#### NOTE
This is a **community plugin**, an external project maintained by its respective author.
Community plugins are not part of FiftyOne core and may change independently.
Please review each plugin’s documentation and license before use.

<a href="https://github.com/mgustineli/roi-patches-plugin" target="_blank">![GitHub Repo](https://img.shields.io/badge/GitHub-Repository-black?logo=github)</a>

# ROI Patches Plugin for FiftyOne

A [FiftyOne](https://github.com/voxel51/fiftyone) plugin that tiles images into a configurable grid of ROI (Region of Interest) patches for region-based analysis.

Instead of saving physical cropped files, the plugin leverages FiftyOne’s native [`to_patches()`](https://docs.voxel51.com/user_guide/using_views.html#patches) mechanism — it adds bounding box detections representing grid tiles to each sample. After creation, select the patches field via the **Patches** button to view the individual cropped tiles.

![gif](https://raw.githubusercontent.com/mgustineli/roi-patches-plugin/main/roi-patches-plugin.gif)

## Installation

```shell
fiftyone plugins download https://github.com/mgustineli/roi-patches-plugin
```

## Operators

### Create ROI Patches

Tiles images into a grid of ROI patches.

- **Rows / Columns** — grid dimensions (1-20)
- **Overlap %** — overlap between adjacent tiles (0-90%)
- **Field name** — sample field to store the detections (default: `roi_patches`)

Supports delegated execution (schedule on builtin) for large datasets.

### Clear ROI Patches

Removes an ROI patches field from the dataset. Select any existing Detections field from the dropdown.

## Usage

1. Open the FiftyOne App and load a dataset
2. Open the operator search and look for **“Create ROI patches”**
3. Configure the grid and click **Schedule**
4. Once complete, click the **Patches** button in the App toolbar and select your field to view the individual tiles

To remove patches, open the operator search and look for **“Clear ROI patches”**, then select the field to delete.

## How It Works

The grid math computes bounding boxes in normalized `[0, 1]` coordinates:

- `tile_w = 1 / (cols - (cols - 1) * overlap)` for cols > 1, else 1.0
- `tile_h = 1 / (rows - (rows - 1) * overlap)` for rows > 1, else 1.0
- Each tile gets a label in `R{row}_C{col}` format (e.g., `R0_C0`, `R2_C3`)
- Tiles also store `row`, `col`, `overlap_pct`, `grid_rows`, and `grid_cols` as dynamic attributes