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6
docs/en/hub/api/index.md
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@ -17,13 +17,13 @@ Welcome to the Ultralytics "Under Construction" page! Here, we're hard at work d
This placeholder page is your first stop for upcoming developments. Keep an eye out for:
- **Newsletter:** Subscribe [here](https://ultralytics.com/#newsletter) for the latest news.
- **Newsletter:** Subscribe [here](https://www.ultralytics.com/#newsletter) for the latest news.
- **Social Media:** Follow us [here](https://www.linkedin.com/company/ultralytics) for updates and teasers.
- **Blog:** Visit our [blog](https://ultralytics.com/blog) for detailed insights.
- **Blog:** Visit our [blog](https://www.ultralytics.com/blog) for detailed insights.
## We Value Your Input 🗣️
Your feedback shapes our future releases. Share your thoughts and suggestions [here](https://ultralytics.com/contact).
Your feedback shapes our future releases. Share your thoughts and suggestions [here](https://www.ultralytics.com/contact).
## Thank You, Community! 🌍

16
docs/en/hub/app/android.md
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@ -60,7 +60,7 @@ INT8 (or 8-bit integer) quantization further reduces the model's size and comput
## Delegates and Performance Variability
Different delegates are available on Android devices to accelerate model inference. These delegates include CPU, [GPU](https://www.tensorflow.org/lite/android/delegates/gpu), [Hexagon](https://www.tensorflow.org/lite/android/delegates/hexagon) and [NNAPI](https://www.tensorflow.org/lite/android/delegates/nnapi). The performance of these delegates varies depending on the device's hardware vendor, product line, and specific chipsets used in the device.
Different delegates are available on Android devices to accelerate model inference. These delegates include CPU, [GPU](https://ai.google.dev/edge/litert/android/gpu), [Hexagon](https://developer.android.com/ndk/guides/neuralnetworks/migration-guide) and [NNAPI](https://developer.android.com/ndk/guides/neuralnetworks/migration-guide). The performance of these delegates varies depending on the device's hardware vendor, product line, and specific chipsets used in the device.
1. **CPU**: The default option, with reasonable performance on most devices.
2. **GPU**: Utilizes the device's GPU for faster inference. It can provide a significant performance boost on devices with powerful GPUs.
@ -69,13 +69,13 @@ Different delegates are available on Android devices to accelerate model inferen
Here's a table showing the primary vendors, their product lines, popular devices, and supported delegates:
| Vendor | Product Lines | Popular Devices | Delegates Supported |
| --------------------------------------- | ------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ------------------------ |
| [Qualcomm](https://www.qualcomm.com/) | [Snapdragon (e.g., 800 series)](https://www.qualcomm.com/snapdragon) | [Samsung Galaxy S21](https://www.samsung.com/global/galaxy/galaxy-s21-5g/), [OnePlus 9](https://www.oneplus.com/9), [Google Pixel 6](https://store.google.com/product/pixel_6) | CPU, GPU, Hexagon, NNAPI |
| [Samsung](https://www.samsung.com/) | [Exynos (e.g., Exynos 2100)](https://www.samsung.com/semiconductor/minisite/exynos/) | [Samsung Galaxy S21 (Global version)](https://www.samsung.com/global/galaxy/galaxy-s21-5g/) | CPU, GPU, NNAPI |
| [MediaTek](https://i.mediatek.com/) | [Dimensity (e.g., Dimensity 1200)](https://i.mediatek.com/dimensity-1200) | [Realme GT](https://www.realme.com/global/realme-gt), [Xiaomi Redmi Note](https://www.mi.com/en/phone/redmi/note-list) | CPU, GPU, NNAPI |
| [HiSilicon](https://www.hisilicon.com/) | [Kirin (e.g., Kirin 990)](https://www.hisilicon.com/en/products/Kirin) | [Huawei P40 Pro](https://consumer.huawei.com/en/phones/p40-pro/), [Huawei Mate 30 Pro](https://consumer.huawei.com/en/phones/mate30-pro/) | CPU, GPU, NNAPI |
| [NVIDIA](https://www.nvidia.com/) | [Tegra (e.g., Tegra X1)](https://developer.nvidia.com/content/tegra-x1) | [NVIDIA Shield TV](https://www.nvidia.com/en-us/shield/shield-tv/), [Nintendo Switch](https://www.nintendo.com/switch/) | CPU, GPU, NNAPI |
| Vendor | Product Lines | Popular Devices | Delegates Supported |
| ----------------------------------------- | ------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ------------------------ |
| [Qualcomm](https://www.qualcomm.com/) | [Snapdragon (e.g., 800 series)](https://www.qualcomm.com/snapdragon/overview) | [Samsung Galaxy S21](https://www.samsung.com/global/galaxy/galaxy-s21-5g/), [OnePlus 9](https://www.oneplus.com/9), [Google Pixel 6](https://store.google.com/product/pixel_6) | CPU, GPU, Hexagon, NNAPI |
| [Samsung](https://www.samsung.com/) | [Exynos (e.g., Exynos 2100)](https://www.samsung.com/semiconductor/minisite/exynos/) | [Samsung Galaxy S21 (Global version)](https://www.samsung.com/global/galaxy/galaxy-s21-5g/) | CPU, GPU, NNAPI |
| [MediaTek](https://i.mediatek.com/) | [Dimensity (e.g., Dimensity 1200)](https://i.mediatek.com/dimensity-1200) | [Realme GT](https://www.realme.com/global/realme-gt), [Xiaomi Redmi Note](https://www.mi.com/global/phone/redmi/note-list) | CPU, GPU, NNAPI |
| [HiSilicon](https://www.hisilicon.com/cn) | [Kirin (e.g., Kirin 990)](https://www.hisilicon.com/en/products/Kirin) | [Huawei P40 Pro](https://consumer.huawei.com/en/phones/), [Huawei Mate 30 Pro](https://consumer.huawei.com/en/phones/) | CPU, GPU, NNAPI |
| [NVIDIA](https://www.nvidia.com/) | [Tegra (e.g., Tegra X1)](https://developer.nvidia.com/content/tegra-x1) | [NVIDIA Shield TV](https://www.nvidia.com/en-us/shield/shield-tv/), [Nintendo Switch](https://www.nintendo.com/switch/) | CPU, GPU, NNAPI |
Please note that the list of devices mentioned is not exhaustive and may vary depending on the specific chipsets and device models. Always test your models on your target devices to ensure compatibility and optimal performance.

