# Weighted Boxes Fusion A plugin that provides methods for ensembling bounding boxes from different object detection models directly within the [FiftyOne App](https://docs.voxel51.com), using [Weighted Boxes Fusion (WBF)](https://arxiv.org/abs/1910.13302). Based on [ZFTurbo’s Weighted-Boxes-Fusion](https://github.com/ZFTurbo/Weighted-Boxes-Fusion). ## Installation ```shell fiftyone labs install @51labs/box_combine ``` ## Usage 1. Launch the App: ```python import fiftyone as fo import fiftyone.zoo as foz dataset = foz.load_zoo_dataset("quickstart") session = fo.launch_app(dataset) ``` 1. Click the `Browse operations` action to open the Operators list 2. Select the `box_combine` operator. ### Example workflow A common workflow is to run multiple object detection models on a dataset and then combine their predictions: ```python import fiftyone as fo import fiftyone.zoo as foz dataset = foz.load_zoo_dataset("quickstart") # Run multiple detection models model1 = foz.load_zoo_model("faster-rcnn-resnet50-fpn-coco-torch") model2 = foz.load_zoo_model("retinanet-resnet50-fpn-coco-torch") dataset.apply_model(model1, label_field="det_faster_rcnn") dataset.apply_model(model2, label_field="det_retinanet") session = fo.launch_app(dataset) ``` In the app, select `det_faster_rcnn` and `det_retinanet` labels in the panel on the left. Open `box_combine` operator to fuse the predictions from the selected label into a single field using weighted boxes fusion method.