datasets/classify/imagenet.md b/docs/datasets/classify/imagenet.md index ca4deec..9ac8d15 100644 --- a/docs/datasets/classify/imagenet.md +++ b/docs/datasets/classify/imagenet.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the ImageNet dataset, a large-scale database of annotated images commonly used for training deep learning models in computer vision tasks. -keywords: ImageNet, dataset, deep learning, computer vision, YOLO models, training, object recognition, image classification, object detection, WordNet, synsets, ILSVRC +description: Understand how to use ImageNet, an extensive annotated image dataset for object recognition research, with Ultralytics YOLO models. Learn about its structure, usage, and significance in computer vision. +keywords: Ultralytics, YOLO, ImageNet, dataset, object recognition, deep learning, computer vision, machine learning, dataset training, model training, image classification, object detection --- # ImageNet Dataset diff --git a/docs/datasets/classify/imagenet10.md b/docs/datasets/classify/imagenet10.md index 069515c..806ef2a 100644 --- a/docs/datasets/classify/imagenet10.md +++ b/docs/datasets/classify/imagenet10.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the ImageNet10 dataset, a compact subset of the original ImageNet dataset designed for quick testing, CI tests, and sanity checks. -keywords: ImageNet10 dataset, ImageNet, small scale, subset, computer vision models, pipelines, testing, debugging, synsets, annotations, applications, structure, sample images, citations, acknowledgments, Ultralytics Docs +description: Explore the compact ImageNet10 Dataset developed by Ultralytics. Ideal for fast testing of computer vision training pipelines and CV model sanity checks. +keywords: Ultralytics, YOLO, ImageNet10 Dataset, Image detection, Deep Learning, ImageNet, AI model testing, Computer vision, Machine learning --- # ImageNet10 Dataset diff --git a/docs/datasets/classify/imagenette.md b/docs/datasets/classify/imagenette.md index 371beee..9790904 100644 --- a/docs/datasets/classify/imagenette.md +++ b/docs/datasets/classify/imagenette.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the ImageNette dataset, a subset of 10 easily classified classes from the Imagenet dataset commonly used for training various image processing systems and machine learning models. -keywords: ImageNette Dataset, ImageNette, training set, validation set, image classification, convolutional neural networks, machine learning, computer vision, ultralytics, yolov8n-cls.pt, python +description: Learn about the ImageNette dataset and its usage in deep learning model training. Find code snippets for model training and explore ImageNette datatypes. +keywords: ImageNette dataset, Ultralytics, YOLO, Image classification, Machine Learning, Deep learning, Training code snippets, CNN, ImageNette160, ImageNette320 --- # ImageNette Dataset diff --git a/docs/datasets/classify/imagewoof.md b/docs/datasets/classify/imagewoof.md index 17c346f..ba046a7 100644 --- a/docs/datasets/classify/imagewoof.md +++ b/docs/datasets/classify/imagewoof.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the ImageWoof dataset, a subset of the ImageNet consisting of 10 challenging-to-classify dog breed classes. -keywords: ImageWoof dataset, dog breed images, image classification, noisy labels, deep learning models, CNN training, fastai +description: Explore the ImageWoof dataset, designed for challenging dog breed classification. Train AI models with Ultralytics YOLO using this dataset. +keywords: ImageWoof, image classification, dog breeds, machine learning, deep learning, Ultralytics, YOLO, dataset --- # ImageWoof Dataset diff --git a/docs/datasets/classify/index.md b/docs/datasets/classify/index.md index ab6ca5c..1b4e497 100644 --- a/docs/datasets/classify/index.md +++ b/docs/datasets/classify/index.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn how torchvision organizes classification image datasets. Use this code to create and train models. CLI and Python code shown. -keywords: image classification, datasets, format, torchvision, YOLO, Ultralytics +description: Explore image classification datasets supported by Ultralytics, learn the standard dataset format, and set up your own dataset for training models. +keywords: Ultralytics, image classification, dataset, machine learning, CIFAR-10, ImageNet, MNIST, torchvision --- # Image Classification Datasets Overview diff --git a/docs/datasets/classify/mnist.md b/docs/datasets/classify/mnist.md index 054173c..3b439f7 100644 --- a/docs/datasets/classify/mnist.md +++ b/docs/datasets/classify/mnist.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the MNIST dataset, a large database of handwritten digits commonly used for training various image processing systems and machine learning models. -keywords: MNIST, EMNIST, dataset, handwritten digits, convolutional neural networks, support vector machines, machine learning, computer vision, image processing, benchmark data, Ultralytics +description: Detailed guide on the MNIST Dataset, a benchmark in the machine learning community for image classification tasks. Learn about its structure, usage and application. +keywords: MNIST dataset, Ultralytics, image classification, machine learning, computer vision, deep learning, AI, dataset guide --- # MNIST Dataset diff --git a/docs/datasets/detect/argoverse.md b/docs/datasets/detect/argoverse.md index 139c920..a0ab7c9 100644 --- a/docs/datasets/detect/argoverse.md +++ b/docs/datasets/detect/argoverse.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the Argoverse dataset, a rich dataset designed to support research in autonomous driving tasks such as 3D tracking, motion forecasting, and stereo depth estimation. -keywords: Argoverse Dataset, Sensor Dataset, Autonomous Driving Research, Deep Learning Models, YOLOv8n Model, 3D Tracking, Motion Forecasting, Stereo Depth Estimation, Labeled 3D Object Tracks, High-Quality Sensor Data, Richly Annotated HD Maps +description: Explore Argoverse, a comprehensive dataset for autonomous driving tasks including 3D tracking, motion forecasting and depth estimation used in YOLO. +keywords: Argoverse dataset, autonomous driving, YOLO, 3D tracking, motion forecasting, LiDAR data, HD maps, ultralytics documentation --- # Argoverse Dataset diff --git a/docs/datasets/detect/coco.md b/docs/datasets/detect/coco.md index b296b7f..9f6a270 100644 --- a/docs/datasets/detect/coco.md +++ b/docs/datasets/detect/coco.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the COCO dataset, designed to encourage research on object detection, segmentation, and captioning with standardized evaluation metrics. -keywords: COCO dataset, object detection, segmentation, captioning, deep learning models, computer vision, benchmarking, data annotations, COCO Consortium +description: Learn how COCO, a leading dataset for object detection and segmentation, integrates with Ultralytics. Discover ways to use it for training YOLO models. +keywords: Ultralytics, COCO dataset, object detection, YOLO, YOLO model training, image segmentation, computer vision, deep learning models --- # COCO Dataset diff --git a/docs/datasets/detect/coco8.md b/docs/datasets/detect/coco8.md index 8cbb75a..703d087 100644 --- a/docs/datasets/detect/coco8.md +++ b/docs/datasets/detect/coco8.md @@ -1,7 +1,7 @@ --- comments: true -description: Get started with Ultralytics COCO8. Ideal for testing and debugging object detection models or experimenting with new detection approaches. -keywords: Ultralytics, COCO8, object detection dataset, YAML file format, dataset usage, COCO dataset, acknowledgments +description: Discover the benefits of using the practical and diverse COCO8 dataset for object detection model testing. Learn to configure and use it via Ultralytics HUB and YOLOv8. +keywords: Ultralytics, COCO8 dataset, object detection, model testing, dataset configuration, detection approaches, sanity check, training pipelines, YOLOv8 --- # COCO8 Dataset diff --git a/docs/datasets/detect/globalwheat2020.md b/docs/datasets/detect/globalwheat2020.md index 9b99974..27fb6fa 100644 --- a/docs/datasets/detect/globalwheat2020.md +++ b/docs/datasets/detect/globalwheat2020.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the Global Wheat Head Dataset, aimed at supporting the development of accurate wheat head models for applications in wheat phenotyping and crop management. -keywords: Global Wheat Head Dataset, wheat head detection, wheat phenotyping, crop management, object detection, deep learning models, dataset structure, annotations, sample data, citations and acknowledgments +description: Understand how to utilize the vast Global Wheat Head Dataset for building wheat head detection models. Features, structure, applications, usage, sample data, and citation. +keywords: Ultralytics, YOLO, Global Wheat Head Dataset, wheat head detection, plant phenotyping, crop management, deep learning, outdoor images, annotations, YAML configuration --- # Global Wheat Head Dataset diff --git a/docs/datasets/detect/index.md b/docs/datasets/detect/index.md index cf29cba..9a7b3b6 100644 --- a/docs/datasets/detect/index.md +++ b/docs/datasets/detect/index.md @@ -1,7 +1,7 @@ --- comments: true -description: Explore supported dataset formats for training YOLO detection models, including Ultralytics YOLO and COCO. This guide covers various dataset formats and their specific configurations for effective object detection training. -keywords: object detection, datasets, formats, Ultralytics YOLO, COCO, label format, dataset file format, dataset definition, YOLO dataset, model configuration +description: Navigate through supported dataset formats, methods to utilize them and how to add your own datasets. Get insights on porting or converting label formats. +keywords: Ultralytics, YOLO, datasets, object detection, dataset formats, label formats, data conversion --- # Object Detection Datasets Overview diff --git a/docs/datasets/detect/objects365.md b/docs/datasets/detect/objects365.md index 85a65f1..e47d83a 100644 --- a/docs/datasets/detect/objects365.md +++ b/docs/datasets/detect/objects365.md @@ -1,7 +1,7 @@ --- comments: true -description: Discover the Objects365 dataset, designed for object detection research with a focus on diverse objects, featuring 365 categories, 2 million images, and 30 million bounding boxes. -keywords: Objects365 dataset, object detection, computer vision, deep learning, Ultralytics Docs +description: Discover the Objects365 dataset, a wide-scale, high-quality resource for object detection research. Learn to use it with the Ultralytics YOLO model. +keywords: Objects365, object detection, Ultralytics, dataset, YOLO, bounding boxes, annotations, computer vision, deep learning, training models --- # Objects365 Dataset diff --git a/docs/datasets/detect/sku-110k.md b/docs/datasets/detect/sku-110k.md index 419dc72..270dad9 100644 --- a/docs/datasets/detect/sku-110k.md +++ b/docs/datasets/detect/sku-110k.md @@ -1,7 +1,7 @@ --- comments: true -description: Explore the SKU-110k dataset, designed for object detection in densely packed retail shelf images, featuring over 110k unique SKU categories and annotations. -keywords: SKU-110k, object detection, retail shelves, dataset, computer vision +description: 'Explore the SKU-110k dataset: densely packed retail shelf images for object detection research. Learn how to use it with Ultralytics.' +keywords: SKU-110k dataset, object detection, retail shelf images, Ultralytics, YOLO, computer vision, deep learning models --- # SKU-110k Dataset diff --git a/docs/datasets/detect/visdrone.md b/docs/datasets/detect/visdrone.md index 15b5995..fc2218d 100644 --- a/docs/datasets/detect/visdrone.md +++ b/docs/datasets/detect/visdrone.md @@ -1,7 +1,7 @@ --- comments: true -description: Discover the VisDrone dataset, a comprehensive benchmark for drone-based computer vision tasks, including object detection, tracking, and crowd counting. -keywords: VisDrone Dataset, Ultralytics YOLO Docs, AISKYEYE, Lab of Machine Learning and Data Mining, Computer Vision tasks, drone-based image analysis, object detection, object tracking, crowd counting, YOLOv8n model +description: Explore the VisDrone Dataset, a large-scale benchmark for drone-based image analysis, and learn how to train a YOLO model using it. +keywords: VisDrone Dataset, Ultralytics, drone-based image analysis, YOLO model, object detection, object tracking, crowd counting --- # VisDrone Dataset diff --git a/docs/datasets/detect/voc.md b/docs/datasets/detect/voc.md index c9f5993..5a42524 100644 --- a/docs/datasets/detect/voc.md +++ b/docs/datasets/detect/voc.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the VOC dataset, designed to encourage research on object detection, segmentation, and classification with standardized evaluation metrics. -keywords: PASCAL VOC dataset, object detection, segmentation, classification, computer vision, deep learning, benchmarking, VOC2007, VOC2012, mean Average Precision, mAP, PASCAL VOC evaluation server, trained models, YAML, YAML file, VOC.yaml, training, YOLOv8n model, model training, image size, annotations, object bounding boxes, segmentation masks, instance segmentation, SSD, Mask R-CNN, yolov8n.pt, mosaicing, PASCAL VOC Consortium +description: A complete guide to the PASCAL VOC dataset used for object detection, segmentation and classification tasks with relevance to YOLO model training. +keywords: Ultralytics, PASCAL VOC dataset, object detection, segmentation, image classification, YOLO, model training, VOC.yaml, deep learning --- # VOC Dataset diff --git a/docs/datasets/detect/xview.md b/docs/datasets/detect/xview.md index db956b9..9bdb55b 100644 --- a/docs/datasets/detect/xview.md +++ b/docs/datasets/detect/xview.md @@ -1,7 +1,7 @@ --- comments: true -description: Discover the xView Dataset, a large-scale overhead imagery dataset for object detection tasks, featuring 1M instances, 60 classes, and high-resolution images. -keywords: xView dataset, overhead imagery, computer vision, deep learning models, satellite imagery analysis, object detection +description: Explore xView, a large-scale, high resolution satellite imagery dataset for object detection. Dive into dataset structure, usage examples & its potential applications. +keywords: Ultralytics, YOLO, computer vision, xView dataset, satellite imagery, object detection, overhead imagery, training, deep learning, dataset YAML --- # xView Dataset diff --git a/docs/datasets/index.md b/docs/datasets/index.md index 72dbef6..8f19a1c 100644 --- a/docs/datasets/index.md +++ b/docs/datasets/index.md @@ -1,7 +1,7 @@ --- comments: true -description: Ultralytics provides support for various datasets to facilitate multiple computer vision tasks. Check out our list of main datasets and their summaries. -keywords: ultralytics, computer vision, object detection, instance segmentation, pose estimation, image classification, multi-object tracking +description: Explore various computer vision datasets supported by Ultralytics for object detection, segmentation, pose estimation, image classification, and multi-object tracking. +keywords: computer vision, datasets, Ultralytics, YOLO, object detection, instance segmentation, pose estimation, image classification, multi-object tracking --- # Datasets Overview diff --git a/docs/datasets/pose/coco.md b/docs/datasets/pose/coco.md index 72d6eb6..6466e6e 100644 --- a/docs/datasets/pose/coco.md +++ b/docs/datasets/pose/coco.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the COCO-Pose dataset, designed to encourage research on pose estimation tasks with standardized evaluation metrics. -keywords: COCO-Pose, COCO dataset, pose estimation, keypoints detection, computer vision, deep learning, YOLOv8n-pose, dataset configuration +description: Detailed guide on the special COCO-Pose Dataset in Ultralytics. Learn about its key features, structure, and usage in pose estimation tasks with YOLO. +keywords: Ultralytics YOLO, COCO-Pose Dataset, Deep Learning, Pose Estimation, Training Models, Dataset YAML, openpose, YOLO --- # COCO-Pose Dataset diff --git a/docs/datasets/pose/coco8-pose.md b/docs/datasets/pose/coco8-pose.md index e13cd04..c0e2996 100644 --- a/docs/datasets/pose/coco8-pose.md +++ b/docs/datasets/pose/coco8-pose.md @@ -1,7 +1,7 @@ --- comments: true -description: Test and debug object detection models with Ultralytics COCO8-Pose Dataset - a small, versatile pose detection dataset with 8 images. -keywords: coco8-pose dataset, ultralytics, object detection, pose detection, yolo, hub +description: Discover the versatile COCO8-Pose dataset, perfect for testing and debugging pose detection models. Learn how to get started with YOLOv8-pose model training. +keywords: Ultralytics, YOLOv8, pose detection, COCO8-Pose dataset, dataset, model training, YAML --- # COCO8-Pose Dataset diff --git a/docs/datasets/pose/index.md b/docs/datasets/pose/index.md index b18012b..ff0f8ce 100644 --- a/docs/datasets/pose/index.md +++ b/docs/datasets/pose/index.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn how to format your dataset for training YOLO models with Ultralytics YOLO format using our concise tutorial and example YAML files. -keywords: pose estimation, datasets, supported formats, YAML file, object class index, keypoints, ultralytics YOLO format +description: Understand the YOLO pose dataset format and learn to use Ultralytics datasets to train your pose estimation models effectively. +keywords: Ultralytics, YOLO, pose estimation, datasets, training, YAML, keypoints, COCO-Pose, COCO8-Pose, data conversion --- # Pose Estimation Datasets Overview @@ -125,4 +125,4 @@ from ultralytics.data.converter import convert_coco convert_coco(labels_dir='../coco/annotations/', use_keypoints=True) ``` -This conversion tool can be used to convert the COCO dataset or any dataset in the COCO format to the Ultralytics YOLO format. The `use_keypoints` parameter specifies whether to include keypoints (for pose estimation) in the converted labels. +This conversion tool can be used to convert the COCO dataset or any dataset in the COCO format to the Ultralytics YOLO format. The `use_keypoints` parameter specifies whether to include keypoints (for pose estimation) in the converted labels. \ No newline at end of file diff --git a/docs/datasets/segment/coco.md b/docs/datasets/segment/coco.md index c84a818..a1a102d 100644 --- a/docs/datasets/segment/coco.md +++ b/docs/datasets/segment/coco.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the COCO-Seg dataset, designed for simple training of YOLO models on instance segmentation tasks. -keywords: COCO-Seg, COCO, instance segmentation, segmentation annotations, computer vision, deep learning, data science, YOLO models, image size, open-source datasets +description: Explore the possibilities of the COCO-Seg dataset, designed for object instance segmentation and YOLO model training. Discover key features, dataset structure, applications, and usage. +keywords: Ultralytics, YOLO, COCO-Seg, dataset, instance segmentation, model training, deep learning, computer vision --- # COCO-Seg Dataset diff --git a/docs/datasets/segment/coco8-seg.md b/docs/datasets/segment/coco8-seg.md index b35c4d5..32fa157 100644 --- a/docs/datasets/segment/coco8-seg.md +++ b/docs/datasets/segment/coco8-seg.md @@ -1,7 +1,7 @@ --- comments: true -description: Test and debug segmentation models on small, versatile COCO8-Seg instance segmentation dataset, now available for use with YOLOv8 and Ultralytics HUB. -keywords: Ultralytics, COCO8-Seg, instance segmentation dataset, segmentation models, new detection approaches, COCO train 2017 set +description: 'Discover the COCO8-Seg: a compact but versatile instance segmentation dataset ideal for testing Ultralytics YOLOv8 detection approaches. Complete usage guide included.' +keywords: COCO8-Seg dataset, Ultralytics, YOLOv8, instance segmentation, dataset configuration, YAML, YOLOv8n-seg model, mosaiced dataset images --- # COCO8-Seg Dataset diff --git a/docs/datasets/segment/index.md b/docs/datasets/segment/index.md index af2dc96..0dd8459 100644 --- a/docs/datasets/segment/index.md +++ b/docs/datasets/segment/index.