4
docs/en/hub/cloud-training.md
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@ -6,9 +6,9 @@ keywords: Ultralytics HUB, cloud training, model training, Pro Plan, easy AI set
# Ultralytics HUB Cloud Training
We've listened to the high demand and widespread interest and are thrilled to unveil [Ultralytics HUB](https://ultralytics.com/hub) Cloud Training, offering a single-click training experience for our [Pro](./pro.md) users!
We've listened to the high demand and widespread interest and are thrilled to unveil [Ultralytics HUB](https://www.ultralytics.com/hub) Cloud Training, offering a single-click training experience for our [Pro](./pro.md) users!
[Ultralytics HUB](https://ultralytics.com/hub) [Pro](./pro.md) users can finetune [Ultralytics HUB](https://ultralytics.com/hub) models on a custom dataset using our Cloud Training solution, making the model training process easy. Say goodbye to complex setups and hello to streamlined workflows with [Ultralytics HUB](https://ultralytics.com/hub)'s intuitive interface.
[Ultralytics HUB](https://www.ultralytics.com/hub) [Pro](./pro.md) users can finetune [Ultralytics HUB](https://www.ultralytics.com/hub) models on a custom dataset using our Cloud Training solution, making the model training process easy. Say goodbye to complex setups and hello to streamlined workflows with [Ultralytics HUB](https://www.ultralytics.com/hub)'s intuitive interface.
<p align="center">
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/ie3vLUDNYZo"

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docs/en/hub/datasets.md
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@ -6,7 +6,7 @@ keywords: Ultralytics HUB, datasets, custom datasets, dataset management, model
# Ultralytics HUB Datasets
[Ultralytics HUB](https://ultralytics.com/hub) datasets are a practical solution for managing and leveraging your custom datasets.
[Ultralytics HUB](https://www.ultralytics.com/hub) datasets are a practical solution for managing and leveraging your custom datasets.
Once uploaded, datasets can be immediately utilized for model training. This integrated approach facilitates a seamless transition from dataset management to model training, significantly simplifying the entire process.
@ -22,9 +22,9 @@ Once uploaded, datasets can be immediately utilized for model training. This int
## Upload Dataset
[Ultralytics HUB](https://ultralytics.com/hub) datasets are just like YOLOv5 and YOLOv8 🚀 datasets. They use the same structure and the same label formats to keep everything simple.
[Ultralytics HUB](https://www.ultralytics.com/hub) datasets are just like YOLOv5 and YOLOv8 🚀 datasets. They use the same structure and the same label formats to keep everything simple.
Before you upload a dataset to [Ultralytics HUB](https://ultralytics.com/hub), make sure to **place your dataset YAML file inside the dataset root directory** and that **your dataset YAML, directory and ZIP have the same name**, as shown in the example below, and then zip the dataset directory.
Before you upload a dataset to [Ultralytics HUB](https://www.ultralytics.com/hub), make sure to **place your dataset YAML file inside the dataset root directory** and that **your dataset YAML, directory and ZIP have the same name**, as shown in the example below, and then zip the dataset directory.
For example, if your dataset is called "coco8", as our [COCO8](https://docs.ultralytics.com/datasets/detect/coco8) example dataset, then you should have a `coco8.yaml` inside your `coco8/` directory, which will create a `coco8.zip` when zipped:
@ -46,7 +46,7 @@ The dataset YAML is the same standard YOLOv5 and YOLOv8 YAML format.
