Ultralytics Snippets

v0.0.2 · by Ayberk Gezer · added 3 November 2026

Ultralytics snippets for Zed IDE.

Snippets

How to install

With Forge Super installed, the button above opens the app on this extension, where you press Install. Nothing is installed until you do.

You can also open the Extensions panel in the app and search for Ultralytics Snippets. The extension's id is ultralytics-snippets.

Don't have Forge Super yet? Download it here.

README

From the extension's repository, written by its authors and not by Mentenaz. See the source.

Ultralytics Zed Snippets

Ultralytics snippets for Zed IDE.

This project is an adaptation of the VSCode plugin called ultralytics-snippets created by Burhan-Q.

Installation

Method 1

Go to Extensions menu in Zed IDE
Search for "ultralytics-zed-snippets"
Click "Install"

Method 2

Clone this repo:

git clone https://github.com/ayberkgezer/ultralytics-zed-snippets.git

Go to Extensions menu in Zed IDE
Click "Install Dev Extension"
Select the folder you cloned

Usage

Start typing ultra. in a Python file to see the available snippets. Snippets are organized into categories:

ultra.yolo-*: YOLO model operations
ultra.sam-*: SAM model operations
ultra.util-*: Utility functions
ultra.result-*: Working with results
ultra.kwargs-*: Method arguments
ultra.example-*: Complete examples
ultra.import-*: Import statements

Import

Import snippets are for common objects that would be imported from the Ultralytics library.

Alias	Description
`ultra.import-model`	Add line to import Ultralytics YOLO
`ultra.import-assets`	Import Ultralytics ASSETS directory constant.
`ultra.import-results`	Import Ultralytics Results class (usually for type hinting).
`ultra.import-annotator`	Import Ultralytics auto_annotate function.
`ultra.import-coco2yolo`	Import Ultralytics function to convert annotations from COCO to YOLO format.
`ultra.import-bbox2seg`	Import Ultralytics function to convert horizontal bounding boxes to segmentation contours.
`ultra.import-seg2bbox`	Import Ultralytics function to convert segmentation contours into horizontal bounding boxes.
`ultra.import-box-convert`	Import Ultralytics function for converting bounding box coordinates.
`ultra.import-formats`	Import Ultralytics supported file formats constant.
`ultra.import-task-result`	Import task-based results class (generally helpful for type hinting).

Results

These snippets will provide shortcuts for working with ultralytics.engine.results.Results objects returned from model inference. See the [Working with Results][pred results] of the documentation and the [Results class] reference page for more information.

Alias	Description
`ultra.result-class-str`	Convert class indices to class string names for a single image result.
`ultra.result-data`	Get result data array of detections from a single image result.
`ultra.result-loop`	Iterate prediction results from an Ultralytics model.
`ultra.result-box-xyxy`	Get pixel-value `(x1, y1, x2, y2)` bounding box coordinates from a single image result.
`ultra.result-box-xywh`	Get pixel-value `(x-center, y-center, w, h)` bounding box coordinates from a single image result.
`ultra.result-mask-binary`	Get binary segmentation masks from a single image result. NOTE: `[N, H, W]` shape, with inference H, W dimensions.
`ultra.result-mask-contours`	Get segmentation contours with pixel value `xy` or normalized `xyn` coordinates.
`ultra.result-obb-xywhr`	Get OBB rotated bounding boxes in pixel value `[x, y, w, h, r]` coordinates as torch.Tensor array.
`ultra.result-orig-image`	Get original image from a single image result.
`ultra.result-filter-class`	Filter prediction results by class ID. Using `classes` keyword argument for prediction should be preferred.

Models

Shortcuts for initializing pretrained [Ultralytics models][models], like [YOLOv8].

