BoostCompTrack: Dataset for a multi-purpose tracking framework for salmon welfare monitoring

The data relates to code available at https://github.com/espenbh/BoostCompTrack CS_train.zip31 labeled images of salmon in cage scenes for training. Annotations include key anatomical features. CS_val.zip6 labeled images from the same context, used for validation. detector_optimization.zipContains 5 Precision–Recall (PR) curves used for evaluating and selecting detection models. detector.zipTrained YOLOv5 models for salmon detection: keybox_detection: models trained to detect keypoints (e.g., fins, head, body). bounding_box_detection: models trained to detect bounding boxes around salmon.Both use consistent label sets. TBW_train_1.zip, TBW_train_2.zip, TBW_train_3.zipLabeled images (12, 12, and 22 respectively). Annotation content consistent across all. "TBW" refers to a specific scene type or internal naming convention. TBW_val.zipVideo clip used to visualize model tracking performance in TBW scene. TS_train.zip8 labeled images from TS scenes with annotations. TS_val.zipVideo clip used to visualize model tracking performance in TS scene. GH010031_reduced_length.mp4, GH030031.MP4Underwater example video (with camera tilt), used for inspection and testing. 20230312_145025_cage15_t0x_yz.avi.aviSample underwater video recorded in cage 15, showing fish behavior under standard conditions. Used for visual inspection and qualitative assessment of model performance. 20240508_121121_1715170281739114875_Korsneset_Merd07_22228352_B2Ave_cAIge.avi-0000_00h02m40s_00h00m40s_win.aviCropped segment from stereo footage recorded at Korsneset, cage 07 (camera ID 22228352), showing 40 seconds of activity. Used for model evaluation and behavioral analysis.