--8<-- "ultralytics/cfg/datasets/coco8.yaml"
```
After zipping your dataset, you should [validate it](https://docs.ultralytics.com/reference/hub/__init__/#ultralytics.hub.check_dataset) before uploading it to [Ultralytics HUB](https://ultralytics.com/hub). [Ultralytics HUB](https://ultralytics.com/hub) conducts the dataset validation check post-upload, so by ensuring your dataset is correctly formatted and error-free ahead of time, you can forestall any setbacks due to dataset rejection.
After zipping your dataset, you should [validate it](https://docs.ultralytics.com/reference/hub/__init__/#ultralytics.hub.check_dataset) before uploading it to [Ultralytics HUB](https://www.ultralytics.com/hub). [Ultralytics HUB](https://www.ultralytics.com/hub) conducts the dataset validation check post-upload, so by ensuring your dataset is correctly formatted and error-free ahead of time, you can forestall any setbacks due to dataset rejection.
```py
from ultralytics.hub import check_dataset
@ -68,7 +68,7 @@ This action will trigger the **Upload Dataset** dialog.
Select the dataset task of your dataset and upload it in the _Dataset .zip file_ field.
You have the additional option to set a custom name and description for your [Ultralytics HUB](https://ultralytics.com/hub) dataset.
You have the additional option to set a custom name and description for your [Ultralytics HUB](https://www.ultralytics.com/hub) dataset.
When you're happy with your dataset configuration, click **Upload**.
@ -114,13 +114,13 @@ Navigate to the Dataset page of the dataset you want to download, open the datas
!!! info "Info"
[Ultralytics HUB](https://ultralytics.com/hub)'s sharing functionality provides a convenient way to share datasets with others. This feature is designed to accommodate both existing [Ultralytics HUB](https://ultralytics.com/hub) users and those who have yet to create an account.
[Ultralytics HUB](https://www.ultralytics.com/hub)'s sharing functionality provides a convenient way to share datasets with others. This feature is designed to accommodate both existing [Ultralytics HUB](https://www.ultralytics.com/hub) users and those who have yet to create an account.
!!! note "Note"
You have control over the general access of your datasets.
You can choose to set the general access to "Private", in which case, only you will have access to it. Alternatively, you can set the general access to "Unlisted" which grants viewing access to anyone who has the direct link to the dataset, regardless of whether they have an [Ultralytics HUB](https://ultralytics.com/hub) account or not.
You can choose to set the general access to "Private", in which case, only you will have access to it. Alternatively, you can set the general access to "Unlisted" which grants viewing access to anyone who has the direct link to the dataset, regardless of whether they have an [Ultralytics HUB](https://www.ultralytics.com/hub) account or not.
Navigate to the Dataset page of the dataset you want to share, open the dataset actions dropdown and click on the **Share** option. This action will trigger the **Share Dataset** dialog.

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docs/en/hub/index.md
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@ -26,7 +26,7 @@ keywords: Ultralytics HUB, YOLO models, train YOLO, YOLOv5, YOLOv8, object detec
</div>
👋 Hello from the [Ultralytics](https://ultralytics.com/) Team! We've been working hard these last few months to launch [Ultralytics HUB](https://ultralytics.com/hub), a new web tool for training and deploying all your YOLOv5 and YOLOv8 🚀 models from one spot!
👋 Hello from the [Ultralytics](https://www.ultralytics.com/) Team! We've been working hard these last few months to launch [Ultralytics HUB](https://www.ultralytics.com/hub), a new web tool for training and deploying all your YOLOv5 and YOLOv8 🚀 models from one spot!
We hope that the resources here will help you get the most out of HUB. Please browse the HUB <a href="https://docs.ultralytics.com/">Docs</a> for details, raise an issue on <a href="https://github.com/ultralytics/hub/issues/new/choose">GitHub</a> for support, and join our <a href="https://ultralytics.com/discord">Discord</a> community for questions and discussions!
@ -49,7 +49,7 @@ We hope that the resources here will help you get the most out of HUB. Please br
## Introduction
[Ultralytics HUB](https://ultralytics.com/hub) is designed to be user-friendly and intuitive, allowing users to quickly upload their datasets and train new YOLO models. It also offers a range of pre-trained models to choose from, making it extremely easy for users to get started. Once a model is trained, it can be effortlessly previewed in the [Ultralytics HUB App](app/index.md) before being deployed for real-time classification, object detection, and instance segmentation tasks.
[Ultralytics HUB](https://www.ultralytics.com/hub) is designed to be user-friendly and intuitive, allowing users to quickly upload their datasets and train new YOLO models. It also offers a range of pre-trained models to choose from, making it extremely easy for users to get started. Once a model is trained, it can be effortlessly previewed in the [Ultralytics HUB App](app/index.md) before being deployed for real-time classification, object detection, and instance segmentation tasks.
<p align="center">
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/lveF9iCMIzc?si=_Q4WB5kMB5qNe7q6"
@ -80,9 +80,9 @@ We hope that the resources here will help you get the most out of HUB. Please br
### How do I get started with Ultralytics HUB for training YOLO models?
To get started with [Ultralytics HUB](https://ultralytics.com/hub), follow these steps:
To get started with [Ultralytics HUB](https://www.ultralytics.com/hub), follow these steps:
1. **Sign Up:** Create an account on the [Ultralytics HUB](https://ultralytics.com/hub).