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the Ultralytics YOLO dataset format for segmentation models. Use YAML to train Detection Models. Convert COCO to YOLO format using Python. -keywords: instance segmentation datasets, yolov8 segmentations, yaml dataset format, auto annotation, convert label formats +description: Learn how Ultralytics YOLO supports various dataset formats for instance segmentation. This guide includes information on data conversions, auto-annotations, and dataset usage. +keywords: Ultralytics, YOLO, Instance Segmentation, Dataset, YAML, COCO, Auto-Annotation, Image Segmentation --- # Instance Segmentation Datasets Overview diff --git a/docs/datasets/track/index.md b/docs/datasets/track/index.md index 7a6ff5e..9ae4979 100644 --- a/docs/datasets/track/index.md +++ b/docs/datasets/track/index.md @@ -1,7 +1,7 @@ --- comments: true -description: Discover the datasets compatible with Multi-Object Detector. Train your trackers and make your detections more efficient with Ultralytics' YOLO. -keywords: multi-object tracking, dataset format, ultralytics yolo, object detection, segmentation, pose model, python, cli +description: Understand multi-object tracking datasets, upcoming features and how to use them with YOLO in Python and CLI. Dive in now!. +keywords: Ultralytics, YOLO, multi-object tracking, datasets, detection, segmentation, pose models, Python, CLI --- # Multi-object Tracking Datasets Overview diff --git a/docs/help/CI.md b/docs/help/CI.md index 2fdad90..3fea95d 100644 --- a/docs/help/CI.md +++ b/docs/help/CI.md @@ -1,7 +1,7 @@ --- comments: true -description: Understand all the Continuous Integration (CI) tests for Ultralytics repositories and see their statuses in a clear, concise table. -keywords: Ultralytics, CI Tests, Continuous Integration, Docker Deployment, Broken Links, CodeQL, PyPI Publishing +description: Learn how Ultralytics leverages Continuous Integration (CI) for maintaining high-quality code. Explore our CI tests and the status of these tests for our repositories. +keywords: continuous integration, software development, CI tests, Ultralytics repositories, high-quality code, Docker Deployment, Broken Links, CodeQL, PyPi Publishing --- # Continuous Integration (CI) diff --git a/docs/help/CLA.md b/docs/help/CLA.md index ffc9371..10a7ca6 100644 --- a/docs/help/CLA.md +++ b/docs/help/CLA.md @@ -1,6 +1,6 @@ --- -description: Individual Contributor License Agreement. Settle Intellectual Property issues for Contributions made to anything open source released by Ultralytics. -keywords: Ultralytics, Individual, Contributor, License, Agreement, open source, software, projects, contributions +description: Understand terms governing contributions to Ultralytics projects including source code, bug fixes, documentation and more. Read our Contributor License Agreement. +keywords: Ultralytics, Contributor License Agreement, Open Source Software, Contributions, Copyright License, Patent License, Moral Rights --- # Ultralytics Individual Contributor License Agreement diff --git a/docs/help/FAQ.md b/docs/help/FAQ.md index 1369202..94c2f78 100644 --- a/docs/help/FAQ.md +++ b/docs/help/FAQ.md @@ -1,7 +1,7 @@ --- comments: true -description: 'Get quick answers to common Ultralytics YOLO questions: Hardware requirements, fine-tuning, conversion, real-time detection, and accuracy tips.' -keywords: Ultralytics YOLO, Frequently Asked Questions, hardware requirements, model fine-tuning, converting to ONNX, TensorFlow, real-time detection, improving model accuracy +description: Find solutions to your common Ultralytics YOLO related queries. Learn about hardware requirements, fine-tuning YOLO models, conversion to ONNX/TensorFlow, and more. +keywords: Ultralytics, YOLO, FAQ, hardware requirements, ONNX, TensorFlow, real-time detection, YOLO accuracy --- # Ultralytics YOLO Frequently Asked Questions (FAQ) diff --git a/docs/help/code_of_conduct.md b/docs/help/code_of_conduct.md index 1cc27e1..c23efdd 100644 --- a/docs/help/code_of_conduct.md +++ b/docs/help/code_of_conduct.md @@ -1,7 +1,7 @@ --- comments: true -description: Read the Ultralytics Contributor Covenant Code of Conduct. Learn ways to create a welcoming community & consequences for inappropriate conduct. -keywords: Ultralytics, contributor, covenant, code, conduct, pledge, standards, enforcement, harassment-free, community, guidelines +description: Explore Ultralytics community’s Code of Conduct, ensuring a supportive, inclusive environment for contributors & members at all levels. Find our guidelines on acceptable behavior & enforcement. +keywords: Ultralytics, code of conduct, community, contribution, behavior guidelines, enforcement, open source contributions --- # Ultralytics Contributor Covenant Code of Conduct diff --git a/docs/help/contributing.md b/docs/help/contributing.md index 4fa8f63..0069fad 100644 --- a/docs/help/contributing.md +++ b/docs/help/contributing.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn how to contribute to Ultralytics Open-Source YOLO Repositories with contributions guidelines, pull requests requirements, and GitHub CI tests. -keywords: Ultralytics YOLO, Open source, Contribution guidelines, Pull requests, CLA, GitHub Actions CI Tests, Google-style docstrings +description: Learn how to contribute to Ultralytics YOLO projects – guidelines for pull requests, reporting bugs, code conduct and CLA signing. +keywords: Ultralytics, YOLO, open-source, contribute, pull request, bug report, coding guidelines, CLA, code of conduct, GitHub --- # Contributing to Ultralytics Open-Source YOLO Repositories diff --git a/docs/help/environmental-health-safety.md b/docs/help/environmental-health-safety.md index 2d072a5..006f864 100644 --- a/docs/help/environmental-health-safety.md +++ b/docs/help/environmental-health-safety.md @@ -1,7 +1,7 @@ --- comments: false -description: Discover Ultralytics' commitment to Environmental, Health, and Safety (EHS). Learn about our policy, principles, and strategies for ensuring a sustainable and safe working environment. -keywords: Ultralytics, Environmental Policy, Health and Safety, EHS, Sustainability, Workplace Safety, Environmental Compliance +description: Discover Ultralytics’ EHS policy principles and implementation measures. Committed to safety, environment, and continuous improvement for a sustainable future. +keywords: Ultralytics policy, EHS, environment, health and safety, compliance, prevention, continuous improvement, risk management, emergency preparedness, resource allocation, communication --- # Ultralytics Environmental, Health and Safety (EHS) Policy @@ -34,4 +34,4 @@ At Ultralytics, we recognize that the long-term success of our company relies no This policy reflects our commitment to minimizing our environmental footprint, ensuring the safety and well-being of our employees, and continuously improving our performance. -Please remember that the implementation of an effective EHS policy requires the involvement and commitment of everyone working at or with Ultralytics. We encourage you to take personal responsibility for your safety and the safety of others, and to take care of the environment in which we live and work. +Please remember that the implementation of an effective EHS policy requires the involvement and commitment of everyone working at or with Ultralytics. We encourage you to take personal responsibility for your safety and the safety of others, and to take care of the environment in which we live and work. \ No newline at end of file diff --git a/docs/help/index.md b/docs/help/index.md index ed6b93e..00c20af 100644 --- a/docs/help/index.md +++ b/docs/help/index.md @@ -1,7 +1,7 @@ --- comments: true -description: Get comprehensive resources for Ultralytics YOLO repositories. Find guides, FAQs, MRE creation, CLA & more. Join the supportive community now! -keywords: ultralytics, yolo, help, guide, resources, faq, contributing, continuous integration, contributor license agreement, minimum reproducible example, code of conduct, security policy +description: Find comprehensive guides and documents on Ultralytics YOLO tasks. Includes FAQs, contributing guides, CI guide, CLA, MRE guide, code of conduct & more. +keywords: Ultralytics, YOLO, guides, documents, FAQ, contributing, CI guide, CLA, MRE guide, code of conduct, EHS policy, security policy --- Welcome to the Ultralytics Help page! We are committed to providing you with comprehensive resources to make your experience with Ultralytics YOLO repositories as smooth and enjoyable as possible. On this page, you'll find essential links to guides and documents that will help you navigate through common tasks and address any questions you might have while using our repositories. diff --git a/docs/help/minimum_reproducible_example.md b/docs/help/minimum_reproducible_example.md index 1a8acd2..0dba0e6 100644 --- a/docs/help/minimum_reproducible_example.md +++ b/docs/help/minimum_reproducible_example.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn how to create a Minimum Reproducible Example (MRE) for Ultralytics YOLO bug reports to help maintainers and contributors understand your issue better. -keywords: Ultralytics, YOLO, bug report, minimum reproducible example, MRE, isolate problem, public models, public datasets, necessary dependencies, clear description, format code properly, test code, GitHub code block, error message +description: Learn how to create minimum reproducible examples (MRE) for efficient bug reporting in Ultralytics YOLO repositories with this step-by-step guide. +keywords: Ultralytics, YOLO, minimum reproducible example, MRE, bug reports, guide, dependencies, code, troubleshooting --- # Creating a Minimum Reproducible Example for Bug Reports in Ultralytics YOLO Repositories diff --git a/docs/hub/app/android.md b/docs/hub/app/android.md index 2f2ea9b..1177db5 100644 --- a/docs/hub/app/android.md +++ b/docs/hub/app/android.md @@ -1,7 +1,7 @@ --- comments: true -description: Run YOLO models on your Android device for real-time object detection with Ultralytics Android App. Utilizes TensorFlow Lite and hardware delegates. -keywords: Ultralytics, Android, app, YOLO models, real-time object detection, TensorFlow Lite, quantization, acceleration, delegates, performance variability +description: Learn about the Ultralytics Android App, enabling real-time object detection using YOLO models. Discover in-app features, quantization methods, and delegate options for optimal performance. +keywords: Ultralytics, Android App, real-time object detection, YOLO models, TensorFlow Lite, FP16 quantization, INT8 quantization, CPU, GPU, Hexagon, NNAPI --- # Ultralytics Android App: Real-time Object Detection with YOLO Models diff --git a/docs/hub/app/index.md b/docs/hub/app/index.md index 76b8ce3..4f87e7a 100644 --- a/docs/hub/app/index.md +++ b/docs/hub/app/index.md @@ -1,7 +1,7 @@ --- comments: true -description: Experience the power of YOLOv5 and YOLOv8 models with Ultralytics HUB app. Download from Google Play and App Store now. -keywords: Ultralytics, HUB, App, Mobile, Object Detection, Image Recognition, YOLOv5, YOLOv8, Hardware Acceleration, Custom Model Training, iOS, Android +description: Explore the Ultralytics HUB App, offering the ability to run YOLOv5 and YOLOv8 models on your iOS and Android devices with optimized performance. +keywords: Ultralytics, HUB App, YOLOv5, YOLOv8, mobile AI, real-time object detection, image recognition, mobile device, hardware acceleration, Apple Neural Engine, Android GPU, NNAPI, custom model training --- # Ultralytics HUB App diff --git a/docs/hub/app/ios.md b/docs/hub/app/ios.md index ed49f45..09c5792 100644 --- a/docs/hub/app/ios.md +++ b/docs/hub/app/ios.md @@ -1,7 +1,7 @@ --- comments: true -description: Get started with the Ultralytics iOS app and run YOLO models in real-time for object detection on your iPhone or iPad with the Apple Neural Engine. -keywords: YOLO, object detection, iOS app, Ultralytics, Apple Neural Engine, quantization, FP16, INT8, Core ML, machine learning +description: Execute object detection in real-time on your iOS devices utilizing YOLO models. Leverage the power of the Apple Neural Engine and Core ML for fast and efficient object detection. +keywords: Ultralytics, iOS app, object detection, YOLO models, real time, Apple Neural Engine, Core ML, FP16, INT8, quantization --- # Ultralytics iOS App: Real-time Object Detection with YOLO Models diff --git a/docs/hub/datasets.md b/docs/hub/datasets.md index 77a4946..7ca5c5a 100644 --- a/docs/hub/datasets.md +++ b/docs/hub/datasets.md @@ -1,7 +1,7 @@ --- comments: true -description: Efficiently manage and use custom datasets on Ultralytics HUB for streamlined training with YOLOv5 and YOLOv8 models. -keywords: Ultralytics, HUB, Datasets, Upload, Visualize, Train, Custom Data, YAML, YOLOv5, YOLOv8 +description: Learn how Ultralytics HUB datasets streamline your ML workflow. Upload, format, validate, access, share, edit or delete datasets for Ultralytics YOLO model training. +keywords: Ultralytics, HUB datasets, YOLO model training, upload datasets, dataset validation, ML workflow, share datasets --- # HUB Datasets @@ -156,4 +156,4 @@ Navigate to the Dataset page of the dataset you want to delete, open the dataset If you change your mind, you can restore the dataset from the [Trash](https://hub.ultralytics.com/trash) page. - ![Ultralytics HUB screenshot of the Trash page with an arrow pointing to the Restore option of one of the datasets](https://raw.githubusercontent.com/ultralytics/assets/main/docs/hub/datasets/hub_delete_dataset_3.jpg) + ![Ultralytics HUB screenshot of the Trash page with an arrow pointing to the Restore option of one of the datasets](https://raw.githubusercontent.com/ultralytics/assets/main/docs/hub/datasets/hub_delete_dataset_3.jpg) \ No newline at end of file diff --git a/docs/hub/index.md b/docs/hub/index.md index 30f1652..790bfae 100644 --- a/docs/hub/index.md +++ b/docs/hub/index.md @@ -1,7 +1,7 @@ --- comments: true -description: 'Ultralytics HUB: Train & deploy YOLO models from one spot! Use drag-and-drop interface with templates & pre-training models. Check quickstart, datasets, and more.' -keywords: Ultralytics HUB, YOLOv5, YOLOv8, object detection, instance segmentation, classification, drag-and-drop interface, pre-trained models, integrations, mobile app, Inference API, datasets, projects, models +description: Gain seamless experience in training and deploying your YOLOv5 and YOLOv8 models with Ultralytics HUB. Explore pre-trained models, templates and various integrations. +keywords: Ultralytics HUB, YOLOv5, YOLOv8, model training, model deployment, pretrained models, model integrations --- # Ultralytics HUB diff --git a/docs/hub/inference_api.md b/docs/hub/inference_api.md index 22851ab..ca623d1 100644 --- a/docs/hub/inference_api.md +++ b/docs/hub/inference_api.md @@ -1,7 +1,7 @@ --- comments: true -description: Explore Ultralytics YOLOv8 Inference API for efficient object detection. Check out our Python and CLI examples to streamline your image analysis. -keywords: YOLO, object detection, Ultralytics, inference API, RESTful API +description: Access object detection capabilities of YOLOv8 via our RESTful API. Learn how to use the YOLO Inference API with Python or CLI for swift object detection. +keywords: Ultralytics, YOLOv8, Inference API, object detection, RESTful API, Python, CLI, Quickstart --- # YOLO Inference API diff --git a/docs/hub/models.md b/docs/hub/models.md index 31cba2d..ccaae53 100644 --- a/docs/hub/models.md +++ b/docs/hub/models.md @@ -1,7 +1,7 @@ --- comments: true -description: Train and Deploy your Model to 13 different formats, including TensorFlow, ONNX, OpenVINO, CoreML, Paddle or directly on Mobile. -keywords: Ultralytics, HUB, models, artificial intelligence, APIs, export models, TensorFlow, ONNX, Paddle, OpenVINO, CoreML, iOS, Android +description: Learn how to use Ultralytics HUB models for efficient and user-friendly AI model training. For easy model creation, training, evaluation and deployment, follow our detailed guide. +keywords: Ultralytics, HUB Models, AI model training, model creation, model training, model evaluation, model deployment --- # Ultralytics HUB Models @@ -210,4 +210,4 @@ Navigate to the Model page of the model you want to delete, open the model actio If you change your mind, you can restore the model from the [Trash](https://hub.ultralytics.com/trash) page. - ![Ultralytics HUB screenshot of the Trash page with an arrow pointing to the Restore option of one of the models](https://raw.githubusercontent.com/ultralytics/assets/main/docs/hub/models/hub_delete_model_3.jpg) + ![Ultralytics HUB screenshot of the Trash page with an arrow pointing to the Restore option of one of the models](https://raw.githubusercontent.com/ultralytics/assets/main/docs/hub/models/hub_delete_model_3.jpg) \ No newline at end of file diff --git a/docs/hub/projects.md b/docs/hub/projects.md index d8e0f86..8577936 100644 --- a/docs/hub/projects.md +++ b/docs/hub/projects.md @@ -1,7 +1,7 @@ --- comments: true -description: Efficiently manage and compare AI models with Ultralytics HUB Projects. Create, share, and edit projects for streamlined model development. -keywords: Ultralytics HUB projects, model management, model comparison, create project, share project, edit project, delete project, compare models +description: Learn how to manage Ultralytics HUB projects. Understand effective strategies to create, share, edit, delete, and compare models in an organized workspace. +keywords: Ultralytics, HUB projects, Create project, Edit project, Share project, Delete project, Compare Models, Model Management --- # Ultralytics HUB Projects @@ -166,4 +166,4 @@ Navigate to the Project page of the project where the model you want to mode is Select the project you want to transfer the model to and click **Save**. -![Ultralytics HUB screenshot of the Transfer Model dialog with an arrow pointing to the dropdown and one to the Save button](https://raw.githubusercontent.com/ultralytics/assets/main/docs/hub/projects/hub_transfer_models_3.jpg) +![Ultralytics HUB screenshot of the Transfer Model dialog with an arrow pointing to the dropdown and one to the Save button](https://raw.githubusercontent.com/ultralytics/assets/main/docs/hub/projects/hub_transfer_models_3.jpg) \ No newline at end of file diff --git a/docs/index.md b/docs/index.md index 79768a1..f3e9ff5 100644 --- a/docs/index.md +++ b/docs/index.md @@ -1,7 +1,7 @@ --- comments: true -description: Explore Ultralytics YOLOv8, a cutting-edge real-time object detection and image segmentation model for various applications and hardware platforms. -keywords: YOLOv8, object detection, image segmentation, computer vision, machine learning, deep learning, AGPL-3.0 License, Enterprise License +description: Explore a complete guide to Ultralytics YOLOv8, a high-speed, high-accuracy object detection & image segmentation model. Installation, prediction, training tutorials and more. +keywords: Ultralytics, YOLOv8, object detection, image segmentation, machine learning, deep learning, computer vision, YOLOv8 installation, YOLOv8 prediction, YOLOv8 training, YOLO history, YOLO licenses ---
