Synthetic Operating Room Table (SORT) Dataset
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The Synthetic Operating Room Table (SORT) dataset is a largescale computer vision focused on instance counting, segmentation and localisation surgical instrument depictions placed on a table. The depictions contained are rendered using the Unrealgame engine and annotated leveraging the UnrealCV plugin (Qui, 2017). SORT contains one container class, one material class (gauze) and six instrument classes namely, forceps, scalpels, pincettes (tweezers), syringes, periotomes, and scissors.  Each class contains two different 3D representations equally likely to be present for a given instance, with exception of the container class that leverages three different 3D models. In total, we generated 89,838 images, split into 60% training (53,906), 20% validation (17,96' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["computer vision","instance counting","instance segmentation","localization","retained foreign body","retained surgical item (RSI)","semantic segmentation","Synthetic data"]} <|eot_id|>
 Here is the Description of a dataset. Description:'The Synthetic Operating Room Table (SORT) dataset is a largescale computer vision focused on instance counting, segmentation and localisation surgical instrument depictions placed on a table. The depictions contained are rendered using the Unrealgame engine and annotated leveraging the UnrealCV plugin (Qui, 2017). SORT contains one container class, one material class (gauze) and six instrument classes namely, forceps, scalpels, pincettes (tweezers), syringes, periotomes, and scissors.  Each class contains two different 3D representations equally likely to be present for a given instance, with exception of the container class that leverages three different 3D models. In total, we generated 89,838 images, split into 60% training (53,906), 20% validation (17,96' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
The Synthetic Operating Room Table (SORT) dataset is a largescale computer vision focused on instance counting, segmentation and localisation surgical instrument depictions placed on a table. The depictions contained are rendered using the Unrealgame engine and annotated leveraging the UnrealCV plugin (Qui, 2017). SORT contains one container class, one material class (gauze) and six instrument classes namely, forceps, scalpels, pincettes (tweezers), syringes, periotomes, and scissors.  Each class contains two different 3D representations equally likely to be present for a given instance, with exception of the container class that leverages three different 3D models. In total, we generated 89,838 images, split into 60% training (53,906), 20% validation (17,96
computer vision; instance counting; instance segmentation; localization; retained foreign body; retained surgical item (RSI); semantic segmentation; Synthetic data