1. **Sign Up:** Create an account on the [Ultralytics HUB](https://www.ultralytics.com/hub).
2. **Upload Dataset:** Navigate to the [Datasets](datasets.md) section to upload your custom dataset.
3. **Train Model:** Go to the [Models](models.md) section and select a pre-trained YOLOv5 or YOLOv8 model to start training.
4. **Deploy Model:** Once trained, preview and deploy your model using the [Ultralytics HUB App](app/index.md) for real-time tasks.
@ -91,7 +91,7 @@ For a detailed guide, refer to the [Quickstart](quickstart.md) page.
### What are the benefits of using Ultralytics HUB over other AI platforms?
[Ultralytics HUB](https://ultralytics.com/hub) offers several unique benefits:
[Ultralytics HUB](https://www.ultralytics.com/hub) offers several unique benefits:
- **User-Friendly Interface:** Intuitive design for easy dataset uploads and model training.
- **Pre-Trained Models:** Access to a variety of pre-trained YOLOv5 and YOLOv8 models.

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docs/en/hub/inference-api.md
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@ -6,7 +6,7 @@ keywords: Ultralytics, HUB, Inference API, Python, cURL, REST API, YOLO, image p
# Ultralytics HUB Inference API
After you [train a model](./models.md#train-model), you can use the [Shared Inference API](#shared-inference-api) for free. If you are a [Pro](./pro.md) user, you can access the [Dedicated Inference API](#dedicated-inference-api). The [Ultralytics HUB](https://ultralytics.com/hub) Inference API allows you to run inference through our REST API without the need to install and set up the Ultralytics YOLO environment locally.
After you [train a model](./models.md#train-model), you can use the [Shared Inference API](#shared-inference-api) for free. If you are a [Pro](./pro.md) user, you can access the [Dedicated Inference API](#dedicated-inference-api). The [Ultralytics HUB](https://www.ultralytics.com/hub) Inference API allows you to run inference through our REST API without the need to install and set up the Ultralytics YOLO environment locally.
![Ultralytics HUB screenshot of the Deploy tab inside the Model page with an arrow pointing to the Dedicated Inference API card and one to the Shared Inference API card](https://github.com/ultralytics/docs/releases/download/0/hub-inference-api-card.avif)
@ -22,7 +22,7 @@ After you [train a model](./models.md#train-model), you can use the [Shared Infe
## Dedicated Inference API
In response to high demand and widespread interest, we are thrilled to unveil the [Ultralytics HUB](https://ultralytics.com/hub) Dedicated Inference API, offering single-click deployment in a dedicated environment for our [Pro](./pro.md) users!
In response to high demand and widespread interest, we are thrilled to unveil the [Ultralytics HUB](https://www.ultralytics.com/hub) Dedicated Inference API, offering single-click deployment in a dedicated environment for our [Pro](./pro.md) users!
!!! note "Note"
@ -33,7 +33,7 @@ In response to high demand and widespread interest, we are thrilled to unveil th
- **High Speed:** Sub-100ms latency is possible for YOLOv8n inference at 640 resolution from nearby regions based on Ultralytics testing.
- **Enhanced Security:** Provides robust security features to protect your data and ensure compliance with industry standards. [Learn more about Google Cloud security](https://cloud.google.com/security).
To use the [Ultralytics HUB](https://ultralytics.com/hub) Dedicated Inference API, click on the **Start Endpoint** button. Next, use the unique endpoint URL as described in the guides below.
To use the [Ultralytics HUB](https://www.ultralytics.com/hub) Dedicated Inference API, click on the **Start Endpoint** button. Next, use the unique endpoint URL as described in the guides below.
![Ultralytics HUB screenshot of the Deploy tab inside the Model page with an arrow pointing to the Start Endpoint button in Dedicated Inference API card](https://github.com/ultralytics/docs/releases/download/0/ultralytics-hub-dedicated-inference-api.avif)
@ -47,7 +47,7 @@ To shut down the dedicated endpoint, click on the **Stop Endpoint** button.
## Shared Inference API
To use the [Ultralytics HUB](https://ultralytics.com/hub) Shared Inference API, follow the guides below.
To use the [Ultralytics HUB](https://www.ultralytics.com/hub) Shared Inference API, follow the guides below.
Free users have the following usage limits:
@ -61,7 +61,7 @@ Free users have the following usage limits:
## Python
To access the [Ultralytics HUB](https://ultralytics.com/hub) Inference API using Python, use the following code:
To access the [Ultralytics HUB](https://www.ultralytics.com/hub) Inference API using Python, use the following code:
```python
import requests
@ -91,7 +91,7 @@ print(response.json())
## cURL
To access the [Ultralytics HUB](https://ultralytics.com/hub) Inference API using cURL, use the following code:
To access the [Ultralytics HUB](https://www.ultralytics.com/hub) Inference API using cURL, use the following code:
```bash
curl -X POST "https://api.ultralytics.com/v1/predict/MODEL_ID" \
@ -121,7 +121,7 @@ See the table below for a full list of available inference arguments.