diff --git a/docs/models/fast-sam.md b/docs/models/fast-sam.md index c360a29..fae0c8c 100644 --- a/docs/models/fast-sam.md +++ b/docs/models/fast-sam.md @@ -1,7 +1,7 @@ --- comments: true -description: Explore the Fast Segment Anything Model (FastSAM), a real-time solution for the segment anything task that leverages a Convolutional Neural Network (CNN) for segmenting any object within an image, guided by user interaction prompts. -keywords: FastSAM, Segment Anything Model, SAM, Convolutional Neural Network, CNN, image segmentation, real-time image processing +description: Explore FastSAM, a CNN-based solution for real-time object segmentation in images. Enhanced user interaction, computational efficiency and adaptable across vision tasks. +keywords: FastSAM, machine learning, CNN-based solution, object segmentation, real-time solution, Ultralytics, vision tasks, image processing, industrial applications, user interaction --- # Fast Segment Anything Model (FastSAM) @@ -166,4 +166,4 @@ We would like to acknowledge the FastSAM authors for their significant contribut } ``` -The original FastSAM paper can be found on [arXiv](https://arxiv.org/abs/2306.12156). The authors have made their work publicly available, and the codebase can be accessed on [GitHub](https://github.com/CASIA-IVA-Lab/FastSAM). We appreciate their efforts in advancing the field and making their work accessible to the broader community. +The original FastSAM paper can be found on [arXiv](https://arxiv.org/abs/2306.12156). The authors have made their work publicly available, and the codebase can be accessed on [GitHub](https://github.com/CASIA-IVA-Lab/FastSAM). We appreciate their efforts in advancing the field and making their work accessible to the broader community. \ No newline at end of file diff --git a/docs/models/index.md b/docs/models/index.md index e841db2..04d7044 100644 --- a/docs/models/index.md +++ b/docs/models/index.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about the supported models and architectures, such as YOLOv3, YOLOv5, and YOLOv8, and how to contribute your own model to Ultralytics. -keywords: Ultralytics YOLO, YOLOv3, YOLOv4, YOLOv5, YOLOv6, YOLOv7, YOLOv8, SAM, YOLO-NAS, RT-DETR, object detection, instance segmentation, detection transformers, real-time detection, computer vision, CLI, Python +description: Learn about the YOLO family, SAM, MobileSAM, FastSAM, YOLO-NAS, and RT-DETR models supported by Ultralytics, with examples on how to use them via CLI and Python. +keywords: Ultralytics, documentation, YOLO, SAM, MobileSAM, FastSAM, YOLO-NAS, RT-DETR, models, architectures, Python, CLI --- # Models @@ -45,4 +45,4 @@ model.info() # display model information model.train(data="coco128.yaml", epochs=100) # train the model ``` -For more details on each model, their supported tasks, modes, and performance, please visit their respective documentation pages linked above. +For more details on each model, their supported tasks, modes, and performance, please visit their respective documentation pages linked above. \ No newline at end of file diff --git a/docs/models/mobile-sam.md b/docs/models/mobile-sam.md index 0a7083b..0bf7a65 100644 --- a/docs/models/mobile-sam.md +++ b/docs/models/mobile-sam.md @@ -1,7 +1,7 @@ --- comments: true -description: MobileSAM is a lightweight adaptation of the Segment Anything Model (SAM) designed for mobile applications. It maintains the full functionality of the original SAM while significantly improving speed, making it suitable for CPU-only edge devices, such as mobile phones. -keywords: MobileSAM, Faster Segment Anything, Segment Anything, Segment Anything Model, SAM, Meta SAM, image segmentation, promptable segmentation, zero-shot performance, SA-1B dataset, advanced architecture, auto-annotation, Ultralytics, pre-trained models, SAM base, SAM large, instance segmentation, computer vision, AI, artificial intelligence, machine learning, data annotation, segmentation masks, detection model, YOLO detection model, bibtex, Meta AI +description: Learn more about MobileSAM, its implementation, comparison with the original SAM, and how to download and test it in the Ultralytics framework. Improve your mobile applications today. +keywords: MobileSAM, Ultralytics, SAM, mobile applications, Arxiv, GPU, API, image encoder, mask decoder, model download, testing method --- ![MobileSAM Logo](https://github.com/ChaoningZhang/MobileSAM/blob/master/assets/logo2.png?raw=true) @@ -96,4 +96,4 @@ If you find MobileSAM useful in your research or development work, please consid journal={arXiv preprint arXiv:2306.14289}, year={2023} } -``` +``` \ No newline at end of file diff --git a/docs/models/rtdetr.md b/docs/models/rtdetr.md index f2c6516..76b90ac 100644 --- a/docs/models/rtdetr.md +++ b/docs/models/rtdetr.md @@ -1,7 +1,7 @@ --- comments: true -description: Dive into Baidu's RT-DETR, a revolutionary real-time object detection model built on the foundation of Vision Transformers (ViT). Learn how to use pre-trained PaddlePaddle RT-DETR models with the Ultralytics Python API for various tasks. -keywords: RT-DETR, Transformer, ViT, Vision Transformers, Baidu RT-DETR, PaddlePaddle, Paddle Paddle RT-DETR, real-time object detection, Vision Transformers-based object detection, pre-trained PaddlePaddle RT-DETR models, Baidu's RT-DETR usage, Ultralytics Python API, object detector +description: Discover the features and benefits of RT-DETR, Baidu’s efficient and adaptable real-time object detector powered by Vision Transformers, including pre-trained models. +keywords: RT-DETR, Baidu, Vision Transformers, object detection, real-time performance, CUDA, TensorRT, IoU-aware query selection, Ultralytics, Python API, PaddlePaddle --- # Baidu's RT-DETR: A Vision Transformer-Based Real-Time Object Detector @@ -71,4 +71,4 @@ If you use Baidu's RT-DETR in your research or development work, please cite the We would like to acknowledge Baidu and the [PaddlePaddle](https://github.com/PaddlePaddle/PaddleDetection) team for creating and maintaining this valuable resource for the computer vision community. Their contribution to the field with the development of the Vision Transformers-based real-time object detector, RT-DETR, is greatly appreciated. -*Keywords: RT-DETR, Transformer, ViT, Vision Transformers, Baidu RT-DETR, PaddlePaddle, Paddle Paddle RT-DETR, real-time object detection, Vision Transformers-based object detection, pre-trained PaddlePaddle RT-DETR models, Baidu's RT-DETR usage, Ultralytics Python API* +*Keywords: RT-DETR, Transformer, ViT, Vision Transformers, Baidu RT-DETR, PaddlePaddle, Paddle Paddle RT-DETR, real-time object detection, Vision Transformers-based object detection, pre-trained PaddlePaddle RT-DETR models, Baidu's RT-DETR usage, Ultralytics Python API* \ No newline at end of file diff --git a/docs/models/sam.md b/docs/models/sam.md index ae334ce..ab47fa4 100644 --- a/docs/models/sam.md +++ b/docs/models/sam.md @@ -1,7 +1,7 @@ --- comments: true -description: Discover the Segment Anything Model (SAM), a revolutionary promptable image segmentation model, and delve into the details of its advanced architecture and the large-scale SA-1B dataset. -keywords: Segment Anything, Segment Anything Model, SAM, Meta SAM, image segmentation, promptable segmentation, zero-shot performance, SA-1B dataset, advanced architecture, auto-annotation, Ultralytics, pre-trained models, SAM base, SAM large, instance segmentation, computer vision, AI, artificial intelligence, machine learning, data annotation, segmentation masks, detection model, YOLO detection model, bibtex, Meta AI +description: Explore the cutting-edge Segment Anything Model (SAM) from Ultralytics that allows real-time image segmentation. Learn about its promptable segmentation, zero-shot performance, and how to use it. +keywords: Ultralytics, image segmentation, Segment Anything Model, SAM, SA-1B dataset, real-time performance, zero-shot transfer, object detection, image analysis, machine learning --- # Segment Anything Model (SAM) @@ -218,4 +218,4 @@ If you find SAM useful in your research or development work, please consider cit We would like to express our gratitude to Meta AI for creating and maintaining this valuable resource for the computer vision community. -*keywords: Segment Anything, Segment Anything Model, SAM, Meta SAM, image segmentation, promptable segmentation, zero-shot performance, SA-1B dataset, advanced architecture, auto-annotation, Ultralytics, pre-trained models, SAM base, SAM large, instance segmentation, computer vision, AI, artificial intelligence, machine learning, data annotation, segmentation masks, detection model, YOLO detection model, bibtex, Meta AI.* +*keywords: Segment Anything, Segment Anything Model, SAM, Meta SAM, image segmentation, promptable segmentation, zero-shot performance, SA-1B dataset, advanced architecture, auto-annotation, Ultralytics, pre-trained models, SAM base, SAM large, instance segmentation, computer vision, AI, artificial intelligence, machine learning, data annotation, segmentation masks, detection model, YOLO detection model, bibtex, Meta AI.* \ No newline at end of file diff --git a/docs/models/yolo-nas.md b/docs/models/yolo-nas.md index 4ce38e8..e21574c 100644 --- a/docs/models/yolo-nas.md +++ b/docs/models/yolo-nas.md @@ -1,7 +1,7 @@ --- comments: true -description: Dive into YOLO-NAS, Deci's next-generation object detection model, offering breakthroughs in speed and accuracy. Learn how to utilize pre-trained models using the Ultralytics Python API for various tasks. -keywords: YOLO-NAS, Deci AI, Ultralytics, object detection, deep learning, neural architecture search, Python API, pre-trained models, quantization +description: Explore detailed documentation of YOLO-NAS, a superior object detection model. Learn about its features, pre-trained models, usage with Ultralytics Python API, and more. +keywords: YOLO-NAS, Deci AI, object detection, deep learning, neural architecture search, Ultralytics Python API, YOLO model, pre-trained models, quantization, optimization, COCO, Objects365, Roboflow 100 --- # YOLO-NAS diff --git a/docs/models/yolov3.md b/docs/models/yolov3.md index da1415e..6315d1f 100644 --- a/docs/models/yolov3.md +++ b/docs/models/yolov3.md @@ -1,7 +1,7 @@ --- comments: true -description: YOLOv3, YOLOv3-Ultralytics and YOLOv3u by Ultralytics explained. Learn the evolution of these models and their specifications. -keywords: YOLOv3, Ultralytics YOLOv3, YOLO v3, YOLOv3 models, object detection, models, machine learning, AI, image recognition, object recognition +description: Get an overview of YOLOv3, YOLOv3-Ultralytics and YOLOv3u. Learn about their key features, usage, and supported tasks for object detection. +keywords: YOLOv3, YOLOv3-Ultralytics, YOLOv3u, Object Detection, Inferencing, Training, Ultralytics --- # YOLOv3, YOLOv3-Ultralytics, and YOLOv3u diff --git a/docs/models/yolov4.md b/docs/models/yolov4.md index 36a09cc..ce78cf8 100644 --- a/docs/models/yolov4.md +++ b/docs/models/yolov4.md @@ -1,7 +1,7 @@ --- comments: true -description: Explore YOLOv4, a state-of-the-art, real-time object detector. Learn about its architecture, features, and performance. -keywords: YOLOv4, object detection, real-time, CNN, GPU, Ultralytics, documentation, YOLOv4 architecture, YOLOv4 features, YOLOv4 performance +description: Explore our detailed guide on YOLOv4, a state-of-the-art real-time object detector. Understand its architectural highlights, innovative features, and application examples. +keywords: ultralytics, YOLOv4, object detection, neural network, real-time detection, object detector, machine learning --- # YOLOv4: High-Speed and Precise Object Detection diff --git a/docs/models/yolov5.md b/docs/models/yolov5.md index 884fea6..231dad7 100644 --- a/docs/models/yolov5.md +++ b/docs/models/yolov5.md @@ -1,7 +1,7 @@ --- comments: true -description: YOLOv5 by Ultralytics explained. Discover the evolution of this model and its key specifications. Experience faster and more accurate object detection. -keywords: YOLOv5, Ultralytics YOLOv5, YOLO v5, YOLOv5 models, YOLO, object detection, model, neural network, accuracy, speed, pre-trained weights, inference, validation, training +description: Discover YOLOv5u, a boosted version of the YOLOv5 model featuring an improved accuracy-speed tradeoff and numerous pre-trained models for various object detection tasks. +keywords: YOLOv5u, object detection, pre-trained models, Ultralytics, Inference, Validation, YOLOv5, YOLOv8, anchor-free, objectness-free, real-time applications, machine learning --- # YOLOv5 diff --git a/docs/models/yolov6.md b/docs/models/yolov6.md index a8a2449..1012c13 100644 --- a/docs/models/yolov6.md +++ b/docs/models/yolov6.md @@ -1,7 +1,7 @@ --- comments: true -description: Discover Meituan YOLOv6, a robust real-time object detector. Learn how to utilize pre-trained models with Ultralytics Python API for a variety of tasks. -keywords: Meituan, YOLOv6, object detection, Bi-directional Concatenation (BiC), anchor-aided training (AAT), pre-trained models, high-resolution input, real-time, ultra-fast computations +description: Explore Meituan YOLOv6, a state-of-the-art object detection model striking a balance between speed and accuracy. Dive into features, pre-trained models, and Python usage. +keywords: Meituan YOLOv6, object detection, Ultralytics, YOLOv6 docs, Bi-directional Concatenation, Anchor-Aided Training, pretrained models, real-time applications --- # Meituan YOLOv6 diff --git a/docs/models/yolov7.md b/docs/models/yolov7.md index d8b1ea6..20ae129 100644 --- a/docs/models/yolov7.md +++ b/docs/models/yolov7.md @@ -1,7 +1,7 @@ --- comments: true -description: Discover YOLOv7, a cutting-edge real-time object detector that surpasses competitors in speed and accuracy. Explore its unique trainable bag-of-freebies. -keywords: object detection, real-time object detector, YOLOv7, MS COCO, computer vision, neural networks, AI, deep learning, deep neural networks, real-time, GPU, GitHub, arXiv +description: Explore the YOLOv7, a real-time object detector. Understand its superior speed, impressive accuracy, and unique trainable bag-of-freebies optimization focus. +keywords: YOLOv7, real-time object detector, state-of-the-art, Ultralytics, MS COCO dataset, model re-parameterization, dynamic label assignment, extended scaling, compound scaling --- # YOLOv7: Trainable Bag-of-Freebies diff --git a/docs/models/yolov8.md b/docs/models/yolov8.md index 8907248..02225c5 100644 --- a/docs/models/yolov8.md +++ b/docs/models/yolov8.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about YOLOv8's pre-trained weights supporting detection, instance segmentation, pose, and classification tasks. Get performance details. -keywords: YOLOv8, real-time object detection, object detection, deep learning, machine learning +description: Explore the thrilling features of YOLOv8, the latest version of our real-time object detector! Learn how advanced architectures, pre-trained models and optimal balance between accuracy & speed make YOLOv8 the perfect choice for your object detection tasks. +keywords: YOLOv8, Ultralytics, real-time object detector, pre-trained models, documentation, object detection, YOLO series, advanced architectures, accuracy, speed --- # YOLOv8 diff --git a/docs/modes/benchmark.md b/docs/modes/benchmark.md index 9ce6221..d90cd47 100644 --- a/docs/modes/benchmark.md +++ b/docs/modes/benchmark.md @@ -1,7 +1,7 @@ --- comments: true -description: Benchmark mode compares speed and accuracy of various YOLOv8 export formats like ONNX or OpenVINO. Optimize formats for speed or accuracy. -keywords: YOLOv8, Benchmark Mode, Export Formats, ONNX, OpenVINO, TensorRT, Ultralytics Docs +description: Learn how to profile speed and accuracy of YOLOv8 across various export formats; get insights on mAP50-95, accuracy_top5 metrics, and more. +keywords: Ultralytics, YOLOv8, benchmarking, speed profiling, accuracy profiling, mAP50-95, accuracy_top5, ONNX, OpenVINO, TensorRT, YOLO export formats --- diff --git a/docs/modes/export.md b/docs/modes/export.md index bff65d3..9f76d36 100644 --- a/docs/modes/export.md +++ b/docs/modes/export.md @@ -1,7 +1,7 @@ --- comments: true -description: 'Export mode: Create a deployment-ready YOLOv8 model by converting it to various formats. Export to ONNX or OpenVINO for up to 3x CPU speedup.' -keywords: ultralytics docs, YOLOv8, export YOLOv8, YOLOv8 model deployment, exporting YOLOv8, ONNX, OpenVINO, TensorRT, CoreML, TF SavedModel, PaddlePaddle, TorchScript, ONNX format, OpenVINO format, TensorRT format, CoreML format, TF SavedModel format, PaddlePaddle format, Tencent ncnn format +description: Step-by-step guide on exporting your YOLOv8 models to various format like ONNX, TensorRT, CoreML and more for deployment. Explore now!. +keywords: YOLO, YOLOv8, Ultralytics, Model export, ONNX, TensorRT, CoreML, TensorFlow SavedModel, OpenVINO, PyTorch, export model --- diff --git a/docs/modes/index.md b/docs/modes/index.md index 5a00afa..9cfe6dc 100644 --- a/docs/modes/index.md +++ b/docs/modes/index.md @@ -1,7 +1,7 @@ --- comments: true -description: Use Ultralytics YOLOv8 Modes (Train, Val, Predict, Export, Track, Benchmark) to train, validate, predict, track, export or benchmark. -keywords: yolov8, yolo, ultralytics, training, validation, prediction, export, tracking, benchmarking, real-time object detection, object tracking +description: From training to tracking, make the most of YOLOv8 with Ultralytics. Get insights and examples for each supported mode including validation, export, and benchmarking. +keywords: Ultralytics, YOLOv8, Machine Learning, Object Detection, Training, Validation, Prediction, Export, Tracking, Benchmarking --- # Ultralytics YOLOv8 Modes diff --git a/docs/modes/predict.md b/docs/modes/predict.md index 7a6bf82..02117c3 100644 --- a/docs/modes/predict.md +++ b/docs/modes/predict.md @@ -1,7 +1,7 @@ --- comments: true -description: Get started with YOLOv8 Predict mode and input sources. Accepts various input sources such as images, videos, and directories. -keywords: YOLOv8, predict mode, generator, streaming mode, input sources, video formats, arguments customization +description: Discover how to use YOLOv8 predict mode for various tasks. Learn about different inference sources like images, videos, and data formats. +keywords: Ultralytics, YOLOv8, predict mode, inference sources, prediction tasks, streaming mode, image processing, video processing, machine learning, AI --- diff --git a/docs/modes/track.md b/docs/modes/track.md index e0266b9..9c50d85 100644 --- a/docs/modes/track.md +++ b/docs/modes/track.md @@ -1,7 +1,7 @@ --- comments: true -description: Explore YOLOv8n-based object tracking with Ultralytics' BoT-SORT and ByteTrack. Learn configuration, usage, and customization tips. -keywords: object tracking, YOLO, trackers, BoT-SORT, ByteTrack +description: Learn how to use Ultralytics YOLO for object tracking in video streams. Guides to use different trackers and customise tracker configurations. +keywords: Ultralytics, YOLO, object tracking, video streams, BoT-SORT, ByteTrack, Python guide, CLI guide --- diff --git a/docs/modes/train.md b/docs/modes/train.md index 16c32ef..89b1b9c 100644 --- a/docs/modes/train.md +++ b/docs/modes/train.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn how to train custom YOLOv8 models on various datasets, configure hyperparameters, and use Ultralytics' YOLO for seamless training. -keywords: YOLOv8, train mode, train a custom YOLOv8 model, hyperparameters, train a model, Comet, ClearML, TensorBoard, logging, loggers +description: Step-by-step guide to train YOLOv8 models with Ultralytics YOLO with examples of single-GPU and multi-GPU training. Efficient way for object detection training. +keywords: Ultralytics, YOLOv8, YOLO, object detection, train mode, custom dataset, GPU training, multi-GPU, hyperparameters, CLI examples, Python examples --- diff --git a/docs/modes/val.md b/docs/modes/val.md index 4ffff73..8ec6fc5 100644 --- a/docs/modes/val.md +++ b/docs/modes/val.md @@ -1,7 +1,7 @@ --- comments: true -description: Validate and improve YOLOv8n model accuracy on COCO128 and other datasets using hyperparameter & configuration tuning, in Val mode. -keywords: Ultralytics, YOLO, YOLOv8, Val, Validation, Hyperparameters, Performance, Accuracy, Generalization, COCO, Export Formats, PyTorch +description: 'Guide for Validating YOLOv8 Models: Learn how to evaluate the performance of your YOLO models using validation settings and metrics with Python and CLI examples.' +keywords: Ultralytics, YOLO Docs, YOLOv8, validation, model evaluation, hyperparameters, accuracy, metrics, Python, CLI --- diff --git a/docs/quickstart.md b/docs/quickstart.md index cd8d630..a910983 100644 --- a/docs/quickstart.md +++ b/docs/quickstart.md @@ -1,7 +1,7 @@ --- comments: true -description: Install and use YOLOv8 via CLI or Python. Run single-line commands or integrate with Python projects for object detection, segmentation, and classification. -keywords: YOLOv8, object detection, segmentation, classification, pip, git, CLI, Python +description: Explore various methods to install Ultralytics using pip, conda, git and Docker. Learn how to use Ultralytics with command line interface or within your Python projects. +keywords: Ultralytics installation, pip install Ultralytics, Docker install Ultralytics, Ultralytics command line interface, Ultralytics Python interface --- ## Install Ultralytics diff --git a/docs/reference/cfg/__init__.md b/docs/reference/cfg/__init__.md index a30308c..e400d20 100644 --- a/docs/reference/cfg/__init__.md +++ b/docs/reference/cfg/__init__.md @@ -1,3 +1,8 @@ +--- +description: Explore Ultralytics cfg functions like cfg2dict, handle_deprecation, merge_equal_args & more to handle YOLO settings and configurations efficiently. +keywords: Ultralytics, YOLO, Configuration, cfg2dict, handle_deprecation, merge_equals_args, handle_yolo_settings, copy_default_cfg, Image Detection +--- + ## cfg2dict --- ### ::: ultralytics.cfg.cfg2dict @@ -41,4 +46,4 @@ ## copy_default_cfg --- ### ::: ultralytics.cfg.copy_default_cfg -