Alias	Description	Reference
`ultra.yolo-model`	Shortcut to initialize YOLO model.	[YOLOv5], [YOLOv8], [YOLOv9], [YOLOv10], [YOLO-World]
`ultra.yolo-export`	Shortcut to export YOLO model weights.	[Model Export]
`ultra.sam-model`	Shortcut to initialize SAM.	[SAM]
`ultra.mobileam-model`	Shortcut to initialize MobileSAM.	[Mobile SAM]
`ultra.fastam-model`	Shortcut to initialize FastSAM.	[FastSAM]
`ultra.nas-model`	Shortcut to initialize YOLO-NAS model.	[YOLO-NAS]
`ultra.rtdetr-model`	Shortcut to initialize RTDETR model.	[RTDETR]
`ultra.yolo-world-model`	Shortcut to initialize YOLO-world model, with class prompts.	[YOLO-World]
`ultra.sam2-bboxes`	Shortcut to initialize YOLO-World model with text prompts.	[SAM2]
`ultra.sam2-points`	Shortcut to initialize YOLO-World model with text prompts.	[SAM2]

Utilities

Alias	Description	Reference
`ultra.util-auto-annotate`	Use Ultralytics auto_annotate function to generate annotations.	[`auto_annotator` fucntion][auto ann]
`ultra.util-annotator`	Use Ultralytics Annotator class to draw box annotations	[`Annotator` class][ann]
`ultra.util-make-divisible`	Use Ultralytics make_divisible function to make a number divisible by another.	[`make_divisible` function][divisible]
`ultra.util-callback`	Shortcut for adding custom model callback for a defined function.	[`callbacks`][callbacks]

Examples

The Example snippets are more "complete" blocks of code that can be used for boilerplate demonstrations.

Prefix	Description
`ultra.example-predict-filter-class`	Ultralytics basic YOLO object detection predict with filtered classes example.
`ultra.example-result-filter-class`	Filter prediction results by class ID. Using "classes" keyword argument for prediction should be preferred.
`ultra.example-yolo-predict`	Setup Ultralytics YOLO to perform predict (simple).
`ultra.example-yolo-val`	Setup Ultralytics YOLO to perform validation (simple).
`ultra.example-yolo-train`	Setup Ultralytics YOLO to perform training (simple).
`ultra.example-yolo-predict-kwords`	Setup Ultralytics YOLO to perform inference, show all inference keyword arguments and their default values.
`ultra.example-yolo-train-kwords`	Setup Ultralytics YOLO for training, with all keyword arguments and their default values.
`ultra.example-sam-predict`	Setup Ultralytics SAM to perform inference (simple).
`ultra.example-sam2`	Example showing use of SAM2 with bounding box and point prompts.
`ultra.example-mobile-sam-predict`	Setup Ultralytics MobileSAM to perform inference (simple).
`ultra.example-fast-sam-predict`	Setup Ultralytics FastSAM to perform inference (simple).
`ultra.example-nas-predict`	Setup Ultralytics NAS to perform inference (simple).
`ultra.example-rtdetr-predict`	Setup Ultralytics RT-DETR to perform inference (simple).
`ultra.example-callback`	Example showing how to add a custom callback function.
`ultra.example-track-loop-persist`	Example of how to open video, loop frames, and maintain tracked object IDs.
`ultra.example-track-kwords`	Example showing all keyword arguments available for track mode.

KWARGS

Use these to insert the various model methods defined in [modes] with all keyword arguments, default values, and commented descriptions quickly into your code. Includes model as default variable, but is an editable field accessible using tab stops.

Prefix	Description	Reference
`ultra.kwargs-predict`	Snippet using model `predict` method, including all keyword arguments and defaults.	[predict]
`ultra.kwargs-train`	Snippet using model `train` method, including all keyword arguments and defaults.	[train]
`ultra.kwargs-track`	Snippet using model `track` method, including all keyword arguments and defaults.	[track]
`ultra.kwargs-val`	Snippet using model `val` method, including all keyword arguments and defaults.	[val]

Credits and Attribution

This project is an adaptation of the VSCode plugin called ultralytics-snippets created by Burhan-Q. The original project is licensed under AGPL-3.0. All content structure, descriptions, and snippet design have been adapted for Zed IDE from the original VSCode extension. Full credit for the original concept, structure, and content goes to the original author.

Original source: Github - ultralytics-snippets