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Glenn Jocher
2023-07-17 12:40:04 +02:00
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docs/hub/app/android.md
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---
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

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docs/hub/app/index.md
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---
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

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docs/hub/app/ios.md
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---
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

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docs/hub/datasets.md
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---
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)

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docs/hub/index.md
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---
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

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docs/hub/inference_api.md
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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

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docs/hub/models.md
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---
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)

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docs/hub/projects.md
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---
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)