Explore

Ultralytics Platform Explore page showcases public content from the community. Discover datasets and projects for inspiration and learning. The Explore page is accessible to everyone — even without signing in.

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graph LR
    A[🔍 Browse Explore]:::start --> B[📥 Clone to Account]:::proc
    B --> C[✏️ Customize & Annotate]:::proc
    C --> D[🚀 Train Model]:::proc
    D --> E[🌐 Deploy Endpoint]:::out

    classDef start fill:#4CAF50,color:#fff
    classDef proc fill:#2196F3,color:#fff
    classDef out fill:#9C27B0,color:#fff

!!! info "Anonymous Access"

The Explore page works without signing in. Signed-out visitors get **Datasets** and **Models** sections in the sidebar listing official `@ultralytics` content, in place of the **Annotate**, **Train**, and **Deploy** sections that hold your own work. Public models can even be tested in the browser from their `Predict` tab. To clone content or create your own, you'll need to sign up.

Overview

The Explore page features two tabs:

• Public Datasets: Community training data with image previews
• Public Projects: Complete experiments containing trained models

Official Ultralytics content (e.g., @ultralytics projects and datasets) is pinned to the top of results.

Only datasets that contain at least one image and projects that contain at least one model appear on Explore, so empty placeholders never surface in results.

Browse Content

Tabs

The Explore page uses a tabbed interface with Datasets and Projects tabs. Each tab has its own search, sort, and view mode controls.

Search

Each tab has its own search bar. Results update as you type and the query is kept in the URL as ?q=, so a search is easy to bookmark or share.

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Sort and Filter

The dropdown next to the view toggle holds sort options and, on the Datasets tab, filters:

Sorting and filtering are also stored in the URL (dsort, psort, task, and starred), so the browser back button restores the previous result list.

!!! note "Sorting by Stars"

The **Stars** sort shows only datasets with at least one star, so unrated datasets are hidden while it is active.

View Modes

Toggle between three view modes for browsing:

Cards and compact views load more results by infinite scroll. Table view replaces the sort dropdown with sortable column headers and its own pagination controls.

Content Cards

Each item displays:

<!-- screenshot --> === "Project Cards"

| Element         | Description                                                   |
| --------------- | ------------------------------------------------------------- |
| **Icon**        | Project icon with custom color, letter, or cover image        |
| **Name**        | Project title                                                 |
| **Creator**     | Author avatar and username                                    |
| **Description** | Short project description                                     |
| **Star Count**  | Number of community stars (shown when above zero)             |
| **Model Count** | Number of models in the project                               |
| **Size**        | Total storage used by the project's model files               |
| **Updated**     | Date the project last changed                                 |
| **Model Tags**  | Names of the first few models in the project                  |
| **Tags**        | Project tags                                                  |

=== "Dataset Cards"

| Element          | Description                                                       |
| ---------------- | ----------------------------------------------------------------- |
| **Thumbnails**   | Up to four preview images with their annotations drawn on top     |
| **Name**         | Dataset title                                                     |
| **Creator**      | Author avatar and username                                        |
| **Task Badge**   | YOLO task type (detect, segment, etc.)                            |
| **Image Count**  | Number of images, overlaid on the thumbnail strip                 |
| **Star Count**   | Number of community stars (shown when above zero)                 |
| **Class Count**  | Number of classes defined in the dataset                          |
| **Size**         | Total storage used by the dataset                                 |
| **Updated**      | Date the dataset last changed                                     |
| **Class Names**  | First few class names as badges                                   |
| **Tags**         | Dataset tags                                                      |
| **Split Bar**    | Relative sizes of the train, val, and test splits                 |

Use Public Content

graph TD
    A[Find Content on Explore]:::start --> B{Content Type}:::decide
    B --> C[Dataset]:::proc
    B --> D[Project]:::proc
    B --> E[Model]:::proc
    C --> F[Clone Dataset]:::proc
    D --> G[Clone Project]:::proc
    E --> H[Download Model]:::proc
    E --> I[Clone Model]:::proc
    F --> J[Copy in Destination Workspace]:::out
    G --> K[Project Copy with Completed Models]:::out
    H --> L[.pt / Completed Exports]:::out
    I --> M[Copy to Your Project]:::proc
    J --> N[Edit, Annotate, Train]:::out
    K --> N
    M --> N

    classDef start fill:#4CAF50,color:#fff
    classDef proc fill:#2196F3,color:#fff
    classDef decide fill:#FF9800,color:#fff
    classDef out fill:#9C27B0,color:#fff

Clone Dataset

Use a public dataset for your training:

1. Click on the dataset to open its detail page
2. Click Clone Dataset
3. Review the destination workspace, name, visibility, and license
4. Click Clone Dataset to confirm

<!-- screenshot --> !!! note "Cloned Dataset Properties"

- The clone dialog lets you review the destination, name, visibility, and license
- Public datasets stay public by default in workspaces whose default visibility is public; Enterprise workspace clones default to private
- A copyleft source license is carried over and locked, so the clone keeps the terms it was published under
- The destination slug is auto-renamed if the name is already taken in your workspace
- You can modify classes, annotations, and splits
- Changes don't affect the original dataset
- Image bytes reuse content-addressable storage (CAS), but the clone still counts toward the destination workspace's storage quota

See Datasets for managing and annotating your cloned dataset.