+

\ No newline at end of file diff --git a/docs/reference/data/annotator.md b/docs/reference/data/annotator.md index 6a58074..11fbd16 100644 --- a/docs/reference/data/annotator.md +++ b/docs/reference/data/annotator.md @@ -1,4 +1,9 @@ +--- +description: Enhance your machine learning model with Ultralytics’ auto_annotate function. Simplify data annotation for improved model training. +keywords: Ultralytics, Auto-Annotate, Machine Learning, AI, Annotation, Data Processing, Model Training +--- + ## auto_annotate --- ### ::: ultralytics.data.annotator.auto_annotate -

+

\ No newline at end of file diff --git a/docs/reference/data/augment.md b/docs/reference/data/augment.md index a3dbfea..c6c6498 100644 --- a/docs/reference/data/augment.md +++ b/docs/reference/data/augment.md @@ -1,3 +1,8 @@ +--- +description: Detailed exploration into Ultralytics data augmentation methods including BaseTransform, MixUp, LetterBox, ToTensor, and more for enhancing model performance. +keywords: Ultralytics, Data Augmentation, BaseTransform, MixUp, RandomHSV, LetterBox, Albumentations, classify_transforms, classify_albumentations +--- + ## BaseTransform --- ### ::: ultralytics.data.augment.BaseTransform @@ -91,4 +96,4 @@ ## classify_albumentations --- ### ::: ultralytics.data.augment.classify_albumentations -

+

\ No newline at end of file diff --git a/docs/reference/data/base.md b/docs/reference/data/base.md index 65aadce..7336a7a 100644 --- a/docs/reference/data/base.md +++ b/docs/reference/data/base.md @@ -1,4 +1,9 @@ +--- +description: Explore BaseDataset in Ultralytics docs. Learn how this implementation simplifies dataset creation and manipulation. +keywords: Ultralytics, docs, BaseDataset, data manipulation, dataset creation +--- + ## BaseDataset --- ### ::: ultralytics.data.base.BaseDataset -

+

\ No newline at end of file diff --git a/docs/reference/data/build.md b/docs/reference/data/build.md index fa7e271..705972a 100644 --- a/docs/reference/data/build.md +++ b/docs/reference/data/build.md @@ -1,3 +1,8 @@ +--- +description: Explore the Ultralytics YOLO v3 data build procedures, including the InfiniteDataLoader, seed_worker, build_dataloader, and load_inference_source. +keywords: Ultralytics, YOLO v3, Data build, DataLoader, InfiniteDataLoader, seed_worker, build_dataloader, load_inference_source +--- + ## InfiniteDataLoader --- ### ::: ultralytics.data.build.InfiniteDataLoader @@ -31,4 +36,4 @@ ## load_inference_source --- ### ::: ultralytics.data.build.load_inference_source -

+

\ No newline at end of file diff --git a/docs/reference/data/converter.md b/docs/reference/data/converter.md index c38e078..9fbefec 100644 --- a/docs/reference/data/converter.md +++ b/docs/reference/data/converter.md @@ -1,3 +1,8 @@ +--- +description: Explore Ultralytics data converter functions like coco91_to_coco80_class, merge_multi_segment, rle2polygon for efficient data handling. +keywords: Ultralytics, Data Converter, coco91_to_coco80_class, merge_multi_segment, rle2polygon +--- + ## coco91_to_coco80_class --- ### ::: ultralytics.data.converter.coco91_to_coco80_class @@ -26,4 +31,4 @@ ## delete_dsstore --- ### ::: ultralytics.data.converter.delete_dsstore -

+

\ No newline at end of file diff --git a/docs/reference/data/dataset.md b/docs/reference/data/dataset.md index 6d69959..015c934 100644 --- a/docs/reference/data/dataset.md +++ b/docs/reference/data/dataset.md @@ -1,3 +1,8 @@ +--- +description: Explore the YOLODataset and SemanticDataset classes in YOLO data. Learn how to efficiently handle and manipulate your data with Ultralytics. +keywords: Ultralytics, YOLO, YOLODataset, SemanticDataset, data handling, data manipulation +--- + ## YOLODataset --- ### ::: ultralytics.data.dataset.YOLODataset @@ -11,4 +16,4 @@ ## SemanticDataset --- ### ::: ultralytics.data.dataset.SemanticDataset -

+

\ No newline at end of file diff --git a/docs/reference/data/loaders.md b/docs/reference/data/loaders.md index 3c98d8f..e257bc1 100644 --- a/docs/reference/data/loaders.md +++ b/docs/reference/data/loaders.md @@ -1,3 +1,8 @@ +--- +description: Find detailed guides on Ultralytics YOLO data loaders, including LoadStreams, LoadImages and LoadTensor. Learn how to get the best YouTube URLs. +keywords: Ultralytics, data loaders, LoadStreams, LoadImages, LoadTensor, YOLO, YouTube URLs +--- + ## SourceTypes --- ### ::: ultralytics.data.loaders.SourceTypes @@ -36,4 +41,4 @@ ## get_best_youtube_url --- ### ::: ultralytics.data.loaders.get_best_youtube_url -

+

\ No newline at end of file diff --git a/docs/reference/data/utils.md b/docs/reference/data/utils.md index 6d471cc..99a8e76 100644 --- a/docs/reference/data/utils.md +++ b/docs/reference/data/utils.md @@ -1,3 +1,8 @@ +--- +description: Uncover a detailed guide to Ultralytics data utilities. Learn functions from img2label_paths to autosplit, all boosting your YOLO model’s efficiency. +keywords: Ultralytics, data utils, YOLO, img2label_paths, exif_size, polygon2mask, polygons2masks_overlap, check_cls_dataset, delete_dsstore, autosplit +--- + ## HUBDatasetStats --- ### ::: ultralytics.data.utils.HUBDatasetStats @@ -66,4 +71,4 @@ ## autosplit --- ### ::: ultralytics.data.utils.autosplit -

+

\ No newline at end of file diff --git a/docs/reference/engine/exporter.md b/docs/reference/engine/exporter.md index 662f74a..7630669 100644 --- a/docs/reference/engine/exporter.md +++ b/docs/reference/engine/exporter.md @@ -1,3 +1,8 @@ +--- +description: Explore the exporter functionality of Ultralytics. Learn about exporting formats, iOSDetectModel, and try exporting with examples. +keywords: Ultralytics, Exporter, iOSDetectModel, Export Formats, Try export +--- + ## Exporter --- ### ::: ultralytics.engine.exporter.Exporter @@ -26,4 +31,4 @@ ## export --- ### ::: ultralytics.engine.exporter.export -

+

\ No newline at end of file diff --git a/docs/reference/engine/model.md b/docs/reference/engine/model.md index 4343325..c86ba2e 100644 --- a/docs/reference/engine/model.md +++ b/docs/reference/engine/model.md @@ -1,4 +1,9 @@ +--- +description: Explore the detailed guide on using the Ultralytics YOLO Engine Model. Learn better ways to implement, train and evaluate YOLO models. +keywords: Ultralytics, YOLO, engine model, documentation, guide, implementation, training, evaluation +--- + ## YOLO --- ### ::: ultralytics.engine.model.YOLO -

+

\ No newline at end of file diff --git a/docs/reference/engine/predictor.md b/docs/reference/engine/predictor.md index 8c3d3c3..d474060 100644 --- a/docs/reference/engine/predictor.md +++ b/docs/reference/engine/predictor.md @@ -1,4 +1,9 @@ +--- +description: Learn about Ultralytics BasePredictor, an essential component of our engine that serves as the foundation for all prediction operations. +keywords: Ultralytics, BasePredictor, YOLO, prediction, engine +--- + ## BasePredictor --- ### ::: ultralytics.engine.predictor.BasePredictor -

+

\ No newline at end of file diff --git a/docs/reference/engine/results.md b/docs/reference/engine/results.md index ec3a09f..9348338 100644 --- a/docs/reference/engine/results.md +++ b/docs/reference/engine/results.md @@ -1,3 +1,8 @@ +--- +description: Master Ultralytics engine results including base tensors, boxes, and keypoints with our thorough documentation. +keywords: Ultralytics, engine, results, base tensor, boxes, keypoints +--- + ## BaseTensor --- ### ::: ultralytics.engine.results.BaseTensor @@ -26,4 +31,4 @@ ## Probs --- ### ::: ultralytics.engine.results.Probs -

+

\ No newline at end of file diff --git a/docs/reference/engine/trainer.md b/docs/reference/engine/trainer.md index e215a44..89cb689 100644 --- a/docs/reference/engine/trainer.md +++ b/docs/reference/engine/trainer.md @@ -1,4 +1,9 @@ +--- +description: Learn about the BaseTrainer class in the Ultralytics library. From training control, customization to advanced usage. +keywords: Ultralytics, BaseTrainer, Machine Learning, Training Control, Python library +--- + ## BaseTrainer --- ### ::: ultralytics.engine.trainer.BaseTrainer -

+

\ No newline at end of file diff --git a/docs/reference/engine/validator.md b/docs/reference/engine/validator.md index 1927114..5dce001 100644 --- a/docs/reference/engine/validator.md +++ b/docs/reference/engine/validator.md @@ -1,4 +1,9 @@ +--- +description: Learn about the Ultralytics BaseValidator module. Understand its principles, uses, and how it interacts with other components. +keywords: Ultralytics, BaseValidator, Ultralytics engine, module, components +--- + ## BaseValidator --- ### ::: ultralytics.engine.validator.BaseValidator -

+

\ No newline at end of file diff --git a/docs/reference/hub/__init__.md b/docs/reference/hub/__init__.md index 93c9bef..0dc1c3c 100644 --- a/docs/reference/hub/__init__.md +++ b/docs/reference/hub/__init__.md @@ -1,3 +1,8 @@ +--- +description: Explore Ultralytics hub functions for model resetting, checking datasets, model exporting and more. Easy-to-follow instructions provided. +keywords: Ultralytics, hub functions, model export, dataset check, reset model, YOLO Docs +--- + ## login --- ### ::: ultralytics.hub.login @@ -36,4 +41,4 @@ ## check_dataset --- ### ::: ultralytics.hub.check_dataset -

+

\ No newline at end of file diff --git a/docs/reference/hub/auth.md b/docs/reference/hub/auth.md index d293b4c..95375e7 100644 --- a/docs/reference/hub/auth.md +++ b/docs/reference/hub/auth.md @@ -1,4 +1,9 @@ +--- +description: Dive into the Ultralytics Auth API documentation & learn how to manage authentication in your AI & ML projects easily and effectively. +keywords: Ultralytics, Auth, API documentation, User Authentication, AI, Machine Learning +--- + ## Auth --- ### ::: ultralytics.hub.auth.Auth -

+

\ No newline at end of file diff --git a/docs/reference/hub/session.md b/docs/reference/hub/session.md index 6863c5a..9982a03 100644 --- a/docs/reference/hub/session.md +++ b/docs/reference/hub/session.md @@ -1,4 +1,9 @@ +--- +description: Explore details about the HUBTrainingSession in Ultralytics framework. Learn to utilize this functionality for effective model training. +keywords: Ultralytics, HUBTrainingSession, Documentation, Model Training, AI, Machine Learning, YOLO +--- + ## HUBTrainingSession --- ### ::: ultralytics.hub.session.HUBTrainingSession -

+

\ No newline at end of file diff --git a/docs/reference/hub/utils.md b/docs/reference/hub/utils.md index 2d78273..c876ab2 100644 --- a/docs/reference/hub/utils.md +++ b/docs/reference/hub/utils.md @@ -1,3 +1,8 @@ +--- +description: Explore Ultralytics docs for various Events, including "request_with_credentials" and "requests_with_progress". Also, understand the use of the "smart_request". +keywords: Ultralytics, Events, request_with_credentials, smart_request, Ultralytics hub utils, requests_with_progress +--- + ## Events --- ### ::: ultralytics.hub.utils.Events @@ -16,4 +21,4 @@ ## smart_request --- ### ::: ultralytics.hub.utils.smart_request -

+

\ No newline at end of file diff --git a/docs/reference/models/fastsam/model.md b/docs/reference/models/fastsam/model.md index 0dd097c..8c9b805 100644 --- a/docs/reference/models/fastsam/model.md +++ b/docs/reference/models/fastsam/model.md @@ -1,4 +1,9 @@ +--- +description: Learn all about Ultralytics FastSAM model. Dive into our comprehensive guide for seamless integration and efficient model training. +keywords: Ultralytics, FastSAM model, Model documentation, Efficient model training +--- + ## FastSAM --- ### ::: ultralytics.models.fastsam.model.FastSAM -

+

\ No newline at end of file diff --git a/docs/reference/models/fastsam/predict.md b/docs/reference/models/fastsam/predict.md index 59080e7..4f0faf8 100644 --- a/docs/reference/models/fastsam/predict.md +++ b/docs/reference/models/fastsam/predict.md @@ -1,4 +1,9 @@ +--- +description: Get detailed insights about Ultralytics FastSAMPredictor. Learn to predict and optimize your AI models with our properly documented guidelines. +keywords: Ultralytics, FastSAMPredictor, predictive modeling, AI optimization, machine learning, deep learning, Ultralytics documentation +--- + ## FastSAMPredictor --- ### ::: ultralytics.models.fastsam.predict.FastSAMPredictor -

+

\ No newline at end of file diff --git a/docs/reference/models/fastsam/prompt.md b/docs/reference/models/fastsam/prompt.md index a8e4df0..6c116c7 100644 --- a/docs/reference/models/fastsam/prompt.md +++ b/docs/reference/models/fastsam/prompt.md @@ -1,4 +1,9 @@ +--- +description: Learn to effectively utilize FastSAMPrompt model from Ultralytics. Detailed guide to help you get the most out of your machine learning models. +keywords: Ultralytics, FastSAMPrompt, machine learning, model, guide, documentation +--- + ## FastSAMPrompt --- ### ::: ultralytics.models.fastsam.prompt.FastSAMPrompt -

+

\ No newline at end of file diff --git a/docs/reference/models/fastsam/utils.md b/docs/reference/models/fastsam/utils.md index 0b6659a..d6eeee5 100644 --- a/docs/reference/models/fastsam/utils.md +++ b/docs/reference/models/fastsam/utils.md @@ -1,3 +1,8 @@ +--- +description: Learn how to adjust bounding boxes to image borders in Ultralytics models using the bbox_iou utility. Enhance your object detection performance. +keywords: Ultralytics, bounding boxes, Bboxes, image borders, object detection, bbox_iou, model utilities +--- + ## adjust_bboxes_to_image_border --- ### ::: ultralytics.models.fastsam.utils.adjust_bboxes_to_image_border @@ -6,4 +11,4 @@ ## bbox_iou --- ### ::: ultralytics.models.fastsam.utils.bbox_iou -

+

\ No newline at end of file diff --git a/docs/reference/models/fastsam/val.md b/docs/reference/models/fastsam/val.md index b72c06a..e28968d 100644 --- a/docs/reference/models/fastsam/val.md +++ b/docs/reference/models/fastsam/val.md @@ -1,4 +1,9 @@ +--- +description: Learn about FastSAMValidator in Ultralytics models. Comprehensive guide to enhancing AI capabilities with Ultralytics. +keywords: Ultralytics, FastSAMValidator, model, synthetic, AI, machine learning, validation +--- + ## FastSAMValidator --- ### ::: ultralytics.models.fastsam.val.FastSAMValidator -

+

\ No newline at end of file diff --git a/docs/reference/models/nas/model.md b/docs/reference/models/nas/model.md index 48912a3..d4b8e2c 100644 --- a/docs/reference/models/nas/model.md +++ b/docs/reference/models/nas/model.md @@ -1,4 +1,9 @@ +--- +description: Learn how our NAS model operates in Ultralytics. Comprehensive guide with detailed examples. Master the nuances of Ultralytics NAS model. +keywords: Ultralytics, NAS model, NAS guide, machine learning, model documentation +--- + ## NAS --- ### ::: ultralytics.models.nas.model.NAS -

+

\ No newline at end of file diff --git a/docs/reference/models/nas/predict.md b/docs/reference/models/nas/predict.md index e54fb3a..2828009 100644 --- a/docs/reference/models/nas/predict.md +++ b/docs/reference/models/nas/predict.md @@ -1,4 +1,9 @@ +--- +description: Explore Ultralytics NASPredictor. Understand high-level architecture of the model for effective implementation and efficient predictions. +keywords: NASPredictor, Ultralytics, Ultralytics model, model architecture, efficient predictions +--- + ## NASPredictor --- ### ::: ultralytics.models.nas.predict.NASPredictor -

+

\ No newline at end of file diff --git a/docs/reference/models/nas/val.md b/docs/reference/models/nas/val.md index 150ee0a..daf8c01 100644 --- a/docs/reference/models/nas/val.md +++ b/docs/reference/models/nas/val.md @@ -1,4 +1,9 @@ +--- +description: Explore the utilities and functions of the Ultralytics NASValidator. Find out how it benefits allocation and optimization in AI models. +keywords: Ultralytics, NASValidator, models.nas.val.NASValidator, AI models, allocation, optimization +--- + ## NASValidator --- ### ::: ultralytics.models.nas.val.NASValidator -

+

\ No newline at end of file diff --git a/docs/reference/models/rtdetr/model.md b/docs/reference/models/rtdetr/model.md index 3ad8c65..6495901 100644 --- a/docs/reference/models/rtdetr/model.md +++ b/docs/reference/models/rtdetr/model.md @@ -1,4 +1,9 @@ +--- +description: Explore the specifics of using the RTDETR model in Ultralytics. Detailed documentation layered with explanations and examples. +keywords: Ultralytics, RTDETR model, Ultralytics models, object detection, Ultralytics documentation +--- + ## RTDETR --- ### ::: ultralytics.models.rtdetr.model.RTDETR -

