Support loading YOLOv8 and YOLOv9 Segmentation Models from Zoo

[jacobmarks]

Builds off of the existing Ultralytics integration, which allowed for:

• applying YOLO detection, pose estimation, or instance segmentation models to FiftyOne sample collections, and
• loading YOLO detection models directly from the FiftyOne model zoo

Now, you can load YOLOv8 segmentation models and YOLOv9 segmentation models directly from the FiftyOne Model Zoo with:

import fiftyone as fo
import fiftyone.zoo as foz

model_name = "yolov9c-seg-coco-torch"
# model_name = "yolov9e-seg-coco-torch"
# model_name = "yolov8x-seg-coco-torch"
# model_name = "yolov8l-seg-coco-torch"
# model_name = "yolov8m-seg-coco-torch"
# model_name = "yolov8s-seg-coco-torch"
# model_name = "yolov8n-seg-coco-torch"

model = foz.load_zoo_model(model_name, label_field="yolo_seg")

dataset.apply_model(model)

session = fo.launch_app(dataset)

(Details)

Release Notes

Is this a user-facing change that should be mentioned in the release notes?

• No. You can skip the rest of this section.
• Yes. Give a description of this change to be included in the release
  notes for FiftyOne users.

(Details in 1-2 sentences. You can just refer to another PR with a description
if this PR is part of a larger change.)

What areas of FiftyOne does this PR affect?

• App: FiftyOne application changes
• Build: Build and test infrastructure changes
• Core: Core fiftyone Python library changes
• Documentation: FiftyOne documentation changes
• Other

Summary by CodeRabbit

• Documentation
  • Enhanced the Ultralytics integration guide with examples on loading YOLOv8 and YOLOv9 models for dataset segmentation.

[coderabbitai]

Important

Auto Review Skipped

Review was skipped due to path filters

Files ignored due to path filters (1)

• fiftyone/zoo/models/manifest-torch.json is excluded by !**/*.json

Walkthrough

The recent update introduces code examples for loading YOLOv8 and YOLOv9 segmentation models from the FiftyOne Model Zoo and applying them to datasets. This enhancement is documented in the Ultralytics integration section, facilitating users in leveraging advanced YOLO models for their segmentation tasks.

Changes

File Path	Change Summary
docs/source/.../ultralytics.rst	Added examples for loading YOLOv8 and YOLOv9 models and applying them to datasets.

Possibly related issues

• [FR]Assessing Data Diversity in Object Detection Using FIFTYONE and Visualizing with UMAP for YOLO Recognitions #4037: The integration of YOLOv8 and YOLOv9 models could enhance the dataset analysis capabilities mentioned in the issue by providing advanced tools for object detection, potentially aiding in the visualization of data diversity with UMAP for YOLO recognitions.

Poem

In the land of code and byte,
Where models dwell in the night,
Came YOLOv8 and nine, so bright,
To aid our vision, enhance our sight.
🐇 With every pixel, clear and right,
We celebrate this leap in might!

((\
(-.-)
o_(")(")

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[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 15.56%. Comparing base (02c4d49) to head (d333740).
Report is 17 commits behind head on develop.

Additional details and impacted files

@@             Coverage Diff              @@
##           develop    #4220       +/-   ##
============================================
- Coverage    27.99%   15.56%   -12.44%     
============================================
  Files          814      779       -35     
  Lines       101631    86536    -15095     
  Branches      1178     1178               
============================================
- Hits         28453    13467    -14986     
+ Misses       73178    73069      -109     

Flag	Coverage Δ
app	15.56% <ø> (+<0.01%)	⬆️
python	?

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Commits

Files that changed from the base of the PR and between e53596a and 6f9b4e6.

Files ignored due to path filters (1)

• fiftyone/zoo/models/manifest-torch.json is excluded by !**/*.json

Files selected for processing (1)

• docs/source/integrations/ultralytics.rst (1 hunks)

Additional comments not posted (1)

docs/source/integrations/ultralytics.rst (1)

172-191: The addition of code snippets for loading YOLOv8 and YOLOv9 segmentation models from the FiftyOne Model Zoo is clear and follows the established documentation pattern. Ensure that the model names mentioned (e.g., "yolov9c-seg-coco-torch", "yolov9e-seg-coco-torch") are available and correctly named in the FiftyOne Model Zoo.

[brimoor]

LGTM 🥇