## Response
The [Ultralytics HUB](https://ultralytics.com/hub) Inference API returns a JSON response.
The [Ultralytics HUB](https://www.ultralytics.com/hub) Inference API returns a JSON response.
### Classification

24
docs/en/hub/integrations.md
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@ -6,29 +6,29 @@ keywords: Ultralytics HUB, Roboflow integration, dataset import, model training,
# Ultralytics HUB Integrations
Learn about [Ultralytics HUB](https://ultralytics.com/hub) integrations with various platforms and formats.
Learn about [Ultralytics HUB](https://www.ultralytics.com/hub) integrations with various platforms and formats.
## Datasets
Seamlessly import your datasets in [Ultralytics HUB](https://ultralytics.com/hub) for [model training](./models.md#train-model).
Seamlessly import your datasets in [Ultralytics HUB](https://www.ultralytics.com/hub) for [model training](./models.md#train-model).
After a dataset is imported in [Ultralytics HUB](https://ultralytics.com/hub), you can [train a model](./models.md#train-model) on your dataset just like you would using the [Ultralytics HUB](https://ultralytics.com/hub) datasets.
After a dataset is imported in [Ultralytics HUB](https://www.ultralytics.com/hub), you can [train a model](./models.md#train-model) on your dataset just like you would using the [Ultralytics HUB](https://www.ultralytics.com/hub) datasets.
### Roboflow
You can easily filter the [Roboflow](https://roboflow.com/?ref=ultralytics) datasets on the [Ultralytics HUB](https://ultralytics.com/hub) [Datasets](https://hub.ultralytics.com/datasets) page.
You can easily filter the [Roboflow](https://roboflow.com/?ref=ultralytics) datasets on the [Ultralytics HUB](https://www.ultralytics.com/hub) [Datasets](https://hub.ultralytics.com/datasets) page.
![Ultralytics HUB screenshot of the Datasets page with Roboflow provider filter](https://github.com/ultralytics/docs/releases/download/0/ultralytics-hub-datasets-page-roboflow-filter.avif)
[Ultralytics HUB](https://ultralytics.com/hub) supports two types of integrations with [Roboflow](https://roboflow.com/?ref=ultralytics), [Universe](#universe) and [Workspace](#workspace).
[Ultralytics HUB](https://www.ultralytics.com/hub) supports two types of integrations with [Roboflow](https://roboflow.com/?ref=ultralytics), [Universe](#universe) and [Workspace](#workspace).
#### Universe
The [Roboflow](https://roboflow.com/?ref=ultralytics) Universe integration allows you to import one dataset at a time into [Ultralytics HUB](https://ultralytics.com/hub) from [Roboflow](https://roboflow.com/?ref=ultralytics).
The [Roboflow](https://roboflow.com/?ref=ultralytics) Universe integration allows you to import one dataset at a time into [Ultralytics HUB](https://www.ultralytics.com/hub) from [Roboflow](https://roboflow.com/?ref=ultralytics).
##### Import
When you export a [Roboflow](https://roboflow.com/?ref=ultralytics) dataset, select the [Ultralytics HUB](https://ultralytics.com/hub) format. This action will redirect you to [Ultralytics HUB](https://ultralytics.com/hub) and trigger the **Dataset Import** dialog.
When you export a [Roboflow](https://roboflow.com/?ref=ultralytics) dataset, select the [Ultralytics HUB](https://www.ultralytics.com/hub) format. This action will redirect you to [Ultralytics HUB](https://www.ultralytics.com/hub) and trigger the **Dataset Import** dialog.
You can import your [Roboflow](https://roboflow.com/?ref=ultralytics) dataset by clicking on the **Import** button.
@ -52,7 +52,7 @@ Navigate to the Dataset page of the [Roboflow](https://roboflow.com/?ref=ultraly
#### Workspace
The [Roboflow](https://roboflow.com/?ref=ultralytics) Workspace integration allows you to import an entire [Roboflow](https://roboflow.com/?ref=ultralytics) Workspace at once into [Ultralytics HUB](https://ultralytics.com/hub).
The [Roboflow](https://roboflow.com/?ref=ultralytics) Workspace integration allows you to import an entire [Roboflow](https://roboflow.com/?ref=ultralytics) Workspace at once into [Ultralytics HUB](https://www.ultralytics.com/hub).
##### Import
@ -66,7 +66,7 @@ Type your [Roboflow](https://roboflow.com/?ref=ultralytics) Workspace private AP
![Ultralytics HUB screenshot of the Integrations page with an arrow pointing to the Integrations button in the sidebar and one to the Add button](https://github.com/ultralytics/docs/releases/download/0/ultralytics-hub-integrations-page.avif)
This will connect your [Ultralytics HUB](https://ultralytics.com/hub) account with your [Roboflow](https://roboflow.com/?ref=ultralytics) Workspace and make your [Roboflow](https://roboflow.com/?ref=ultralytics) datasets available in [Ultralytics HUB](https://ultralytics.com/hub).