+

\ No newline at end of file diff --git a/docs/reference/models/rtdetr/predict.md b/docs/reference/models/rtdetr/predict.md index 9fc8f5a..b353eef 100644 --- a/docs/reference/models/rtdetr/predict.md +++ b/docs/reference/models/rtdetr/predict.md @@ -1,4 +1,9 @@ +--- +description: Learn how to use the RTDETRPredictor model of the Ultralytics package. Detailed documentation, usage instructions, and advice. +keywords: Ultralytics, RTDETRPredictor, model documentation, guide, real-time object detection +--- + ## RTDETRPredictor --- ### ::: ultralytics.models.rtdetr.predict.RTDETRPredictor -

+

\ No newline at end of file diff --git a/docs/reference/models/rtdetr/train.md b/docs/reference/models/rtdetr/train.md index 2c559c6..4826c33 100644 --- a/docs/reference/models/rtdetr/train.md +++ b/docs/reference/models/rtdetr/train.md @@ -1,3 +1,8 @@ +--- +description: Get insights into RTDETRTrainer, a crucial component of Ultralytics for effective model training. Explore detailed documentation at Ultralytics. +keywords: Ultralytics, RTDETRTrainer, model training, Ultralytics models, PyTorch models, neural networks, machine learning, deep learning +--- + ## RTDETRTrainer --- ### ::: ultralytics.models.rtdetr.train.RTDETRTrainer @@ -6,4 +11,4 @@ ## train --- ### ::: ultralytics.models.rtdetr.train.train -

+

\ No newline at end of file diff --git a/docs/reference/models/rtdetr/val.md b/docs/reference/models/rtdetr/val.md index bffdf4c..dab038e 100644 --- a/docs/reference/models/rtdetr/val.md +++ b/docs/reference/models/rtdetr/val.md @@ -1,3 +1,8 @@ +--- +description: Explore RTDETRDataset in Ultralytics Models. Learn about the RTDETRValidator function, understand its usage in real-time object detection. +keywords: Ultralytics, RTDETRDataset, RTDETRValidator, real-time object detection, models documentation +--- + ## RTDETRDataset --- ### ::: ultralytics.models.rtdetr.val.RTDETRDataset @@ -6,4 +11,4 @@ ## RTDETRValidator --- ### ::: ultralytics.models.rtdetr.val.RTDETRValidator -

+

\ No newline at end of file diff --git a/docs/reference/models/sam/amg.md b/docs/reference/models/sam/amg.md index 8a4e56f..aa10d3a 100644 --- a/docs/reference/models/sam/amg.md +++ b/docs/reference/models/sam/amg.md @@ -1,3 +1,8 @@ +--- +description: Explore Ultralytics methods for mask data processing, transformation and encoding. Deepen your understanding of RLE encoding, image cropping and more. +keywords: Ultralytics, Mask Data, Transformation, Encoding, RLE encoding, Image cropping, Pytorch, SAM, AMG, Ultralytics model +--- + ## MaskData --- ### ::: ultralytics.models.sam.amg.MaskData @@ -81,4 +86,4 @@ ## batched_mask_to_box --- ### ::: ultralytics.models.sam.amg.batched_mask_to_box -

+

\ No newline at end of file diff --git a/docs/reference/models/sam/build.md b/docs/reference/models/sam/build.md index 447ffd3..e6f9b03 100644 --- a/docs/reference/models/sam/build.md +++ b/docs/reference/models/sam/build.md @@ -1,3 +1,8 @@ +--- +description: Master building SAM ViT models with Ultralytics. Discover steps to leverage the power of SAM and Vision Transformer sessions. +keywords: Ultralytics, SAM, build sam, vision transformer, vits, build_sam_vit_l, build_sam_vit_b, build_sam +--- + ## build_sam_vit_h --- ### ::: ultralytics.models.sam.build.build_sam_vit_h @@ -26,4 +31,4 @@ ## build_sam --- ### ::: ultralytics.models.sam.build.build_sam -

+

\ No newline at end of file diff --git a/docs/reference/models/sam/model.md b/docs/reference/models/sam/model.md index ed2220d..22d9771 100644 --- a/docs/reference/models/sam/model.md +++ b/docs/reference/models/sam/model.md @@ -1,4 +1,9 @@ +--- +description: Dive into the SAM model details in the Ultralytics YOLO documentation. Understand, implement, and optimize your model use. +keywords: Ultralytics, YOLO, SAM Model, Documentations, Machine Learning, AI, Convolutional neural network +--- + ## SAM --- ### ::: ultralytics.models.sam.model.SAM -

+

\ No newline at end of file diff --git a/docs/reference/models/sam/modules/decoders.md b/docs/reference/models/sam/modules/decoders.md index 3b37aaa..b256cd3 100644 --- a/docs/reference/models/sam/modules/decoders.md +++ b/docs/reference/models/sam/modules/decoders.md @@ -1,3 +1,8 @@ +--- +description: Explore MaskDecoder, a part of the Ultralytics models. Gain insights on how to utilize it effectively in the SAM modules decoders MLP. +keywords: Ultralytics, MaskDecoder, SAM modules, decoders, MLP, YOLO, machine learning, image recognition +--- + ## MaskDecoder --- ### ::: ultralytics.models.sam.modules.decoders.MaskDecoder @@ -6,4 +11,4 @@ ## MLP --- ### ::: ultralytics.models.sam.modules.decoders.MLP -

+

\ No newline at end of file diff --git a/docs/reference/models/sam/modules/encoders.md b/docs/reference/models/sam/modules/encoders.md index 82ade99..9127c69 100644 --- a/docs/reference/models/sam/modules/encoders.md +++ b/docs/reference/models/sam/modules/encoders.md @@ -1,3 +1,8 @@ +--- +description: Discover detailed information on ImageEncoderViT, PositionEmbeddingRandom, Attention, window_partition, get_rel_pos and more in Ultralytics models encoders documentation. +keywords: Ultralytics, Encoders, Modules, Documentation, ImageEncoderViT, PositionEmbeddingRandom, Attention, window_partition, get_rel_pos +--- + ## ImageEncoderViT --- ### ::: ultralytics.models.sam.modules.encoders.ImageEncoderViT @@ -46,4 +51,4 @@ ## add_decomposed_rel_pos --- ### ::: ultralytics.models.sam.modules.encoders.add_decomposed_rel_pos -

+

\ No newline at end of file diff --git a/docs/reference/models/sam/modules/sam.md b/docs/reference/models/sam/modules/sam.md index 9063f5e..719e5ed 100644 --- a/docs/reference/models/sam/modules/sam.md +++ b/docs/reference/models/sam/modules/sam.md @@ -1,4 +1,9 @@ +--- +description: Explore the Sam module of Ultralytics. Discover detailed methods, classes, and information for efficient deep-learning model training!. +keywords: Ultralytics, Sam module, deep learning, model training, Ultralytics documentation +--- + ## Sam --- ### ::: ultralytics.models.sam.modules.sam.Sam -

+

\ No newline at end of file diff --git a/docs/reference/models/sam/modules/tiny_encoder.md b/docs/reference/models/sam/modules/tiny_encoder.md index 813f69a..c0a45f5 100644 --- a/docs/reference/models/sam/modules/tiny_encoder.md +++ b/docs/reference/models/sam/modules/tiny_encoder.md @@ -1,3 +1,8 @@ +--- +description: Get in-depth insights about Ultralytics Tiny Encoder Modules such as Conv2d_BN, MBConv, ConvLayer, Attention, BasicLayer, and TinyViT. Improve your understanding of machine learning model components. +keywords: Ultralytics, Tiny Encoder, Conv2d_BN, MBConv, ConvLayer, Attention, BasicLayer, TinyViT, Machine learning modules, Ultralytics models +--- + ## Conv2d_BN --- ### ::: ultralytics.models.sam.modules.tiny_encoder.Conv2d_BN @@ -51,4 +56,4 @@ ## TinyViT --- ### ::: ultralytics.models.sam.modules.tiny_encoder.TinyViT -

+

\ No newline at end of file diff --git a/docs/reference/models/sam/modules/transformer.md b/docs/reference/models/sam/modules/transformer.md index 70fd497..71f5262 100644 --- a/docs/reference/models/sam/modules/transformer.md +++ b/docs/reference/models/sam/modules/transformer.md @@ -1,3 +1,8 @@ +--- +description: Learn about TwoWayTransformer and Attention modules in Ultralytics. Leverage these tools to enhance your AI models. +keywords: Ultralytics, TwoWayTransformer, Attention, AI models, transformers +--- + ## TwoWayTransformer --- ### ::: ultralytics.models.sam.modules.transformer.TwoWayTransformer @@ -11,4 +16,4 @@ ## Attention --- ### ::: ultralytics.models.sam.modules.transformer.Attention -

+

\ No newline at end of file diff --git a/docs/reference/models/sam/predict.md b/docs/reference/models/sam/predict.md index 038e176..ed9e190 100644 --- a/docs/reference/models/sam/predict.md +++ b/docs/reference/models/sam/predict.md @@ -1,4 +1,9 @@ +--- +description: Master the ultralytics.models.sam.predict.Predictor class with our comprehensive guide. Discover techniques to enhance your model predictions. +keywords: Ultralytics, predictor, models, sam.predict.Predictor, AI, machine learning, predictive models +--- + ## Predictor --- ### ::: ultralytics.models.sam.predict.Predictor -

+

\ No newline at end of file diff --git a/docs/reference/models/utils/loss.md b/docs/reference/models/utils/loss.md index 5b4e016..c3e51a4 100644 --- a/docs/reference/models/utils/loss.md +++ b/docs/reference/models/utils/loss.md @@ -1,3 +1,8 @@ +--- +description: Learn to use the DETRLoss function provided by Ultralytics YOLO. Understand how to utilize loss in RTDETR detection models to improve accuracy. +keywords: Ultralytics, YOLO, Documentation, DETRLoss, Detection Loss, Loss function, DETR, RTDETR Detection Models +--- + ## DETRLoss --- ### ::: ultralytics.models.utils.loss.DETRLoss @@ -6,4 +11,4 @@ ## RTDETRDetectionLoss --- ### ::: ultralytics.models.utils.loss.RTDETRDetectionLoss -

+

\ No newline at end of file diff --git a/docs/reference/models/utils/ops.md b/docs/reference/models/utils/ops.md index ad639b2..ecca6ba 100644 --- a/docs/reference/models/utils/ops.md +++ b/docs/reference/models/utils/ops.md @@ -1,3 +1,8 @@ +--- +description: Discover details for "HungarianMatcher" & "inverse_sigmoid" functions in Ultralytics YOLO, advanced tools supporting detection models. +keywords: Ultralytics, YOLO, HungarianMatcher, inverse_sigmoid, detection models, model utilities, ops +--- + ## HungarianMatcher --- ### ::: ultralytics.models.utils.ops.HungarianMatcher @@ -11,4 +16,4 @@ ## inverse_sigmoid --- ### ::: ultralytics.models.utils.ops.inverse_sigmoid -

+

\ No newline at end of file diff --git a/docs/reference/models/yolo/classify/predict.md b/docs/reference/models/yolo/classify/predict.md index ce1a554..cc344a5 100644 --- a/docs/reference/models/yolo/classify/predict.md +++ b/docs/reference/models/yolo/classify/predict.md @@ -1,3 +1,8 @@ +--- +description: Explore the Ultralytics ClassificationPredictor guide for model prediction and visualization. Build powerful AI models with YOLO. +keywords: Ultralytics, classification predictor, predict, YOLO, AI models, model visualization +--- + ## ClassificationPredictor --- ### ::: ultralytics.models.yolo.classify.predict.ClassificationPredictor @@ -6,4 +11,4 @@ ## predict --- ### ::: ultralytics.models.yolo.classify.predict.predict -

+

\ No newline at end of file diff --git a/docs/reference/models/yolo/classify/train.md b/docs/reference/models/yolo/classify/train.md index 0b505e6..02034f6 100644 --- a/docs/reference/models/yolo/classify/train.md +++ b/docs/reference/models/yolo/classify/train.md @@ -1,3 +1,8 @@ +--- +description: Delve into Classification Trainer at Ultralytics YOLO docs and optimize your model's training process with insights from the masters!. +keywords: Ultralytics, YOLO, Classification Trainer, deep learning, training process, AI models, documentation +--- + ## ClassificationTrainer --- ### ::: ultralytics.models.yolo.classify.train.ClassificationTrainer @@ -6,4 +11,4 @@ ## train --- ### ::: ultralytics.models.yolo.classify.train.train -

+

\ No newline at end of file diff --git a/docs/reference/models/yolo/classify/val.md b/docs/reference/models/yolo/classify/val.md index 20038c5..18a3889 100644 --- a/docs/reference/models/yolo/classify/val.md +++ b/docs/reference/models/yolo/classify/val.md @@ -1,3 +1,8 @@ +--- +description: Explore YOLO ClassificationValidator, a key element of Ultralytics YOLO models. Learn how it validates and fine-tunes model outputs. +keywords: Ultralytics, YOLO, ClassificationValidator, model validation, model fine-tuning, deep learning, computer vision +--- + ## ClassificationValidator --- ### ::: ultralytics.models.yolo.classify.val.ClassificationValidator @@ -6,4 +11,4 @@ ## val --- ### ::: ultralytics.models.yolo.classify.val.val -

+

\ No newline at end of file diff --git a/docs/reference/models/yolo/detect/predict.md b/docs/reference/models/yolo/detect/predict.md index 91b5438..b7e8bf1 100644 --- a/docs/reference/models/yolo/detect/predict.md +++ b/docs/reference/models/yolo/detect/predict.md @@ -1,3 +1,8 @@ +--- +description: Explore the guide to using the DetectionPredictor in Ultralytics YOLO. Learn how to predict, detect and analyze objects accurately. +keywords: Ultralytics, YOLO, DetectionPredictor, detect, predict, object detection, analysis +--- + ## DetectionPredictor --- ### ::: ultralytics.models.yolo.detect.predict.DetectionPredictor @@ -6,4 +11,4 @@ ## predict --- ### ::: ultralytics.models.yolo.detect.predict.predict -

+

\ No newline at end of file diff --git a/docs/reference/models/yolo/detect/train.md b/docs/reference/models/yolo/detect/train.md index a034a7a..1ef7ca8 100644 --- a/docs/reference/models/yolo/detect/train.md +++ b/docs/reference/models/yolo/detect/train.md @@ -1,3 +1,8 @@ +--- +description: Maximize your model's potential with Ultralytics YOLO Detection Trainer. Learn advanced techniques, tips, and tricks for training. +keywords: Ultralytics YOLO, YOLO, Detection Trainer, Model Training, Machine Learning, Deep Learning, Computer Vision +--- + ## DetectionTrainer --- ### ::: ultralytics.models.yolo.detect.train.DetectionTrainer @@ -6,4 +11,4 @@ ## train --- ### ::: ultralytics.models.yolo.detect.train.train -

+

\ No newline at end of file diff --git a/docs/reference/models/yolo/detect/val.md b/docs/reference/models/yolo/detect/val.md index 3ce0496..849d8ab 100644 --- a/docs/reference/models/yolo/detect/val.md +++ b/docs/reference/models/yolo/detect/val.md @@ -1,3 +1,8 @@ +--- +description: Discover function valuation of your YOLO models with the Ultralytics Detection Validator. Enhance precision and recall rates today. +keywords: Ultralytics, YOLO, Detection Validator, model valuation, precision, recall +--- + ## DetectionValidator --- ### ::: ultralytics.models.yolo.detect.val.DetectionValidator @@ -6,4 +11,4 @@ ## val --- ### ::: ultralytics.models.yolo.detect.val.val -

+

\ No newline at end of file diff --git a/docs/reference/models/yolo/pose/predict.md b/docs/reference/models/yolo/pose/predict.md index 589621e..c9952c6 100644 --- a/docs/reference/models/yolo/pose/predict.md +++ b/docs/reference/models/yolo/pose/predict.md @@ -1,3 +1,8 @@ +--- +description: Discover how to use PosePredictor in the Ultralytics YOLO model. Includes detailed guides, code examples, and explanations. +keywords: Ultralytics, YOLO, PosePredictor, machine learning, AI, predictive models +--- + ## PosePredictor --- ### ::: ultralytics.models.yolo.pose.predict.PosePredictor @@ -6,4 +11,4 @@ ## predict --- ### ::: ultralytics.models.yolo.pose.predict.predict -

+

\ No newline at end of file diff --git a/docs/reference/models/yolo/pose/train.md b/docs/reference/models/yolo/pose/train.md index f407029..fc53f7d 100644 --- a/docs/reference/models/yolo/pose/train.md +++ b/docs/reference/models/yolo/pose/train.md @@ -1,3 +1,8 @@ +--- +description: Explore Ultralytics PoseTrainer for YOLO models. Get a step-by-step guide on how to train on custom pose data for more accurate AI modeling. +keywords: Ultralytics, YOLO, PoseTrainer, pose training, AI modeling, custom data training +--- + ## PoseTrainer --- ### ::: ultralytics.models.yolo.pose.train.PoseTrainer @@ -6,4 +11,4 @@ ## train --- ### ::: ultralytics.models.yolo.pose.train.train -

+

\ No newline at end of file diff --git a/docs/reference/models/yolo/pose/val.md b/docs/reference/models/yolo/pose/val.md index 443cb84..6473ad9 100644 --- a/docs/reference/models/yolo/pose/val.md +++ b/docs/reference/models/yolo/pose/val.md @@ -1,3 +1,8 @@ +--- +description: Explore the PoseValidator—review how Ultralytics YOLO validates poses for object detection. Improve your understanding of YOLO. +keywords: PoseValidator, Ultralytics, YOLO, Object detection, Pose validation +--- + ## PoseValidator --- ### ::: ultralytics.models.yolo.pose.val.PoseValidator @@ -6,4 +11,4 @@ ## val --- ### ::: ultralytics.models.yolo.pose.val.val -

+

\ No newline at end of file diff --git a/docs/reference/models/yolo/segment/predict.md b/docs/reference/models/yolo/segment/predict.md index 39b005f..355cc02 100644 --- a/docs/reference/models/yolo/segment/predict.md +++ b/docs/reference/models/yolo/segment/predict.md @@ -1,3 +1,8 @@ +--- +description: Discover how to utilize the YOLO Segmentation Predictor in Ultralytics. Enhance your objects detection skills with us. +keywords: YOLO, Ultralytics, object detection, segmentation predictor +--- + ## SegmentationPredictor --- ### ::: ultralytics.models.yolo.segment.predict.SegmentationPredictor @@ -6,4 +11,4 @@ ## predict --- ### ::: ultralytics.models.yolo.segment.predict.predict -

+

\ No newline at end of file diff --git a/docs/reference/models/yolo/segment/train.md b/docs/reference/models/yolo/segment/train.md index 36822ed..7509214 100644 --- a/docs/reference/models/yolo/segment/train.md +++ b/docs/reference/models/yolo/segment/train.md @@ -1,3 +1,8 @@ +--- +description: Maximize your YOLO model's performance with our SegmentationTrainer. Explore comprehensive guides and tutorials on ultralytics.com. +keywords: Ultralytics, YOLO, SegmentationTrainer, image segmentation, object detection, model training, YOLO model +--- + ## SegmentationTrainer --- ### ::: ultralytics.models.yolo.segment.train.SegmentationTrainer @@ -6,4 +11,4 @@ ## train --- ### ::: ultralytics.models.yolo.segment.train.train -