Download Model

Download a public model:

1. Click on the model within a project
2. Click the download icon to download its PyTorch .pt weights
3. Open the Export tab to download any completed exports that are available

You can also use the model for inference or as a starting point for fine-tuning:

# Use a downloaded model for inference
yolo predict model=path/to/downloaded-model.pt source=image.jpg

# Fine-tune on your own dataset
yolo train model=path/to/downloaded-model.pt data=my-dataset.yaml epochs=50

Clone Model

Clone a public model to one of your projects:

1. Click on the model within a project
2. Click Clone Model
3. Select a Target Project or create a new one
4. Optionally, rename the model
5. Review the source, destination, and storage summary, then click Clone Model to confirm

<!-- screenshot --> !!! note "Clone vs Download"

**Clone** copies the model to a project on the Platform for further training or deployment. **Download** saves the model file to your local machine.

Clone Project

Copy a public project to your workspace:

1. Click on the project to open its detail page
2. Click Clone Project
3. Review the destination, name, visibility, and license, then click Clone Project

<!-- screenshot --> The cloned project includes completed models that have model files. Deployments and exports are not copied. Its default visibility follows the same workspace rules as dataset cloning.

See Projects for organizing models in your project.

Official Ultralytics Content

Official @ultralytics content is pinned to the top of Explore results. The pinned projects are YOLO26, YOLO11, YOLOv8, and YOLOv5. Open a project to see its current models and supported tasks.

Official datasets include benchmark datasets like coco8 (8-image COCO subset), VOC, african-wildlife, dota8, and other commonly used computer vision datasets.

!!! tip "Quick Start with Official Models"

The fastest way to get started is to clone an official Ultralytics project and use a pretrained model to train on your own dataset:

1. Go to `Explore` > `Projects` tab
2. Find the **YOLO26** project from `@ultralytics`
3. Clone it to your account
4. Upload your dataset in [supported formats](data/datasets.md#preparing-your-dataset) and start training with a pretrained checkpoint

User Profiles

Click on a creator's username to view their public profile at platform.ultralytics.com/{username}. Public profiles show:

<!-- screenshot -->

The Datasets and Projects tabs use the same search, sort, and view controls as the Explore page.

Follow Users

Click the Follow button on any user's profile to follow or unfollow them. Follower counts are displayed on public profiles. The Share button next to it copies a link or opens a pre-filled social post.

Make Your Content Public

Make your work available to the community. Public content appears on the Explore page and is visible to everyone, including users who aren't signed in.

graph LR
    A[Your Private Content]:::start --> B[Click Private Badge]:::proc
    B --> C[Confirm Make Public]:::proc
    C --> D[Appears on Explore Page]:::proc
    D --> E[Community Can Clone/Download]:::out

    classDef start fill:#4CAF50,color:#fff
    classDef proc fill:#2196F3,color:#fff
    classDef out fill:#9C27B0,color:#fff

Make Dataset Public

1. Go to your dataset
2. Click the Private visibility badge in the top navigation bar
3. Review the warning and click Make Public

Make Project Public

1. Go to your project
2. Click the Private visibility badge in the top navigation bar
3. Review the warning and click Make Public

!!! tip "Quality Content"

Before making content public:

- Add a clear, descriptive name and description
- Define class names in the dataset settings
- Verify data quality and annotation accuracy
- Test model performance and include training metrics

!!! warning "Public Content Visibility"

Public content is visible to **everyone on the internet**, including anonymous users. Make sure your dataset doesn't contain sensitive, private, or copyrighted data before making it public. You can change visibility back to private at any time.

Guidelines

When contributing public content:

Do

• Provide useful, high-quality content
• Write clear descriptions
• Include relevant metadata
• Respond to questions
• Credit data sources

Don't

• Upload sensitive/private data
• Violate copyrights
• Upload inappropriate content
• Spam low-quality content
• Misrepresent performance

Share Content

Click the Share button on any public profile, project, model, or dataset. On desktop it opens a menu with Share on X, Share on LinkedIn, Copy link, and — for embeddable resources — Copy embed code. The social options open a pre-filled post. On mobile it hands off to your device's native share sheet.

Embed Widgets

Public content can be embedded in external websites using embed URLs:

Use these URLs in an <iframe> to embed public preview cards for projects, models, or datasets. Each card links to the full resource on Platform. Copy embed code in the Share menu produces the <iframe> snippet for you.

Public Content URLs

Public content on the platform uses clean, shareable URLs:

!!! tip "Shareable Links"

You can share any public content URL directly. Recipients can view the content without signing in. To clone or download, they'll need an account.

FAQ

Can I use public content commercially?

Check the license shown on the individual project, model, or dataset. Usage rights depend on that resource's license; contact the creator when the license does not grant the rights you need.

How do I report inappropriate content?

To report inappropriate content:

1. Navigate to the public page containing the content (project or dataset), if accessible
2. Open the Help page from the sidebar
3. Select General as the feedback type
4. Describe the content and the issue, including a link to the page
5. Submit the report

If the content is no longer accessible, use the Help page from any page and include as much detail as possible (URL, username, or description).

Can I make public content private again?

Yes, you can change visibility anytime:

1. Open the project or dataset
2. Click the Public visibility badge in the top navigation bar
3. The resource changes to private immediately

Existing clones are not affected.