# Image Segmentation

## Setup the Dataset

Navigate to [udt.dev](https://udt.dev) and click "New File"

![Click "New File" on udt.dev](https://708390366-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MFuZsfsLW71orr4EXRY%2F-MI1-I35x0iE2R-GuGoG%2F-MI11H2GNT530d7n2r1Q%2Fimage.png?alt=media\&token=8438ff28-e06e-4025-86ab-0be4818a2730)

Then select the Image Segmentation button from the `Setup > Data Type` page.

![](https://708390366-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MFuZsfsLW71orr4EXRY%2F-MI5xmI5P1vIVEHqJPCX%2F-MI5yZO_K24uUxEykcwf%2Fimage.png?alt=media\&token=bc028732-3396-4c41-abdd-e04362301516)

You can configure the Image Segmentation to create the right interface for your dataset. Use the `Setup > Preview` button to see your interface against either an example image or a sample from your dataset.

![Image Segmentation with Bounding Box Classification](https://708390366-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MFuZsfsLW71orr4EXRY%2F-MI5xmI5P1vIVEHqJPCX%2F-MI62IzcaVvt6pVMSitu%2Fimage.png?alt=media\&token=731e0d78-917a-459b-b7bf-7cdb830b30a6)

#### Configuring Regions and Labels

The Image Segmentation interface allows different types of regions, the options for regions are:

* bounding-box
* polygon
* point

Each region can any number of labels, which can be configured under "Available Labels"

![](https://708390366-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MFuZsfsLW71orr4EXRY%2F-MI5xmI5P1vIVEHqJPCX%2F-MI619VeDw1PxdldrLTz%2Fimage.png?alt=media\&token=34cb0b0d-7caa-4ca0-be34-42e98b5965df)

## Import Data

You can use any of the following methods to import image data. If you're just getting started, you can quickly create a dataset using the COCO Images method!

* [Import COCO Dialog](https://docs.universaldatatool.com/importing-data/coco-images)
* [Import from Google Drive](https://docs.universaldatatool.com/importing-data/import-from-google-drive)
* [Import from AWS S3 Bucket](https://docs.universaldatatool.com/importing-data/import-from-aws-s3-bucket)
* [Import from List of URLs](https://docs.universaldatatool.com/importing-data/import-file-urls)
* [Import from CSV or JSON](https://docs.universaldatatool.com/importing-data/import-from-csv-or-json)
* [Upload or Open Directory](https://docs.universaldatatool.com/importing-data/upload-or-open-directories)

## Label your Data!

Use the `Label` tab to label your data. Look at the [Collaborative Labeling Guide](https://docs.universaldatatool.com/collaborative-labeling) to label with others.

## Export and Use

You can download your data using the download icon at the top.

![Download your data in CSV or JSON format to use the annotations](https://708390366-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MFuZsfsLW71orr4EXRY%2F-MIBG6TkE1caLj9yXRio%2F-MIC16UN_c6e0nF3J9QH%2Fimage.png?alt=media\&token=208f6154-a7ad-4fc7-8218-e38cf6de8f51)

You can use the [Universal Data Tool Converter](https://universaldatatool.com/convert) to convert UDT files into PNG masks, or other formats that are helpful for machine learning datasets.

![It's very common to convert into PNGs](https://708390366-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MFuZsfsLW71orr4EXRY%2F-MIBG6TkE1caLj9yXRio%2F-MIC289RAzqgyoTZQ1u4%2Fimage.png?alt=media\&token=7e7f6e24-7b89-4d4b-bf03-20dc20f4213d)