+

\ No newline at end of file diff --git a/docs/reference/models/yolo/segment/val.md b/docs/reference/models/yolo/segment/val.md index 82afadd..627c76f 100644 --- a/docs/reference/models/yolo/segment/val.md +++ b/docs/reference/models/yolo/segment/val.md @@ -1,3 +1,8 @@ +--- +description: Get practical insights about our SegmentationValidator in YOLO Ultralytics models. Discover functionality details, methods, inputs, and outputs. +keywords: Ultralytics, YOLO, SegmentationValidator, model segmentation, image classification, object detection +--- + ## SegmentationValidator --- ### ::: ultralytics.models.yolo.segment.val.SegmentationValidator @@ -6,4 +11,4 @@ ## val --- ### ::: ultralytics.models.yolo.segment.val.val -

+

\ No newline at end of file diff --git a/docs/reference/nn/autobackend.md b/docs/reference/nn/autobackend.md index 6c4ffd1..4576dbf 100644 --- a/docs/reference/nn/autobackend.md +++ b/docs/reference/nn/autobackend.md @@ -1,3 +1,8 @@ +--- +description: Get to know more about Ultralytics nn.autobackend.check_class_names functionality. Optimize your YOLO models seamlessly. +keywords: Ultralytics, AutoBackend, check_class_names, YOLO, YOLO models, optimization +--- + ## AutoBackend --- ### ::: ultralytics.nn.autobackend.AutoBackend @@ -6,4 +11,4 @@ ## check_class_names --- ### ::: ultralytics.nn.autobackend.check_class_names -

+

\ No newline at end of file diff --git a/docs/reference/nn/modules/block.md b/docs/reference/nn/modules/block.md index 7e30b64..91551aa 100644 --- a/docs/reference/nn/modules/block.md +++ b/docs/reference/nn/modules/block.md @@ -1,3 +1,8 @@ +--- +description: Explore Ultralytics YOLO neural network modules, Proto to BottleneckCSP. Detailed explanation of each module with easy-to-follow code examples. +keywords: YOLO, Ultralytics, neural network, nn.modules.block, Proto, HGBlock, SPPF, C2, C3, RepC3, C3Ghost, Bottleneck, BottleneckCSP +--- + ## DFL --- ### ::: ultralytics.nn.modules.block.DFL @@ -81,4 +86,4 @@ ## BottleneckCSP --- ### ::: ultralytics.nn.modules.block.BottleneckCSP -

+

\ No newline at end of file diff --git a/docs/reference/nn/modules/conv.md b/docs/reference/nn/modules/conv.md index 8823546..c64faf6 100644 --- a/docs/reference/nn/modules/conv.md +++ b/docs/reference/nn/modules/conv.md @@ -1,3 +1,8 @@ +--- +description: Explore various Ultralytics convolution modules including Conv2, DWConv, ConvTranspose, GhostConv, Channel Attention and more. +keywords: Ultralytics, Convolution Modules, Conv2, DWConv, ConvTranspose, GhostConv, ChannelAttention, CBAM, autopad +--- + ## Conv --- ### ::: ultralytics.nn.modules.conv.Conv @@ -66,4 +71,4 @@ ## autopad --- ### ::: ultralytics.nn.modules.conv.autopad -

+

\ No newline at end of file diff --git a/docs/reference/nn/modules/head.md b/docs/reference/nn/modules/head.md index 7f055e8..74a3a87 100644 --- a/docs/reference/nn/modules/head.md +++ b/docs/reference/nn/modules/head.md @@ -1,3 +1,8 @@ +--- +description: Explore docs covering Ultralytics YOLO detection, pose & RTDETRDecoder. Comprehensive guides to help you understand Ultralytics nn modules. +keywords: Ultralytics, YOLO, Detection, Pose, RTDETRDecoder, nn modules, guides +--- + ## Detect --- ### ::: ultralytics.nn.modules.head.Detect @@ -21,4 +26,4 @@ ## RTDETRDecoder --- ### ::: ultralytics.nn.modules.head.RTDETRDecoder -

+

\ No newline at end of file diff --git a/docs/reference/nn/modules/transformer.md b/docs/reference/nn/modules/transformer.md index 918178a..ebdb8ee 100644 --- a/docs/reference/nn/modules/transformer.md +++ b/docs/reference/nn/modules/transformer.md @@ -1,3 +1,8 @@ +--- +description: Learn about Ultralytics transformer encoder, layer, MLP block, LayerNorm2d and the deformable transformer decoder layer. Expand your understanding of these crucial AI modules. +keywords: Ultralytics, Ultralytics documentation, TransformerEncoderLayer, TransformerLayer, MLPBlock, LayerNorm2d, DeformableTransformerDecoderLayer +--- + ## TransformerEncoderLayer --- ### ::: ultralytics.nn.modules.transformer.TransformerEncoderLayer @@ -46,4 +51,4 @@ ## DeformableTransformerDecoder --- ### ::: ultralytics.nn.modules.transformer.DeformableTransformerDecoder -

+

\ No newline at end of file diff --git a/docs/reference/nn/modules/utils.md b/docs/reference/nn/modules/utils.md index 740f58d..fabb9ba 100644 --- a/docs/reference/nn/modules/utils.md +++ b/docs/reference/nn/modules/utils.md @@ -1,3 +1,8 @@ +--- +description: Explore Ultralytics neural network utils, such as bias_init_with_prob, inverse_sigmoid and multi_scale_deformable_attn_pytorch functions. +keywords: Ultralytics, neural network, nn.modules.utils, bias_init_with_prob, inverse_sigmoid, multi_scale_deformable_attn_pytorch +--- + ## _get_clones --- ### ::: ultralytics.nn.modules.utils._get_clones @@ -21,4 +26,4 @@ ## multi_scale_deformable_attn_pytorch --- ### ::: ultralytics.nn.modules.utils.multi_scale_deformable_attn_pytorch -

+

\ No newline at end of file diff --git a/docs/reference/nn/tasks.md b/docs/reference/nn/tasks.md index 8285fa4..d96af09 100644 --- a/docs/reference/nn/tasks.md +++ b/docs/reference/nn/tasks.md @@ -1,3 +1,8 @@ +--- +description: Explore Ultralytics YOLO docs to understand task-specific models like DetectionModel, PoseModel, RTDETRDetectionModel and more. Plus, learn about ensemble, model loading. +keywords: Ultralytics, YOLO docs, DetectionModel, SegmentationModel, ClassificationModel, Ensemble, torch_safe_load, yaml_model_load, guess_model_task +--- + ## BaseModel --- ### ::: ultralytics.nn.tasks.BaseModel @@ -71,4 +76,4 @@ ## guess_model_task --- ### ::: ultralytics.nn.tasks.guess_model_task -

+

\ No newline at end of file diff --git a/docs/reference/trackers/basetrack.md b/docs/reference/trackers/basetrack.md index 6118833..f157a78 100644 --- a/docs/reference/trackers/basetrack.md +++ b/docs/reference/trackers/basetrack.md @@ -1,3 +1,8 @@ +--- +description: Get familiar with TrackState in Ultralytics. Learn how it is used in the BaseTrack of the Ultralytics tracker for enhanced functionality. +keywords: Ultralytics, TrackState, BaseTrack, Ultralytics tracker, Ultralytics documentation +--- + ## TrackState --- ### ::: ultralytics.trackers.basetrack.TrackState @@ -6,4 +11,4 @@ ## BaseTrack --- ### ::: ultralytics.trackers.basetrack.BaseTrack -

+

\ No newline at end of file diff --git a/docs/reference/trackers/bot_sort.md b/docs/reference/trackers/bot_sort.md index d0dbc69..0e5410a 100644 --- a/docs/reference/trackers/bot_sort.md +++ b/docs/reference/trackers/bot_sort.md @@ -1,3 +1,8 @@ +--- +description: Master the use of Ultralytics BOTrack, a key component of the powerful Ultralytics tracking system. Learn to integrate and use BOTSORT in your projects. +keywords: Ultralytics, BOTSORT, BOTrack, tracking system, official documentation, machine learning, AI tracking +--- + ## BOTrack --- ### ::: ultralytics.trackers.bot_sort.BOTrack @@ -6,4 +11,4 @@ ## BOTSORT --- ### ::: ultralytics.trackers.bot_sort.BOTSORT -

+

\ No newline at end of file diff --git a/docs/reference/trackers/byte_tracker.md b/docs/reference/trackers/byte_tracker.md index f480c5a..b7bac9d 100644 --- a/docs/reference/trackers/byte_tracker.md +++ b/docs/reference/trackers/byte_tracker.md @@ -1,3 +1,8 @@ +--- +description: Step-in to explore in-depth the functionalities of Ultralytics BYTETracker under STrack. Gain advanced feature insights to streamline your operations. +keywords: STrack, Ultralytics, BYTETracker, documentation, Ultralytics tracker, object tracking, YOLO +--- + ## STrack --- ### ::: ultralytics.trackers.byte_tracker.STrack @@ -6,4 +11,4 @@ ## BYTETracker --- ### ::: ultralytics.trackers.byte_tracker.BYTETracker -

+

\ No newline at end of file diff --git a/docs/reference/trackers/track.md b/docs/reference/trackers/track.md index bba3d0a..14cb5c7 100644 --- a/docs/reference/trackers/track.md +++ b/docs/reference/trackers/track.md @@ -1,3 +1,8 @@ +--- +description: Explore Ultralytics documentation on prediction function starters & register trackers. Understand our code & its applications better. +keywords: Ultralytics, YOLO, on predict start, register tracker, prediction functions, documentation +--- + ## on_predict_start --- ### ::: ultralytics.trackers.track.on_predict_start @@ -11,4 +16,4 @@ ## register_tracker --- ### ::: ultralytics.trackers.track.register_tracker -

+

\ No newline at end of file diff --git a/docs/reference/trackers/utils/gmc.md b/docs/reference/trackers/utils/gmc.md index 299458a..63b56f0 100644 --- a/docs/reference/trackers/utils/gmc.md +++ b/docs/reference/trackers/utils/gmc.md @@ -1,4 +1,9 @@ +--- +description: Explore the Ultralytics GMC tool in our comprehensive documentation. Learn how it works, best practices, and implementation advice. +keywords: Ultralytics, GMC utility, Ultralytics documentation, Ultralytics tracker, machine learning tools +--- + ## GMC --- ### ::: ultralytics.trackers.utils.gmc.GMC -

+

\ No newline at end of file diff --git a/docs/reference/trackers/utils/kalman_filter.md b/docs/reference/trackers/utils/kalman_filter.md index 3502d74..cad52ba 100644 --- a/docs/reference/trackers/utils/kalman_filter.md +++ b/docs/reference/trackers/utils/kalman_filter.md @@ -1,3 +1,8 @@ +--- +description: Explore KalmanFilterXYAH, a key component of Ultralytics trackers. Understand its utilities and learn to leverage it in your own projects. +keywords: Ultralytics, KalmanFilterXYAH, tracker, documentation, guide +--- + ## KalmanFilterXYAH --- ### ::: ultralytics.trackers.utils.kalman_filter.KalmanFilterXYAH @@ -6,4 +11,4 @@ ## KalmanFilterXYWH --- ### ::: ultralytics.trackers.utils.kalman_filter.KalmanFilterXYWH -

+

\ No newline at end of file diff --git a/docs/reference/trackers/utils/matching.md b/docs/reference/trackers/utils/matching.md index a90eb12..60e96d8 100644 --- a/docs/reference/trackers/utils/matching.md +++ b/docs/reference/trackers/utils/matching.md @@ -1,3 +1,8 @@ +--- +description: Explore in-depth guidance for using Ultralytics trackers utils matching, including merge_matches, linear_assignment, iou_distance, embedding_distance, fuse_motion, and fuse_score. +keywords: Ultralytics, Trackers Utils, Matching, merge_matches, linear_assignment, iou_distance, embedding_distance, fuse_motion, fuse_score, documentation +--- + ## merge_matches --- ### ::: ultralytics.trackers.utils.matching.merge_matches @@ -56,4 +61,4 @@ ## bbox_ious --- ### ::: ultralytics.trackers.utils.matching.bbox_ious -

+

\ No newline at end of file diff --git a/docs/reference/utils/__init__.md b/docs/reference/utils/__init__.md index bdf9f6d..ec01602 100644 --- a/docs/reference/utils/__init__.md +++ b/docs/reference/utils/__init__.md @@ -1,3 +1,8 @@ +--- +description: Explore the Ultralytics Utils package, with handy functions like colorstr, yaml_save, set_logging & more, designed to enhance your coding experience. +keywords: Ultralytics, Utils, utilitarian functions, colorstr, yaml_save, set_logging, is_kaggle, is_docker, clean_url +--- + ## SimpleClass --- ### ::: ultralytics.utils.SimpleClass @@ -166,4 +171,4 @@ ## url2file --- ### ::: ultralytics.utils.url2file -

+

\ No newline at end of file diff --git a/docs/reference/utils/autobatch.md b/docs/reference/utils/autobatch.md index f23bc20..d708303 100644 --- a/docs/reference/utils/autobatch.md +++ b/docs/reference/utils/autobatch.md @@ -1,3 +1,8 @@ +--- +description: Explore Ultralytics documentation for check_train_batch_size utility in the autobatch module. Understand how it could improve your machine learning process. +keywords: Ultralytics, check_train_batch_size, autobatch, utility, machine learning, documentation +--- + ## check_train_batch_size --- ### ::: ultralytics.utils.autobatch.check_train_batch_size @@ -6,4 +11,4 @@ ## autobatch --- ### ::: ultralytics.utils.autobatch.autobatch -

+

\ No newline at end of file diff --git a/docs/reference/utils/benchmarks.md b/docs/reference/utils/benchmarks.md index 0e1d166..bde28cd 100644 --- a/docs/reference/utils/benchmarks.md +++ b/docs/reference/utils/benchmarks.md @@ -1,3 +1,8 @@ +--- +description: Discover how to profile your models using Ultralytics utilities. Enhance performance, optimize your benchmarks, and learn best practices. +keywords: Ultralytics, ProfileModels, benchmarks, model profiling, performance optimization +--- + ## ProfileModels --- ### ::: ultralytics.utils.benchmarks.ProfileModels @@ -6,4 +11,4 @@ ## benchmark --- ### ::: ultralytics.utils.benchmarks.benchmark -

+

\ No newline at end of file diff --git a/docs/reference/utils/callbacks/base.md b/docs/reference/utils/callbacks/base.md index 350d61a..e832a07 100644 --- a/docs/reference/utils/callbacks/base.md +++ b/docs/reference/utils/callbacks/base.md @@ -1,3 +1,8 @@ +--- +description: Explore how to use the on-train, on-validation, on-pretrain, and on-predict callbacks in Ultralytics. Learn to update params, save models, and add integration callbacks. +keywords: Ultralytics, Callbacks, On-train, On-validation, On-pretrain, On-predict, Parameters update, Model saving, Integration callbacks +--- + ## on_pretrain_routine_start --- ### ::: ultralytics.utils.callbacks.base.on_pretrain_routine_start @@ -131,4 +136,4 @@ ## add_integration_callbacks --- ### ::: ultralytics.utils.callbacks.base.add_integration_callbacks -

+

\ No newline at end of file diff --git a/docs/reference/utils/callbacks/clearml.md b/docs/reference/utils/callbacks/clearml.md index 39ef7cc..7657c34 100644 --- a/docs/reference/utils/callbacks/clearml.md +++ b/docs/reference/utils/callbacks/clearml.md @@ -1,3 +1,8 @@ +--- +description: Uncover the specifics of Ultralytics ClearML callbacks, from pretrain routine start to training end. Boost your ML model performance. +keywords: Ultralytics, clearML, callbacks, pretrain routine start, validation end, train epoch end, training end +--- + ## _log_debug_samples --- ### ::: ultralytics.utils.callbacks.clearml._log_debug_samples @@ -31,4 +36,4 @@ ## on_train_end --- ### ::: ultralytics.utils.callbacks.clearml.on_train_end -

+

\ No newline at end of file diff --git a/docs/reference/utils/callbacks/comet.md b/docs/reference/utils/callbacks/comet.md index 7f18c1a..96f31b1 100644 --- a/docs/reference/utils/callbacks/comet.md +++ b/docs/reference/utils/callbacks/comet.md @@ -1,3 +1,8 @@ +--- +description: Explore comprehensive documentation for utilising Comet Callbacks in Ultralytics. Learn to optimise training, logging, and experiment workflows. +keywords: Ultralytics, Comet Callbacks, Training optimisation, Logging, Experiment Workflows +--- + ## _get_comet_mode --- ### ::: ultralytics.utils.callbacks.comet._get_comet_mode @@ -116,4 +121,4 @@ ## on_train_end --- ### ::: ultralytics.utils.callbacks.comet.on_train_end -

+

\ No newline at end of file diff --git a/docs/reference/utils/callbacks/dvc.md b/docs/reference/utils/callbacks/dvc.md index 3d0fcef..638a085 100644 --- a/docs/reference/utils/callbacks/dvc.md +++ b/docs/reference/utils/callbacks/dvc.md @@ -1,3 +1,8 @@ +--- +description: Browse through Ultralytics YOLO docs to learn about important logging and callback functions used in training and pretraining models. +keywords: Ultralytics, YOLO, callbacks, logger, training, pretraining, machine learning, models +--- + ## _logger_disabled --- ### ::: ultralytics.utils.callbacks.dvc._logger_disabled @@ -46,4 +51,4 @@ ## on_train_end --- ### ::: ultralytics.utils.callbacks.dvc.on_train_end -

+

\ No newline at end of file diff --git a/docs/reference/utils/callbacks/hub.md b/docs/reference/utils/callbacks/hub.md index ec99c01..eb16dd8 100644 --- a/docs/reference/utils/callbacks/hub.md +++ b/docs/reference/utils/callbacks/hub.md @@ -1,3 +1,8 @@ +--- +description: Explore the detailed information on key Ultralytics callbacks such as on_pretrain_routine_end, on_model_save, on_train_start, and on_predict_start. +keywords: Ultralytics, callbacks, on_pretrain_routine_end, on_model_save, on_train_start, on_predict_start, hub, training +--- + ## on_pretrain_routine_end --- ### ::: ultralytics.utils.callbacks.hub.on_pretrain_routine_end @@ -36,4 +41,4 @@ ## on_export_start --- ### ::: ultralytics.utils.callbacks.hub.on_export_start -

+

\ No newline at end of file diff --git a/docs/reference/utils/callbacks/mlflow.md b/docs/reference/utils/callbacks/mlflow.md index 77d11a0..90d2dc0 100644 --- a/docs/reference/utils/callbacks/mlflow.md +++ b/docs/reference/utils/callbacks/mlflow.md @@ -1,3 +1,8 @@ +--- +description: Understand routines at the end of pre-training and training in Ultralytics. Elevate your MLflow callbacks expertise. +keywords: Ultralytics, MLflow, Callbacks, on_pretrain_routine_end, on_train_end, Machine Learning, Training +--- + ## on_pretrain_routine_end --- ### ::: ultralytics.utils.callbacks.mlflow.on_pretrain_routine_end @@ -11,4 +16,4 @@ ## on_train_end --- ### ::: ultralytics.utils.callbacks.mlflow.on_train_end -