This will connect your [Ultralytics HUB](https://www.ultralytics.com/hub) account with your [Roboflow](https://roboflow.com/?ref=ultralytics) Workspace and make your [Roboflow](https://roboflow.com/?ref=ultralytics) datasets available in [Ultralytics HUB](https://www.ultralytics.com/hub).
![Ultralytics HUB screenshot of the Integrations page with an arrow pointing to one of the connected workspaces](https://github.com/ultralytics/docs/releases/download/0/hub-roboflow-workspace-import-2.avif)
@ -114,13 +114,13 @@ The available export formats are presented in the table below.
This integrations page is your first stop for upcoming developments. Keep an eye out with our:
- **Newsletter:** Subscribe [here](https://ultralytics.com/#newsletter) for the latest news.
- **Newsletter:** Subscribe [here](https://www.ultralytics.com/#newsletter) for the latest news.
- **Social Media:** Follow us [here](https://www.linkedin.com/company/ultralytics) for updates and teasers.
- **Blog:** Visit our [blog](https://ultralytics.com/blog) for detailed insights.
- **Blog:** Visit our [blog](https://www.ultralytics.com/blog) for detailed insights.
## We Value Your Input 🗣️
Your feedback shapes our future releases. Share your thoughts and suggestions [here](https://ultralytics.com/survey).
Your feedback shapes our future releases. Share your thoughts and suggestions [here](https://www.ultralytics.com/survey).
## Thank You, Community! 🌍

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docs/en/hub/models.md
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@ -6,9 +6,9 @@ keywords: Ultralytics HUB, YOLOv8, custom AI models, model training, model deplo
# Ultralytics HUB Models
[Ultralytics HUB](https://ultralytics.com/hub) models provide a streamlined solution for training vision AI models on custom datasets.
[Ultralytics HUB](https://www.ultralytics.com/hub) models provide a streamlined solution for training vision AI models on custom datasets.
The process is user-friendly and efficient, involving a simple three-step creation and accelerated training powered by Ultralytics YOLOv8. During training, real-time updates on model metrics are available so that you can monitor each step of the progress. Once training is completed, you can preview your model and easily deploy it to real-world applications. Therefore, [Ultralytics HUB](https://ultralytics.com/hub) offers a comprehensive yet straightforward system for model creation, training, evaluation, and deployment.
The process is user-friendly and efficient, involving a simple three-step creation and accelerated training powered by Ultralytics YOLOv8. During training, real-time updates on model metrics are available so that you can monitor each step of the progress. Once training is completed, you can preview your model and easily deploy it to real-world applications. Therefore, [Ultralytics HUB](https://www.ultralytics.com/hub) offers a comprehensive yet straightforward system for model creation, training, evaluation, and deployment.
<p align="center">
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/YVlkq5H2tAQ"
@ -56,9 +56,9 @@ In this step, you have to choose the project in which you want to create your mo
Ultralytics HUB will try to pre-select the project.
If you opened the **Train Model** dialog as described above, [Ultralytics HUB](https://ultralytics.com/hub) will pre-select the last project you used.
If you opened the **Train Model** dialog as described above, [Ultralytics HUB](https://www.ultralytics.com/hub) will pre-select the last project you used.
If you opened the **Train Model** dialog from the Project page, [Ultralytics HUB](https://ultralytics.com/hub) will pre-select the project you were inside of.
If you opened the **Train Model** dialog from the Project page, [Ultralytics HUB](https://www.ultralytics.com/hub) will pre-select the project you were inside of.
![Ultralytics HUB screenshot of the Project page with an arrow pointing to the Train Model button](https://github.com/ultralytics/docs/releases/download/0/hub-train-model-button.avif)
@ -74,7 +74,7 @@ By default, your model will use a pre-trained model (trained on the [COCO](https
!!! note "Note"
You can easily change the most common model configuration options (such as the number of epochs) but you can also use the **Custom** option to access all [Train Settings](https://docs.ultralytics.com/modes/train/#train-settings) relevant to [Ultralytics HUB](https://ultralytics.com/hub).
You can easily change the most common model configuration options (such as the number of epochs) but you can also use the **Custom** option to access all [Train Settings](https://docs.ultralytics.com/modes/train/#train-settings) relevant to [Ultralytics HUB](https://www.ultralytics.com/hub).
<p align="center">
<br>
@ -103,7 +103,7 @@ In this step, you will start training you model.
![Ultralytics HUB screenshot of the Model page with an arrow pointing to the Start Training card](https://github.com/ultralytics/docs/releases/download/0/hub-cloud-training-model-page-start-training.avif)
[Ultralytics HUB](https://ultralytics.com/hub) offers three training options:
[Ultralytics HUB](https://www.ultralytics.com/hub) offers three training options:
- [Ultralytics Cloud](./cloud-training.md)
- Google Colab
@ -119,7 +119,7 @@ To train models using our [Cloud Training](./cloud-training.md) solution, read t
#### b. Google Colab
To start training your model using [Google Colab](https://colab.research.google.com/github/ultralytics/hub/blob/master/hub.ipynb), follow the instructions shown in the [Ultralytics HUB](https://ultralytics.com/hub) **Train Model** dialog or on the [Google Colab](https://colab.research.google.com/github/ultralytics/hub/blob/master/hub.ipynb) notebook.
