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Pascal VOC data sets. Data sets from the VOC challenges are available through the challenge links below, and evalution of new methods on these data sets can be achieved through the PASCAL VOC Evaluation Server. The evaluation server will remain active even though the challenges have now finished.
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This dataset has been widely used as a benchmark for object detection, semantic segmentation, and classification tasks. The PASCAL VOC dataset is split into three subsets: 1,464 images for training, 1,449 images for validation and a private testing set.
The Pascal Visual Object Classes (VOC) dataset is a widely used benchmark in the field of computer vision. It is designed for object detection, image classification, semantic segmentation, and action classification tasks.
Sep 30, 2024 · Pascal VOC is a renowned dataset and benchmark suite that has significantly contributed to the advancement of computer vision research. It provides standardized image data sets for object class recognition and a common set of tools for accessing the data and evaluating the performance of computer vision models.
Dec 6, 2022 · This dataset contains the data from the PASCAL Visual Object Classes Challenge, corresponding to the Classification and Detection competitions.
To download the training/validation data, see the development kit. The training data provided consists of a set of images; each image has an annotation file giving a bounding box and object class label for each object in one of the twenty classes present in the image.
Pascal VOC Detection Dataset. Parameters: root (str or pathlib.Path) – Root directory of the VOC Dataset. year (string, optional) – The dataset year, supports years "2007" to "2012". image_set (string, optional) – Select the image_set to use, "train", "trainval" or "val". If year=="2007", can also be "test".
Oct 1, 2024 · The PASCAL VOC (Visual Object Classes) dataset is a well-known object detection, segmentation, and classification dataset. It is designed to encourage research on a wide variety of object categories and is commonly used for benchmarking computer vision models.
PASCAL VOC 2007 is a dataset for image recognition. The twenty object classes that have been selected are: Person: person Animal: bird, cat, cow, dog, horse, sheep Vehicle: aeroplane, bicycle, boat, bus, car, motorbike, train Indoor: bottle, chair, dining table, potted plant, sofa, tv/monitor