+

\ No newline at end of file diff --git a/docs/reference/utils/callbacks/neptune.md b/docs/reference/utils/callbacks/neptune.md index a745c6a..0cdb4b5 100644 --- a/docs/reference/utils/callbacks/neptune.md +++ b/docs/reference/utils/callbacks/neptune.md @@ -1,3 +1,8 @@ +--- +description: Explore exhaustive details about Ultralytics callbacks in Neptune, with specifics about scalar logging, routine start, and more. +keywords: Ultralytics, Neptune callbacks, on_train_epoch_end, on_val_end, _log_plot, _log_images, on_pretrain_routine_start, on_fit_epoch_end, on_train_end +--- + ## _log_scalars --- ### ::: ultralytics.utils.callbacks.neptune._log_scalars @@ -36,4 +41,4 @@ ## on_train_end --- ### ::: ultralytics.utils.callbacks.neptune.on_train_end -

+

\ No newline at end of file diff --git a/docs/reference/utils/callbacks/raytune.md b/docs/reference/utils/callbacks/raytune.md index 1cb2f90..61cb7a8 100644 --- a/docs/reference/utils/callbacks/raytune.md +++ b/docs/reference/utils/callbacks/raytune.md @@ -1,4 +1,9 @@ +--- +description: Discover the functionality of the on_fit_epoch_end callback in the Ultralytics YOLO framework. Learn how to end an epoch in your deep learning projects. +keywords: Ultralytics, YOLO, on_fit_epoch_end, callbacks, documentation, deep learning, YOLO framework +--- + ## on_fit_epoch_end --- ### ::: ultralytics.utils.callbacks.raytune.on_fit_epoch_end -

+

\ No newline at end of file diff --git a/docs/reference/utils/callbacks/tensorboard.md b/docs/reference/utils/callbacks/tensorboard.md index a22d76b..ba45245 100644 --- a/docs/reference/utils/callbacks/tensorboard.md +++ b/docs/reference/utils/callbacks/tensorboard.md @@ -1,3 +1,8 @@ +--- +description: Explore Ultralytics YOLO Docs for a deep understanding of log_scalars, on_batch_end & other callback utilities embedded in the tensorboard module. +keywords: Ultralytics, YOLO, documentation, callback utilities, log_scalars, on_batch_end, tensorboard +--- + ## _log_scalars --- ### ::: ultralytics.utils.callbacks.tensorboard._log_scalars @@ -16,4 +21,4 @@ ## on_fit_epoch_end --- ### ::: ultralytics.utils.callbacks.tensorboard.on_fit_epoch_end -

+

\ No newline at end of file diff --git a/docs/reference/utils/callbacks/wb.md b/docs/reference/utils/callbacks/wb.md index 87ff134..e9eac55 100644 --- a/docs/reference/utils/callbacks/wb.md +++ b/docs/reference/utils/callbacks/wb.md @@ -1,3 +1,8 @@ +--- +description: Deep dive into Ultralytics callbacks. Learn how to use the _log_plots, on_fit_epoch_end, and on_train_end functions effectively. +keywords: Ultralytics, callbacks, _log_plots, on_fit_epoch_end, on_train_end +--- + ## _log_plots --- ### ::: ultralytics.utils.callbacks.wb._log_plots @@ -21,4 +26,4 @@ ## on_train_end --- ### ::: ultralytics.utils.callbacks.wb.on_train_end -

+

\ No newline at end of file diff --git a/docs/reference/utils/checks.md b/docs/reference/utils/checks.md index bf79ed7..65a55c5 100644 --- a/docs/reference/utils/checks.md +++ b/docs/reference/utils/checks.md @@ -1,3 +1,8 @@ +--- +description: Learn about our routine checks that safeguard Ultralytics operations including ASCII, font, YOLO file, YAML, Python and torchvision checks. +keywords: Ultralytics, utility checks, ASCII, check_version, pip_update, check_python, check_torchvision, check_yaml, YOLO filename +--- + ## is_ascii --- ### ::: ultralytics.utils.checks.is_ascii @@ -86,4 +91,4 @@ ## print_args --- ### ::: ultralytics.utils.checks.print_args -

+

\ No newline at end of file diff --git a/docs/reference/utils/dist.md b/docs/reference/utils/dist.md index c5122a3..c3020a9 100644 --- a/docs/reference/utils/dist.md +++ b/docs/reference/utils/dist.md @@ -1,3 +1,8 @@ +--- +description: Discover the role of dist.find_free_network_port & dist.generate_ddp_command in Ultralytics DDP utilities. Use our guide for efficient deployment. +keywords: Ultralytics, DDP, DDP utility functions, Distributed Data Processing, find free network port, generate DDP command +--- + ## find_free_network_port --- ### ::: ultralytics.utils.dist.find_free_network_port @@ -16,4 +21,4 @@ ## ddp_cleanup --- ### ::: ultralytics.utils.dist.ddp_cleanup -

+

\ No newline at end of file diff --git a/docs/reference/utils/downloads.md b/docs/reference/utils/downloads.md index 8f9da2b..dba1f57 100644 --- a/docs/reference/utils/downloads.md +++ b/docs/reference/utils/downloads.md @@ -1,3 +1,8 @@ +--- +description: Learn about the download utilities in Ultralytics YOLO, featuring functions like is_url, check_disk_space, get_github_assets, and download. +keywords: Ultralytics, YOLO, download utilities, is_url, check_disk_space, get_github_assets, download, documentation +--- + ## is_url --- ### ::: ultralytics.utils.downloads.is_url @@ -31,4 +36,4 @@ ## download --- ### ::: ultralytics.utils.downloads.download -

+

\ No newline at end of file diff --git a/docs/reference/utils/errors.md b/docs/reference/utils/errors.md index a508c79..6842c4e 100644 --- a/docs/reference/utils/errors.md +++ b/docs/reference/utils/errors.md @@ -1,4 +1,9 @@ +--- +description: Learn about the HUBModelError in Ultralytics. Enhance your understanding, troubleshoot errors and optimize your machine learning projects. +keywords: Ultralytics, HUBModelError, Machine Learning, Error troubleshooting, Ultralytics documentation +--- + ## HUBModelError --- ### ::: ultralytics.utils.errors.HUBModelError -

+

\ No newline at end of file diff --git a/docs/reference/utils/files.md b/docs/reference/utils/files.md index 0143b5f..31f63d7 100644 --- a/docs/reference/utils/files.md +++ b/docs/reference/utils/files.md @@ -1,3 +1,8 @@ +--- +description: Discover how to use Ultralytics utility functions for file-related operations including incrementing paths, finding file age, checking file size and creating directories. +keywords: Ultralytics, utility functions, file operations, working directory, file age, file size, create directories +--- + ## WorkingDirectory --- ### ::: ultralytics.utils.files.WorkingDirectory @@ -31,4 +36,4 @@ ## make_dirs --- ### ::: ultralytics.utils.files.make_dirs -

+

\ No newline at end of file diff --git a/docs/reference/utils/instance.md b/docs/reference/utils/instance.md index 03771c3..64922ec 100644 --- a/docs/reference/utils/instance.md +++ b/docs/reference/utils/instance.md @@ -1,3 +1,8 @@ +--- +description: Dive into Ultralytics detailed utility guide. Learn about Bboxes, _ntuple and more from Ultralytics utils.instance module. +keywords: Ultralytics, Bboxes, _ntuple, utility, ultralytics utils.instance +--- + ## Bboxes --- ### ::: ultralytics.utils.instance.Bboxes @@ -11,4 +16,4 @@ ## _ntuple --- ### ::: ultralytics.utils.instance._ntuple -

+

\ No newline at end of file diff --git a/docs/reference/utils/loss.md b/docs/reference/utils/loss.md index 164db8a..b55b881 100644 --- a/docs/reference/utils/loss.md +++ b/docs/reference/utils/loss.md @@ -1,3 +1,8 @@ +--- +description: Explore Ultralytics' versatile loss functions - VarifocalLoss, BboxLoss, v8DetectionLoss, v8PoseLoss. Improve your accuracy on YOLO implementations. +keywords: Ultralytics, Loss functions, VarifocalLoss, BboxLoss, v8DetectionLoss, v8PoseLoss, YOLO, Ultralytics Documentation +--- + ## VarifocalLoss --- ### ::: ultralytics.utils.loss.VarifocalLoss @@ -36,4 +41,4 @@ ## v8ClassificationLoss --- ### ::: ultralytics.utils.loss.v8ClassificationLoss -

+

\ No newline at end of file diff --git a/docs/reference/utils/metrics.md b/docs/reference/utils/metrics.md index 4c7764a..788a34f 100644 --- a/docs/reference/utils/metrics.md +++ b/docs/reference/utils/metrics.md @@ -1,3 +1,8 @@ +--- +description: Explore Ultralytics YOLO metrics tools - from confusion matrix, detection metrics, pose metrics to box IOU. Learn how to compute and plot precision-recall curves. +keywords: Ultralytics, YOLO, YOLOv3, YOLOv4, metrics, confusion matrix, detection metrics, pose metrics, box IOU, mask IOU, plot precision-recall curves, compute average precision +--- + ## ConfusionMatrix --- ### ::: ultralytics.utils.metrics.ConfusionMatrix @@ -86,4 +91,4 @@ ## ap_per_class --- ### ::: ultralytics.utils.metrics.ap_per_class -

+

\ No newline at end of file diff --git a/docs/reference/utils/ops.md b/docs/reference/utils/ops.md index 0ed015a..fa272d5 100644 --- a/docs/reference/utils/ops.md +++ b/docs/reference/utils/ops.md @@ -1,3 +1,8 @@ +--- +description: Explore detailed documentation for Ultralytics utility operations. Learn about methods like segment2box, make_divisible, clip_boxes, and many more. +keywords: Ultralytics YOLO, Utility Operations, segment2box, make_divisible, clip_boxes, scale_image, xywh2xyxy, xyxy2xywhn, xywh2ltwh, ltwh2xywh, segments2boxes, crop_mask, process_mask, scale_masks, masks2segments +--- + ## Profile --- ### ::: ultralytics.utils.ops.Profile @@ -136,4 +141,4 @@ ## clean_str --- ### ::: ultralytics.utils.ops.clean_str -

+

\ No newline at end of file diff --git a/docs/reference/utils/patches.md b/docs/reference/utils/patches.md index 30ccb2b..fae2cc7 100644 --- a/docs/reference/utils/patches.md +++ b/docs/reference/utils/patches.md @@ -1,3 +1,8 @@ +--- +description: Learn about Ultralytics utils patches including imread, imshow and torch_save. Enhance your image processing skills. +keywords: Ultralytics, Utils, Patches, imread, imshow, torch_save, image processing +--- + ## imread --- ### ::: ultralytics.utils.patches.imread @@ -16,4 +21,4 @@ ## torch_save --- ### ::: ultralytics.utils.patches.torch_save -

+

\ No newline at end of file diff --git a/docs/reference/utils/plotting.md b/docs/reference/utils/plotting.md index fb641da..9497689 100644 --- a/docs/reference/utils/plotting.md +++ b/docs/reference/utils/plotting.md @@ -1,3 +1,8 @@ +--- +description: Master advanced plotting utils from Ultralytics including color annotations, label and image plotting, and feature visualization. +keywords: Ultralytics, plotting, utils, color annotation, label plotting, image plotting, feature visualization +--- + ## Colors --- ### ::: ultralytics.utils.plotting.Colors @@ -36,4 +41,4 @@ ## feature_visualization --- ### ::: ultralytics.utils.plotting.feature_visualization -

+

\ No newline at end of file diff --git a/docs/reference/utils/tal.md b/docs/reference/utils/tal.md index 99dc543..641ea97 100644 --- a/docs/reference/utils/tal.md +++ b/docs/reference/utils/tal.md @@ -1,3 +1,8 @@ +--- +description: Explore Ultralytics utilities for optimized task assignment, bounding box creation, and distance calculation. Learn more about algorithm implementations. +keywords: Ultralytics, task aligned assigner, select highest overlaps, make anchors, dist2bbox, bbox2dist, utilities, algorithm +--- + ## TaskAlignedAssigner --- ### ::: ultralytics.utils.tal.TaskAlignedAssigner @@ -26,4 +31,4 @@ ## bbox2dist --- ### ::: ultralytics.utils.tal.bbox2dist -

+

\ No newline at end of file diff --git a/docs/reference/utils/torch_utils.md b/docs/reference/utils/torch_utils.md index 2117cd9..cf93c50 100644 --- a/docs/reference/utils/torch_utils.md +++ b/docs/reference/utils/torch_utils.md @@ -1,3 +1,8 @@ +--- +description: Explore Ultralytics-tailored torch utility features like Model EMA, early stopping, smart inference, image scaling, get_flops, and many more. +keywords: Ultralytics, Torch Utils, Model EMA, Early Stopping, Smart Inference, Get CPU Info, Time Sync, Fuse Deconv and bn, Get num params, Get FLOPs, Scale img, Copy attr, Intersect dicts, De_parallel, Init seeds, Profile +--- + ## ModelEMA --- ### ::: ultralytics.utils.torch_utils.ModelEMA @@ -131,4 +136,4 @@ ## profile --- ### ::: ultralytics.utils.torch_utils.profile -

+

\ No newline at end of file diff --git a/docs/reference/utils/tuner.md b/docs/reference/utils/tuner.md index 40263c5..f5310cc 100644 --- a/docs/reference/utils/tuner.md +++ b/docs/reference/utils/tuner.md @@ -1,4 +1,9 @@ +--- +description: Learn to utilize the run_ray_tune function with Ultralytics. Make your machine learning tuning process easier and more efficient. +keywords: Ultralytics, run_ray_tune, machine learning tuning, machine learning efficiency +--- + ## run_ray_tune --- ### ::: ultralytics.utils.tuner.run_ray_tune -