To start training your model using [Google Colab](https://colab.research.google.com/github/ultralytics/hub/blob/master/hub.ipynb), follow the instructions shown in the [Ultralytics HUB](https://www.ultralytics.com/hub) **Train Model** dialog or on the [Google Colab](https://colab.research.google.com/github/ultralytics/hub/blob/master/hub.ipynb) notebook.
<a href="https://colab.research.google.com/github/ultralytics/hub/blob/master/hub.ipynb" target="_blank">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab">
@ -151,11 +151,11 @@ When the training starts, you can click **Done** and monitor the training progre
<strong>Watch:</strong> Bring your Own Agent model training using Ultralytics HUB
</p>
To start training your model using your own agent, follow the instructions shown in the [Ultralytics HUB](https://ultralytics.com/hub) **Train Model** dialog.
To start training your model using your own agent, follow the instructions shown in the [Ultralytics HUB](https://www.ultralytics.com/hub) **Train Model** dialog.
![Ultralytics HUB screenshot of the Train Model dialog with arrows pointing to instructions](https://github.com/ultralytics/docs/releases/download/0/ultralytics-hub-train-model-dialog-instructions-1.avif)
Install the `ultralytics` package from [PyPI](https://pypi.org/project/ultralytics).
Install the `ultralytics` package from [PyPI](https://pypi.org/project/ultralytics/).
```bash
pip install -U ultralytics
@ -213,7 +213,7 @@ In the **Test** card, you can select a preview image from the dataset used durin
![Ultralytics HUB screenshot of the Preview tab inside the Model page with an arrow pointing to Camera tab inside the Test card](https://github.com/ultralytics/docs/releases/download/0/ultralytics-hub-preview-camera-tab.avif)
Furthermore, you can preview your model in real-time directly on your [iOS](https://apps.apple.com/xk/app/ultralytics/id1583935240) or [Android](https://play.google.com/store/apps/details?id=com.ultralytics.ultralytics_app) mobile device by [downloading](https://ultralytics.com/app_install) our [Ultralytics HUB App](app/index.md).
Furthermore, you can preview your model in real-time directly on your [iOS](https://apps.apple.com/xk/app/ultralytics/id1583935240) or [Android](https://play.google.com/store/apps/details?id=com.ultralytics.ultralytics_app) mobile device by [downloading](https://www.ultralytics.com/app-install) our [Ultralytics HUB App](app/index.md).
![Ultralytics HUB screenshot of the Deploy tab inside the Model page with arrow pointing to the Real-Time Preview card](https://github.com/ultralytics/docs/releases/download/0/deploy-tab-real-time-preview-card.avif)
@ -243,13 +243,13 @@ Read the [Ultralytics Inference API](./inference-api.md) documentation for more
!!! info "Info"
[Ultralytics HUB](https://ultralytics.com/hub)'s sharing functionality provides a convenient way to share models with others. This feature is designed to accommodate both existing [Ultralytics HUB](https://ultralytics.com/hub) users and those who have yet to create an account.
[Ultralytics HUB](https://www.ultralytics.com/hub)'s sharing functionality provides a convenient way to share models with others. This feature is designed to accommodate both existing [Ultralytics HUB](https://www.ultralytics.com/hub) users and those who have yet to create an account.
??? note "Note"
You have control over the general access of your models.
You can choose to set the general access to "Private", in which case, only you will have access to it. Alternatively, you can set the general access to "Unlisted" which grants viewing access to anyone who has the direct link to the model, regardless of whether they have an [Ultralytics HUB](https://ultralytics.com/hub) account or not.
You can choose to set the general access to "Private", in which case, only you will have access to it. Alternatively, you can set the general access to "Unlisted" which grants viewing access to anyone who has the direct link to the model, regardless of whether they have an [Ultralytics HUB](https://www.ultralytics.com/hub) account or not.
Navigate to the Model page of the model you want to share, open the model actions dropdown and click on the **Share** option. This action will trigger the **Share Model** dialog.

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docs/en/hub/pro.md
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@ -6,7 +6,7 @@ keywords: Ultralytics HUB, Pro Plan, upgrade guide, cloud training, storage, inf
# Ultralytics HUB Pro
[Ultralytics HUB](https://ultralytics.com/hub) offers the Pro Plan as a monthly or annual subscription.
[Ultralytics HUB](https://www.ultralytics.com/hub) offers the Pro Plan as a monthly or annual subscription.
The Pro Plan provides early access to upcoming features and includes enhanced benefits:

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docs/en/hub/projects.md
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@ -6,7 +6,7 @@ keywords: Ultralytics HUB, model management, create project, share project, edit
# Ultralytics HUB Projects
[Ultralytics HUB](https://ultralytics.com/hub) projects provide an effective solution for consolidating and managing your models. If you are working with several models that perform similar tasks or have related purposes, [Ultralytics HUB](https://ultralytics.com/hub) projects allow you to group these models together.
