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Voxel51/Office-Home HF Unverified

Dataset Card for Office-Home This is a FiftyOne dataset with 15588 samples. Installation If you haven't already, install FiftyOne: pip install -U fiftyone Usage import fiftyone as fo import fiftyone.utils.huggingface as fouh # Load the dataset # Note: other available arguments include 'max_samples', etc dataset = fouh.load_from_hub("Voxel51/Office-Home") # Launch the App session = fo.launch_app(dataset) Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/Office-Home.

Task_categories:image-ClassificationLanguage:enSize_categories:10K<n<100KFormat:imagefolderModality:imageLibrary:datasets
Voxel51/mvtec-ad HF Unverified

Dataset Card for MVTec AD This dataset originates from MVTec but is provided in a different format. You can easily load it using FiftyOne The total number of samples remains the same as the original: 5,354. Installation If you haven't already, install FiftyOne: pip install -U fiftyone Usage import fiftyone as fo import fiftyone.utils.huggingface as fouh # Load the dataset # Note: other available arguments include 'max_samples', etc dataset =… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/mvtec-ad.

Task_categories:image-ClassificationTask_categories:image-SegmentationLanguage:enSize_categories:1K<n<10KFormat:imagefolderModality:image
Voxel51/cholect50 HF Unverified

CholecT50 Dataset (FiftyOne Format) This is a FiftyOne dataset version of the CholecT50 dataset. CholecT50 is a dataset of laparoscopic cholecystectomy surgeries, annotated with surgical action triplets. It is the first public dataset to provide action triplet annotations for surgical videos, enabling research in fine-grained surgical activity recognition. Dataset Summary CholecT50 consists of 50 videos of laparoscopic cholecystectomy surgeries. Each frame is annotated… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/cholect50.

Task_categories:image-ClassificationSize_categories:100K<n<1MModality:imageLibrary:fiftyoneFiftyoneComputer-Vision
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