+

\ No newline at end of file diff --git a/docs/tasks/classify.md b/docs/tasks/classify.md index d0a6349..ae0a424 100644 --- a/docs/tasks/classify.md +++ b/docs/tasks/classify.md @@ -1,7 +1,7 @@ --- comments: true -description: Check YOLO class label with only one class for the whole image, using image classification. Get strategies for training and validation models. -keywords: YOLOv8n-cls, image classification, pretrained models +description: Learn about YOLOv8 Classify models for image classification. Get detailed information on List of Pretrained Models & how to Train, Validate, Predict & Export models. +keywords: Ultralytics, YOLOv8, Image Classification, Pretrained Models, YOLOv8n-cls, Training, Validation, Prediction, Model Export --- Image classification is the simplest of the three tasks and involves classifying an entire image into one of a set of @@ -178,4 +178,4 @@ i.e. `yolo predict model=yolov8n-cls.onnx`. Usage examples are shown for your mo | [PaddlePaddle](https://github.com/PaddlePaddle) | `paddle` | `yolov8n-cls_paddle_model/` | ✅ | `imgsz` | | [ncnn](https://github.com/Tencent/ncnn) | `ncnn` | `yolov8n-cls_ncnn_model/` | ✅ | `imgsz`, `half` | -See full `export` details in the [Export](https://docs.ultralytics.com/modes/export/) page. +See full `export` details in the [Export](https://docs.ultralytics.com/modes/export/) page. \ No newline at end of file diff --git a/docs/tasks/detect.md b/docs/tasks/detect.md index 5c2dd07..e649872 100644 --- a/docs/tasks/detect.md +++ b/docs/tasks/detect.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn how to use YOLOv8, an object detection model pre-trained with COCO and about the different YOLOv8 models and how to train and export them. -keywords: object detection, YOLOv8 Detect models, COCO dataset, models, train, predict, export +description: Official documentation for YOLOv8 by Ultralytics. Learn how to train, validate, predict and export models in various formats. Including detailed performance stats. +keywords: YOLOv8, Ultralytics, object detection, pretrained models, training, validation, prediction, export models, COCO, ImageNet, PyTorch, ONNX, CoreML --- Object detection is a task that involves identifying the location and class of objects in an image or video stream. @@ -169,4 +169,4 @@ Available YOLOv8 export formats are in the table below. You can predict or valid | [PaddlePaddle](https://github.com/PaddlePaddle) | `paddle` | `yolov8n_paddle_model/` | ✅ | `imgsz` | | [ncnn](https://github.com/Tencent/ncnn) | `ncnn` | `yolov8n_ncnn_model/` | ✅ | `imgsz`, `half` | -See full `export` details in the [Export](https://docs.ultralytics.com/modes/export/) page. +See full `export` details in the [Export](https://docs.ultralytics.com/modes/export/) page. \ No newline at end of file diff --git a/docs/tasks/index.md b/docs/tasks/index.md index 23e384b..111635a 100644 --- a/docs/tasks/index.md +++ b/docs/tasks/index.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn how Ultralytics YOLOv8 AI framework supports detection, segmentation, classification, and pose/keypoint estimation tasks. -keywords: YOLOv8, computer vision, detection, segmentation, classification, pose, keypoint detection, image segmentation, medical imaging +description: Learn about the cornerstone computer vision tasks YOLOv8 can perform including detection, segmentation, classification, and pose estimation. Understand their uses in your AI projects. +keywords: Ultralytics, YOLOv8, Detection, Segmentation, Classification, Pose Estimation, AI Framework, Computer Vision Tasks --- # Ultralytics YOLOv8 Tasks diff --git a/docs/tasks/pose.md b/docs/tasks/pose.md index 9eeabed..062c554 100644 --- a/docs/tasks/pose.md +++ b/docs/tasks/pose.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn how to use YOLOv8 pose estimation models to identify the position of keypoints on objects in an image, and how to train, validate, predict, and export these models for use with various formats such as ONNX or CoreML. -keywords: YOLOv8, Pose Models, Keypoint Detection, COCO dataset, COCO val2017, Amazon EC2 P4d, PyTorch +description: Learn how to use Ultralytics YOLOv8 for pose estimation tasks. Find pretrained models, learn how to train, validate, predict, and export your own. +keywords: Ultralytics, YOLO, YOLOv8, pose estimation, keypoints detection, object detection, pre-trained models, machine learning, artificial intelligence --- Pose estimation is a task that involves identifying the location of specific points in an image, usually referred @@ -183,4 +183,4 @@ i.e. `yolo predict model=yolov8n-pose.onnx`. Usage examples are shown for your m | [PaddlePaddle](https://github.com/PaddlePaddle) | `paddle` | `yolov8n-pose_paddle_model/` | ✅ | `imgsz` | | [ncnn](https://github.com/Tencent/ncnn) | `ncnn` | `yolov8n-pose_ncnn_model/` | ✅ | `imgsz`, `half` | -See full `export` details in the [Export](https://docs.ultralytics.com/modes/export/) page. +See full `export` details in the [Export](https://docs.ultralytics.com/modes/export/) page. \ No newline at end of file diff --git a/docs/tasks/segment.md b/docs/tasks/segment.md index 413ec7f..5fca146 100644 --- a/docs/tasks/segment.md +++ b/docs/tasks/segment.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn what Instance segmentation is. Get pretrained YOLOv8 segment models, and how to train and export them to segments masks. Check the preformance metrics! -keywords: instance segmentation, YOLOv8, Ultralytics, pretrained models, train, predict, export, datasets +description: Learn how to use instance segmentation models with Ultralytics YOLO. Instructions on training, validation, image prediction, and model export. +keywords: yolov8, instance segmentation, Ultralytics, COCO dataset, image segmentation, object detection, model training, model validation, image prediction, model export --- Instance segmentation goes a step further than object detection and involves identifying individual objects in an image @@ -183,4 +183,4 @@ i.e. `yolo predict model=yolov8n-seg.onnx`. Usage examples are shown for your mo | [PaddlePaddle](https://github.com/PaddlePaddle) | `paddle` | `yolov8n-seg_paddle_model/` | ✅ | `imgsz` | | [ncnn](https://github.com/Tencent/ncnn) | `ncnn` | `yolov8n-seg_ncnn_model/` | ✅ | `imgsz`, `half` | -See full `export` details in the [Export](https://docs.ultralytics.com/modes/export/) page. +See full `export` details in the [Export](https://docs.ultralytics.com/modes/export/) page. \ No newline at end of file diff --git a/docs/usage/callbacks.md b/docs/usage/callbacks.md index ddaccbc..c379e23 100644 --- a/docs/usage/callbacks.md +++ b/docs/usage/callbacks.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn how to leverage callbacks in Ultralytics YOLO framework to perform custom tasks in trainer, validator, predictor and exporter modes. -keywords: callbacks, Ultralytics framework, Trainer, Validator, Predictor, Exporter, train, val, export, predict, YOLO, Object Detection +description: Learn how to utilize callbacks in the Ultralytics framework during train, val, export, and predict modes for enhanced functionality. +keywords: Ultralytics, YOLO, callbacks guide, training callback, validation callback, export callback, prediction callback --- ## Callbacks diff --git a/docs/usage/cfg.md b/docs/usage/cfg.md index 7d54176..8c2957c 100644 --- a/docs/usage/cfg.md +++ b/docs/usage/cfg.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn about YOLO settings and modes for different tasks like detection, segmentation etc. Train and predict with custom argparse commands. -keywords: YOLO settings, hyperparameters, YOLOv8, Ultralytics, YOLO guide, YOLO commands, YOLO tasks, YOLO modes, YOLO training, YOLO detect, YOLO segment, YOLO classify, YOLO pose, YOLO train, YOLO val, YOLO predict, YOLO export, YOLO track, YOLO benchmark +description: Master YOLOv8 settings and hyperparameters for improved model performance. Learn to use YOLO CLI commands, adjust training settings, and optimize YOLO tasks & modes. +keywords: YOLOv8, settings, hyperparameters, YOLO CLI commands, YOLO tasks, YOLO modes, Ultralytics documentation, model optimization, YOLOv8 training --- YOLO settings and hyperparameters play a critical role in the model's performance, speed, and accuracy. These settings diff --git a/docs/usage/cli.md b/docs/usage/cli.md index 84d9222..dccbb77 100644 --- a/docs/usage/cli.md +++ b/docs/usage/cli.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn how to use YOLOv8 from the Command Line Interface (CLI) through simple, single-line commands with `yolo` without Python code. -keywords: YOLO, CLI, command line interface, detect, segment, classify, train, validate, predict, export, Ultralytics Docs +description: 'Learn how to use Ultralytics YOLO through Command Line: train models, run predictions and exports models to different formats easily using terminal commands.' +keywords: Ultralytics, YOLO, CLI, train, validation, prediction, command line interface, YOLO CLI, YOLO terminal, model training, prediction, exporting --- # Command Line Interface Usage diff --git a/docs/usage/engine.md b/docs/usage/engine.md index 0ce8574..7aabaad 100644 --- a/docs/usage/engine.md +++ b/docs/usage/engine.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn how to train and customize your models fast with the Ultralytics YOLO 'DetectionTrainer' and 'CustomTrainer'. Read more here! -keywords: Ultralytics, YOLO, DetectionTrainer, BaseTrainer, engine components, trainers, customizing, callbacks, validators, predictors +description: Discover how to customize and extend base Ultralytics YOLO Trainer engines. Support your custom model and dataloader by overriding built-in functions. +keywords: Ultralytics, YOLO, trainer engines, BaseTrainer, DetectionTrainer, customizing trainers, extending trainers, custom model, custom dataloader --- Both the Ultralytics YOLO command-line and python interfaces are simply a high-level abstraction on the base engine diff --git a/docs/usage/hyperparameter_tuning.md b/docs/usage/hyperparameter_tuning.md index 1b25ade..df5e7ae 100644 --- a/docs/usage/hyperparameter_tuning.md +++ b/docs/usage/hyperparameter_tuning.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn to integrate hyperparameter tuning using Ray Tune with Ultralytics YOLOv8, and optimize your model's performance efficiently. -keywords: yolov8, ray tune, hyperparameter tuning, hyperparameter optimization, machine learning, computer vision, deep learning, image recognition +description: Discover how to streamline hyperparameter tuning for YOLOv8 models with Ray Tune. Learn to accelerate tuning, integrate with Weights & Biases, and analyze results. +keywords: Ultralytics, YOLOv8, Ray Tune, hyperparameter tuning, machine learning optimization, Weights & Biases integration, result analysis --- # Efficient Hyperparameter Tuning with Ray Tune and YOLOv8 @@ -166,4 +166,4 @@ plt.show() In this documentation, we covered common workflows to analyze the results of experiments run with Ray Tune using Ultralytics. The key steps include loading the experiment results from a directory, performing basic experiment-level and trial-level analysis and plotting metrics. -Explore further by looking into Ray Tune’s [Analyze Results](https://docs.ray.io/en/latest/tune/examples/tune_analyze_results.html) docs page to get the most out of your hyperparameter tuning experiments. +Explore further by looking into Ray Tune’s [Analyze Results](https://docs.ray.io/en/latest/tune/examples/tune_analyze_results.html) docs page to get the most out of your hyperparameter tuning experiments. \ No newline at end of file diff --git a/docs/usage/python.md b/docs/usage/python.md index 7fc30e8..1e9dffe 100644 --- a/docs/usage/python.md +++ b/docs/usage/python.md @@ -1,7 +1,7 @@ --- comments: true -description: Integrate YOLOv8 in Python. Load, use pretrained models, train, and infer images. Export to ONNX. Track objects in videos. -keywords: yolov8, python usage, object detection, segmentation, classification, pretrained models, train models, image predictions +description: Boost your Python projects with object detection, segmentation and classification using YOLOv8. Explore how to load, train, validate, predict, export, track and benchmark models with ease. +keywords: YOLOv8, Ultralytics, Python, object detection, segmentation, classification, model training, validation, prediction, model export, benchmark, real-time tracking --- # Python Usage diff --git a/docs/yolov5/environments/aws_quickstart_tutorial.md b/docs/yolov5/environments/aws_quickstart_tutorial.md index 3e3ea83..42679bc 100644 --- a/docs/yolov5/environments/aws_quickstart_tutorial.md +++ b/docs/yolov5/environments/aws_quickstart_tutorial.md @@ -1,7 +1,7 @@ --- comments: true -description: Get started with YOLOv5 on AWS. Our comprehensive guide provides everything you need to know to run YOLOv5 on an Amazon Deep Learning instance. -keywords: YOLOv5, AWS, Deep Learning, Instance, Guide, Quickstart +description: Step-by-step guide to run YOLOv5 on AWS Deep Learning instance. Learn how to create an instance, connect to it and train, validate and deploy models. +keywords: AWS, YOLOv5, instance, deep learning, Ultralytics, guide, training, deployment, object detection --- # YOLOv5 🚀 on AWS Deep Learning Instance: A Comprehensive Guide diff --git a/docs/yolov5/environments/docker_image_quickstart_tutorial.md b/docs/yolov5/environments/docker_image_quickstart_tutorial.md index b2b90c9..27c2e9f 100644 --- a/docs/yolov5/environments/docker_image_quickstart_tutorial.md +++ b/docs/yolov5/environments/docker_image_quickstart_tutorial.md @@ -1,7 +1,7 @@ --- comments: true -description: Get started with YOLOv5 in a Docker container. Learn to set up and run YOLOv5 models and explore other quickstart options. 🚀 -keywords: YOLOv5, Docker, tutorial, setup, training, testing, detection +description: Learn how to set up and run YOLOv5 in a Docker container. This tutorial includes the prerequisites and step-by-step instructions. +keywords: YOLOv5, Docker, Ultralytics, Image Detection, YOLOv5 Docker Image, Docker Container, Machine Learning, AI --- # Get Started with YOLOv5 🚀 in Docker diff --git a/docs/yolov5/environments/google_cloud_quickstart_tutorial.md b/docs/yolov5/environments/google_cloud_quickstart_tutorial.md index c834a18..2fe407d 100644 --- a/docs/yolov5/environments/google_cloud_quickstart_tutorial.md +++ b/docs/yolov5/environments/google_cloud_quickstart_tutorial.md @@ -1,7 +1,7 @@ --- comments: true -description: Set up YOLOv5 on a Google Cloud Platform (GCP) Deep Learning VM. Train, test, detect, and export YOLOv5 models. Tutorial updated April 2023. -keywords: YOLOv5, GCP, deep learning, tutorial, Google Cloud Platform, virtual machine, VM, setup, free credit, Colab Notebook, AWS, Docker +description: Step-by-step tutorial on how to set up and run YOLOv5 on Google Cloud Platform Deep Learning VM. Perfect guide for beginners and GCP new users!. +keywords: YOLOv5, Google Cloud Platform, GCP, Deep Learning VM, Ultralytics --- # Run YOLOv5 🚀 on Google Cloud Platform (GCP) Deep Learning Virtual Machine (VM) ⭐ diff --git a/docs/yolov5/index.md b/docs/yolov5/index.md index 74f8fee..b1a40b1 100644 --- a/docs/yolov5/index.md +++ b/docs/yolov5/index.md @@ -1,7 +1,7 @@ --- comments: true -description: Explore the extensive functionalities of the YOLOv5 object detection model, renowned for its speed and precision. Dive into our comprehensive guide for installation, architectural insights, use-cases, and more to unlock the full potential of YOLOv5 for your computer vision applications. -keywords: ultralytics, yolov5, object detection, deep learning, pytorch, computer vision, tutorial, architecture, documentation, frameworks, real-time, model training, multicore, multithreading +description: Deep dive into Ultralytics' YOLOv5. Learn about object detection model - YOLOv5, how to train it on custom data, multi-GPU training and more. +keywords: Ultralytics, YOLOv5, Deep Learning, Object detection, PyTorch, Tutorial, Multi-GPU training, Custom data training --- # Comprehensive Guide to Ultralytics YOLOv5 diff --git a/docs/yolov5/quickstart_tutorial.md b/docs/yolov5/quickstart_tutorial.md index e46091f..7a6d801 100644 --- a/docs/yolov5/quickstart_tutorial.md +++ b/docs/yolov5/quickstart_tutorial.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn how to quickly start using YOLOv5 including installation, inference, and training on this Ultralytics Docs page. -keywords: YOLOv5, object detection, PyTorch, quickstart, detect.py, training, Ultralytics Docs +description: Kickstart your journey with YOLOv5. Learn how to install, run inference, and train models on your own images. Dive headfirst into object detection with PyTorch. +keywords: YOLOv5, Quickstart, Installation, Inference, Training, Object detection, PyTorch, Ultralytics --- # YOLOv5 Quickstart diff --git a/docs/yolov5/tutorials/architecture_description.md b/docs/yolov5/tutorials/architecture_description.md index 26a2d91..7ba0cb8 100644 --- a/docs/yolov5/tutorials/architecture_description.md +++ b/docs/yolov5/tutorials/architecture_description.md @@ -1,7 +1,7 @@ --- comments: true -description: Explore the details of Ultralytics YOLOv5 architecture, a comprehensive guide to its model structure, data augmentation techniques, training strategies, and various features. Understand the intricacies of object detection algorithms and improve your skills in the machine learning field. -keywords: yolov5 architecture, data augmentation, training strategies, object detection, yolo docs, ultralytics +description: Explore the architecture of YOLOv5, an object detection algorithm by Ultralytics. Understand the model structure, data augmentation methods, training strategies, and loss computation techniques. +keywords: Ultralytics, YOLOv5, Object Detection, Architecture, Model Structure, Data Augmentation, Training Strategies, Loss Computation --- # Ultralytics YOLOv5 Architecture diff --git a/docs/yolov5/tutorials/clearml_logging_integration.md b/docs/yolov5/tutorials/clearml_logging_integration.md index 3d8672d..6c1c5da 100644 --- a/docs/yolov5/tutorials/clearml_logging_integration.md +++ b/docs/yolov5/tutorials/clearml_logging_integration.md @@ -1,7 +1,7 @@ --- comments: true -description: Integrate ClearML with YOLOv5 to track experiments and manage data versions. Optimize hyperparameters and remotely monitor your runs. -keywords: YOLOv5, ClearML, experiment manager, remotely train, monitor, hyperparameter optimization, data versioning tool, HPO, data version management, optimization locally, agent, training progress, custom YOLOv5, AI development, model building +description: Learn how ClearML can enhance your YOLOv5 pipeline – track your training runs, version your data, remotely monitor your models and optimize performance. +keywords: ClearML, YOLOv5, Ultralytics, AI toolbox, training data, remote training, hyperparameter optimization, YOLOv5 model --- # ClearML Integration diff --git a/docs/yolov5/tutorials/comet_logging_integration.md b/docs/yolov5/tutorials/comet_logging_integration.md index 263f146..6ca7b17 100644 --- a/docs/yolov5/tutorials/comet_logging_integration.md +++ b/docs/yolov5/tutorials/comet_logging_integration.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn how to use YOLOv5 with Comet, a tool for logging and visualizing machine learning model metrics in real-time. Install, log and analyze seamlessly. -keywords: object detection, YOLOv5, Comet, model metrics, deep learning, image classification, Colab notebook, machine learning, datasets, hyperparameters tracking, training script, checkpoint +description: Learn how to set up and use Comet to enhance your YOLOv5 model training, metrics tracking and visualization. Includes a step by step guide to integrate Comet with YOLOv5. +keywords: YOLOv5, Comet, Machine Learning, Ultralytics, Real time metrics tracking, Hyperparameters, Model checkpoints, Model predictions, YOLOv5 training, Comet Credentials --- diff --git a/docs/yolov5/tutorials/hyperparameter_evolution.md b/docs/yolov5/tutorials/hyperparameter_evolution.md index 8134b36..e8a078f 100644 --- a/docs/yolov5/tutorials/hyperparameter_evolution.md +++ b/docs/yolov5/tutorials/hyperparameter_evolution.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn to find optimum YOLOv5 hyperparameters via **evolution**. A guide to learn hyperparameter tuning with Genetic Algorithms. -keywords: YOLOv5, Hyperparameter Evolution, Genetic Algorithm, Hyperparameter Optimization, Fitness, Evolve, Visualize +description: Learn how to optimize YOLOv5 with hyperparameter evolution using Genetic Algorithm. This guide provides steps to initialize, define, evolve and visualize hyperparameters for top performance. +keywords: Ultralytics, YOLOv5, Hyperparameter Optimization, Genetic Algorithm, Machine Learning, Deep Learning, AI, Object Detection, Image Classification, Python --- 📚 This guide explains **hyperparameter evolution** for YOLOv5 🚀. Hyperparameter evolution is a method of [Hyperparameter Optimization](https://en.wikipedia.org/wiki/Hyperparameter_optimization) using a [Genetic Algorithm](https://en.wikipedia.org/wiki/Genetic_algorithm) (GA) for optimization. UPDATED 25 September 2022. diff --git a/docs/yolov5/tutorials/model_export.md b/docs/yolov5/tutorials/model_export.md index 53afd01..77869c9 100644 --- a/docs/yolov5/tutorials/model_export.md +++ b/docs/yolov5/tutorials/model_export.md @@ -1,7 +1,7 @@ --- comments: true -description: Export YOLOv5 models to TFLite, ONNX, CoreML, and TensorRT formats. Achieve up to 5x GPU speedup using TensorRT. Benchmarks included. -keywords: YOLOv5, object detection, export, ONNX, CoreML, TensorFlow, TensorRT, OpenVINO +description: Learn how to export a trained YOLOv5 model from PyTorch to different formats including TorchScript, ONNX, OpenVINO, TensorRT, and CoreML, and how to use these models. +keywords: Ultralytics, YOLOv5, model export, PyTorch, TorchScript, ONNX, OpenVINO, TensorRT, CoreML, TensorFlow --- # TFLite, ONNX, CoreML, TensorRT Export diff --git a/docs/yolov5/tutorials/model_pruning_and_sparsity.md b/docs/yolov5/tutorials/model_pruning_and_sparsity.md index 25e4f8c..e3fb1c3 100644 --- a/docs/yolov5/tutorials/model_pruning_and_sparsity.md +++ b/docs/yolov5/tutorials/model_pruning_and_sparsity.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn how to apply pruning to your YOLOv5 models. See the before and after performance with an explanation of sparsity and more. -keywords: YOLOv5, ultralytics, pruning, deep learning, computer vision, object detection, AI, tutorial +description: Improve YOLOv5 model efficiency by pruning with Ultralytics. Understand the process, conduct tests and view the impact on accuracy and sparsity. Test-maintained API environments. +keywords: YOLOv5, YOLO, Ultralytics, model pruning, PyTorch, machine learning, deep learning, computer vision, object detection --- 📚 This guide explains how to apply **pruning** to YOLOv5 🚀 models. diff --git a/docs/yolov5/tutorials/multi_gpu_training.md b/docs/yolov5/tutorials/multi_gpu_training.md index 24221db..91d010e 100644 --- a/docs/yolov5/tutorials/multi_gpu_training.md +++ b/docs/yolov5/tutorials/multi_gpu_training.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn how to train your dataset on single or multiple machines using YOLOv5 on multiple GPUs. Use simple commands with DDP mode for faster performance. -keywords: ultralytics, yolo, yolov5, multi-gpu, training, dataset, dataloader, data parallel, distributed data parallel, docker, pytorch +description: Learn how to train datasets on single or multiple GPUs using YOLOv5. Includes setup, training modes and result profiling for efficient leveraging of multiple GPUs. +keywords: YOLOv5, multi-GPU Training, YOLOv5 training, deep learning, machine learning, object detection, Ultralytics --- 📚 This guide explains how to properly use **multiple** GPUs to train a dataset with YOLOv5 🚀 on single or multiple machine(s). diff --git a/docs/yolov5/tutorials/neural_magic_pruning_quantization.md b/docs/yolov5/tutorials/neural_magic_pruning_quantization.md index 839f7ef..efddec2 100644 --- a/docs/yolov5/tutorials/neural_magic_pruning_quantization.md +++ b/docs/yolov5/tutorials/neural_magic_pruning_quantization.md @@ -1,7 +1,7 @@ --- comments: true -description: Learn how to deploy YOLOv5 with DeepSparse to achieve exceptional CPU performance close to GPUs, using pruning, and quantization.
-keywords: YOLOv5, DeepSparse, Neural Magic, CPU, Production, Performance, Deployments, APIs, SparseZoo, Ultralytics, Model Sparsity, Inference, Open-source, ONNX, Server +description: Explore how to achieve exceptional AI performance with DeepSparse's incredible inference speed. Discover how to deploy YOLOv5, and learn about model sparsification and fine-tuning with SparseML. +keywords: YOLOv5, DeepSparse, Ultralytics, Neural Magic, sparsification, inference runtime, deep learning, deployment, model fine-tuning, SparseML, AI performance, GPU-class performance ---