--- dataset_info: features: - name: image_id dtype: int64 - name: image dtype: image - name: width dtype: int32 - name: height dtype: int32 - name: objects sequence: - name: id dtype: int64 - name: area dtype: int64 - name: bbox sequence: float32 length: 4 - name: category dtype: class_label: names: '0': poker-cards '1': 59 '2': 10 Diamonds '3': 10 Hearts '4': 10 Spades '5': 10 Trefoils '6': 2 Diamonds '7': 2 Hearts '8': 2 Spades '9': 2 Trefoils '10': 3 Diamonds '11': 3 Hearts '12': 3 Spades '13': 3 Trefoils '14': 4 Diamonds '15': 4 Hearts '16': 4 Spades '17': 4 Trefoils '18': 5 Diamonds '19': 5 Hearts '20': 5 Spades '21': 5 Trefoils '22': 6 Diamonds '23': 6 Hearts '24': 6 Spades '25': 6 Trefoils '26': 7 Diamonds '27': 7 Hearts '28': 7 Spades '29': 7 Trefoils '30': 8 Diamonds '31': 8 Hearts '32': 8 Spades '33': 8 Trefoils '34': 9 Diamonds '35': 9 Hearts '36': 9 Spades '37': 9 Trefoils '38': A Diamonds '39': A Hearts '40': A Spades '41': A Trefoils '42': J Diamonds '43': J Hearts '44': J Spades '45': J Trefoils '46': K Diamonds '47': K Hearts '48': K Spades '49': K Trefoils '50': Q Diamonds '51': Q Hearts '52': Q Spades '53': Q Trefoils annotations_creators: - crowdsourced language_creators: - found language: - en license: - cc multilinguality: - monolingual size_categories: - 1K, 'width': 964043, 'height': 640, 'objects': { 'id': [114, 115, 116, 117], 'area': [3796, 1596, 152768, 81002], 'bbox': [ [302.0, 109.0, 73.0, 52.0], [810.0, 100.0, 57.0, 28.0], [160.0, 31.0, 248.0, 616.0], [741.0, 68.0, 202.0, 401.0] ], 'category': [4, 4, 0, 0] } } ``` ### Data Fields - `image`: the image id - `image`: `PIL.Image.Image` object containing the image. Note that when accessing the image column: `dataset[0]["image"]` the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the `"image"` column, *i.e.* `dataset[0]["image"]` should **always** be preferred over `dataset["image"][0]` - `width`: the image width - `height`: the image height - `objects`: a dictionary containing bounding box metadata for the objects present on the image - `id`: the annotation id - `area`: the area of the bounding box - `bbox`: the object's bounding box (in the [coco](https://albumentations.ai/docs/getting_started/bounding_boxes_augmentation/#coco) format) - `category`: the object's category. #### Who are the annotators? Annotators are Roboflow users ## Additional Information ### Licensing Information See original homepage https://universe.roboflow.com/object-detection/poker-cards-cxcvz ### Citation Information ``` @misc{ poker-cards-cxcvz, title = { poker cards cxcvz Dataset }, type = { Open Source Dataset }, author = { Roboflow 100 }, howpublished = { \url{ https://universe.roboflow.com/object-detection/poker-cards-cxcvz } }, url = { https://universe.roboflow.com/object-detection/poker-cards-cxcvz }, journal = { Roboflow Universe }, publisher = { Roboflow }, year = { 2022 }, month = { nov }, note = { visited on 2023-03-29 }, }" ``` ### Contributions Thanks to [@mariosasko](https://github.com/mariosasko) for adding this dataset.