Feat/ultralytics obb support #4230
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- Add YoloOBB class adapter - Use obb attribute from OBB ultralytics model outputs to create 51 polyline label.
WalkthroughThe recent update introduces functionality to handle Oriented Bounding Box (OBB) models from Ultralytics YOLO within the FiftyOne toolkit. It adds a specific function for converting YOLO instance segmentations to the FiftyOne format, alongside new classes designed for managing YOLO OBB detection models. Additionally, it updates the conversion logic to support these OBB models, enhancing the toolkit's versatility in object detection tasks. Changes
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- fiftyone/utils/ultralytics.py (4 hunks)
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fiftyone/utils/ultralytics.py (4)
45-48: Consider adding a brief docstring to the_convert_yolo_obb_modelfunction to explain its purpose and usage.
172-222: Ensure that theobb_to_polylinesfunction correctly handles the conversion of OBB detections to polylines, especially the transformation of coordinates from the OBB format to the polyline format. Verify that thepointsvariable is correctly populated with the expected format for polylines in FiftyOne.#!/bin/bash # Verify the coordinate transformation logic by checking for unit tests or examples that use `obb_to_polylines`. fd --type f --exec grep -Hn 'obb_to_polylines' {} +
440-458: Ensure that theFiftyOneYOLOOBBModelclass's_format_predictionsmethod correctly converts predictions to the expected format for FiftyOne. This is crucial for integrating OBB detections into the FiftyOne ecosystem seamlessly.#!/bin/bash # Check for usage examples or tests for `FiftyOneYOLOOBBModel` to ensure correct prediction formatting. fd --type f --exec grep -Hn 'FiftyOneYOLOOBBModel' {} +
505-507: The_convert_yolo_obb_modelfunction correctly creates a configuration for the OBB model and returns an instance ofFiftyOneYOLOOBBModel. Ensure that this function is properly integrated and used wherever Ultralytics YOLO OBB models need to be converted for use in FiftyOne.
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Overall this implementation looks solid to me, and it works! Noting that the OBB models from Ultralytics are trained on DOTA so don't really work on datasets like COCO :)
Awesome contribution @dimidagd 💪
If you're so inclined, also feel free to add these pretrained OBB models to the FiftyOne Model Zoo, so that downloading and location of checkpoint is managed by FiftyOne :) You can do so by adding them here. In addition, you can add a section to the Ultralytics integration docs inference section for OBB object detection.
All that being said, if you don't have the time, we can also make sure these get in, so as to highlight the awesomeness of your work!!!
Codecov ReportAll modified and coverable lines are covered by tests ✅
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What changes are proposed in this pull request?
Model outputs from OBB ultralytics models were ignored. This commit enables use of apply_model method on a 51 dataset.
(Details)
Release Notes
Is this a user-facing change that should be mentioned in the release notes?
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?
fiftyonePython library changesSummary by CodeRabbit