# Gallery & Table views

Supervisely provides multiple data display modes to help you **explore and analyze your data more effectively**. Depending on the context, you can choose between visual gallery-based views and structured table-based views. These display modes are available both on the **project list page** and **inside individual projects and datasets**.

Gallery views are best suited for getting a quick **visual overview** of your data. Table views offer a **structured and sortable layout**, which helps when comparing metadata or filtering based on specific attributes.

These features are designed to help teams **understand the composition of their datasets**, **inspect content before labeling**, and **navigate large projects more efficiently**.

The data display modes on the project list page and within a project differ slightly:

## On the Project List Page

On the main project list page (inside a workspace), you can toggle between two display modes. Use the **view switcher icon** in the upper-right corner of the page to switch between **gallery view** and **table view**.

### Gallery View

Projects are displayed as visual cards with thumbnails (default), making it easier to recognize them at a glance.

<figure><img src="/files/KZaloVHrfF0O4SDh6DcP" alt=""><figcaption></figcaption></figure>

### Table View

Projects are listed in a tabular format, which allows for sorting by various parameters such as **project name**, **creator**, and **project size** (based on the number of datasets and files inside each project).

<figure><img src="/files/5unXegTfTUEPvUnJRa1c" alt=""><figcaption></figcaption></figure>

{% hint style="info" %}
**Note**: To select all projects, switch to the **Table View** mode.
{% endhint %}

## Inside a Project

Within a specific project - whether on the datasets overview page or inside an individual dataset - you have additional display modes to choose from. These let you control how files and annotations are visualized.

Use the display settings icon located in the upper-right corner of the screen (next to the **Add** button) to switch between modes:

### Gallery with Hierarchy

Datasets are displayed as visual cards with thumbnails (default), making it easier to recognize them at a glance.

<figure><img src="/files/Nc8bRnAVWPAzcOzRmIfm" alt=""><figcaption></figcaption></figure>

### Gallery Expanded

Flattens all datasets and sub-datasets into a single, continuous gallery. This is helpful for **visually scanning large volumes of data** across the entire project.

<figure><img src="/files/kuijfIY1LdYuDf4UrMZu" alt=""><figcaption></figcaption></figure>

### Table with Hierarchy

Displays a **nested table** that shows the list of datasets and their files at the **top level** of the project. Useful for **reviewing dataset structure** and inspecting associated metadata in a structured format.

<figure><img src="/files/dgynEXFBv7TgAMg2r4ml" alt=""><figcaption></figcaption></figure>

### Table Expanded

Displays all data from all datasets - including nested sub-datasets - in a **single-level table**. Ideal for **sorting and comparing** files across the entire project, regardless of their position in the dataset hierarchy.

<figure><img src="/files/16etm8mPVYJ2QNalniA7" alt=""><figcaption></figcaption></figure>

{% hint style="info" %}
**Note**: To select all datasets within a project, switch to one of the **Table View** modes.
{% endhint %}

## Grid Size (Gallery Views Only)

When using any gallery mode, you can adjust the **grid size** to control how many items are shown per row:

* Smaller grid size: More thumbnails per row, helpful for scanning large datasets.
* Larger grid size: Bigger previews, better suited for reviewing image or point cloud content in detail.

This allows users to **customize the visual density** of the gallery depending on their review or labeling context.

#### Summary

Different display modes are tailored for different stages of dataset management - from **visual exploration** to **structured inspection and filtering**. By choosing the right view, users can better navigate complex projects, understand dataset composition, and prepare data for annotation workflows.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.supervisely.com/data-organization/project-dataset/gallery-table-views.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.