[Ultralytics HUB](https://www.ultralytics.com/hub) projects provide an effective solution for consolidating and managing your models. If you are working with several models that perform similar tasks or have related purposes, [Ultralytics HUB](https://www.ultralytics.com/hub) projects allow you to group these models together.
This creates a unified and organized workspace that facilitates easier model management, comparison and development. Having similar models or various iterations together can facilitate rapid benchmarking, as you can compare their effectiveness. This can lead to faster, more insightful iterative development and refinement of your models.
@ -54,13 +54,13 @@ Next, [train a model](./models.md#train-model) inside your project.
!!! info "Info"
[Ultralytics HUB](https://ultralytics.com/hub)'s sharing functionality provides a convenient way to share projects with others. This feature is designed to accommodate both existing [Ultralytics HUB](https://ultralytics.com/hub) users and those who have yet to create an account.
[Ultralytics HUB](https://www.ultralytics.com/hub)'s sharing functionality provides a convenient way to share projects with others. This feature is designed to accommodate both existing [Ultralytics HUB](https://www.ultralytics.com/hub) users and those who have yet to create an account.
??? note "Note"
You have control over the general access of your projects.
You can choose to set the general access to "Private", in which case, only you will have access to it. Alternatively, you can set the general access to "Unlisted" which grants viewing access to anyone who has the direct link to the project, regardless of whether they have an [Ultralytics HUB](https://ultralytics.com/hub) account or not.
You can choose to set the general access to "Private", in which case, only you will have access to it. Alternatively, you can set the general access to "Unlisted" which grants viewing access to anyone who has the direct link to the project, regardless of whether they have an [Ultralytics HUB](https://www.ultralytics.com/hub) account or not.
Navigate to the Project page of the project you want to share, open the project actions dropdown and click on the **Share** option. This action will trigger the **Share Project** dialog.

6
docs/en/hub/quickstart.md
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@ -6,7 +6,7 @@ keywords: Ultralytics HUB, Quickstart, YOLO models, dataset upload, project mana
# Ultralytics HUB Quickstart
[Ultralytics HUB](https://ultralytics.com/hub) is designed to be user-friendly and intuitive, allowing users to quickly upload their datasets and train new YOLO models. It also offers a range of pre-trained models to choose from, making it extremely easy for users to get started. Once a model is trained, it can be effortlessly previewed in the [Ultralytics HUB App](app/index.md) before being deployed for real-time classification, object detection, and instance segmentation tasks.
[Ultralytics HUB](https://www.ultralytics.com/hub) is designed to be user-friendly and intuitive, allowing users to quickly upload their datasets and train new YOLO models. It also offers a range of pre-trained models to choose from, making it extremely easy for users to get started. Once a model is trained, it can be effortlessly previewed in the [Ultralytics HUB App](app/index.md) before being deployed for real-time classification, object detection, and instance segmentation tasks.
<p align="center">
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/lveF9iCMIzc?si=_Q4WB5kMB5qNe7q6"
@ -20,7 +20,7 @@ keywords: Ultralytics HUB, Quickstart, YOLO models, dataset upload, project mana
## Get Started
[Ultralytics HUB](https://ultralytics.com/hub) offers a variety easy of signup options. You can register and log in using your Google, Apple, or GitHub accounts, or simply with your email address.
[Ultralytics HUB](https://www.ultralytics.com/hub) offers a variety easy of signup options. You can register and log in using your Google, Apple, or GitHub accounts, or simply with your email address.
![Ultralytics HUB screenshot of the Signup page](https://github.com/ultralytics/docs/releases/download/0/ultralytics-hub-signup-page.avif)
@ -36,7 +36,7 @@ During the signup, you will be asked to complete your profile.
## Home
After signing in, you will be directed to the [Home](https://hub.ultralytics.com/home) page of [Ultralytics HUB](https://ultralytics.com/hub), which provides a comprehensive overview, quick links, and updates.
After signing in, you will be directed to the [Home](https://hub.ultralytics.com/home) page of [Ultralytics HUB](https://www.ultralytics.com/hub), which provides a comprehensive overview, quick links, and updates.
The sidebar conveniently offers links to important modules of the platform, such as [Datasets](https://hub.ultralytics.com/datasets), [Projects](https://hub.ultralytics.com/projects), and [Models](https://hub.ultralytics.com/models).

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docs/en/hub/teams.md
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@ -6,7 +6,7 @@ keywords: Ultralytics HUB, Teams, collaboration, team management, AI projects, r
# Ultralytics HUB Teams
We're excited to introduce you to the new Teams feature within [Ultralytics HUB](https://ultralytics.com/hub) for our [Pro](./pro.md) users!
We're excited to introduce you to the new Teams feature within [Ultralytics HUB](https://www.ultralytics.com/hub) for our [Pro](./pro.md) users!
Here, you'll learn how to manage team members, share resources seamlessly, and collaborate efficiently on various projects.