Datasets:

Francesco
/

bccd-ouzjz

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26	640	640	{ "id": [ 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351 ], "area": [ 42582, 13812, 15810, 15810, 15810, 12760, 12760, 12702, 12772, 12772, 19912, 10416, 976...
246	640	640	{ "id": [ 3333, 3334, 3335, 3336, 3337, 3338, 3339, 3340, 3341, 3342 ], "area": [ 16287, 21672, 12500, 12544, 10608, 8399, 34272, 12672, 12672, 12672 ], "bbox": [ [ 86, 1, 122, 133.5 ], [ ...
182	640	640	{ "id": [ 2468, 2469, 2470, 2471, 2472, 2473, 2474, 2475, 2476, 2477, 2478, 2479, 2480 ], "area": [ 14384, 13320, 14384, 16848, 13531, 14746, 13328, 13328, 12000, 18080, 23430, 1452, 14067 ], "bbox": [ ...
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94	640	640	{ "id": [ 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296 ], "area": [ 8832, 14840, 14840, 14840, 12270, 13771, 16416, 16408, 15382, 15382, 16416, 12852, ...
164	640	640	{ "id": [ 2226, 2227, 2228, 2229, 2230, 2231, 2232, 2233, 2234, 2235, 2236 ], "area": [ 14756, 17158, 12682, 19484, 19338, 19484, 13850, 13850, 15776, 15776, 19864 ], "bbox": [ [ 93, 86, 119, 12...
253	640	640	{ "id": [ 3420, 3421, 3422, 3423, 3424, 3425, 3426, 3427, 3428, 3429, 3430, 3431, 3432, 3433, 3434, 3435 ], "area": [ 27289, 16068, 16068, 17434, 14060, 14060, 14060, 16800, 18544, 13696, 8587, 12880, ...
158	640	640	{ "id": [ 2142, 2143, 2144, 2145, 2146, 2147, 2148, 2149, 2150, 2151, 2152, 2153, 2154 ], "area": [ 17548, 17548, 17688, 12949, 12949, 17697, 18648, 12896, 12949, 13725, 73530, 1872, 3312 ], "bbox": [ [...
23	640	640	{ "id": [ 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315 ], "area": [ 35476, 1728, 3471, 1728, 16660, 16660, 16660, 16660, 16660, 16660, 16660, 16660, 16481,...
185	640	640	{ "id": [ 2504, 2505, 2506, 2507, 2508, 2509, 2510, 2511, 2512, 2513 ], "area": [ 14916, 12320, 12460, 20124, 14916, 24502, 10496, 9300, 21653, 2171 ], "bbox": [ [ 201, 298, 113, 132 ], [ ...
34	640	640	{ "id": [ 429, 430, 431, 432, 433, 434, 435, 436, 437 ], "area": [ 15408, 15408, 15408, 22859, 14336, 12720, 14948, 11832, 67744 ], "bbox": [ [ 480, 402, 107, 144 ], [ 204, 110, 107, ...
33	640	640	{ "id": [ 421, 422, 423, 424, 425, 426, 427, 428 ], "area": [ 16295, 16295, 18385, 18385, 16872, 61880, 1765, 1410 ], "bbox": [ [ 191, 489, 109, 149.5 ], [ 406, 488, 109, 149.5 ], ...
142	640	640	{ "id": [ 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913 ], "area": [ 12950, 12950, 12672, 12950, 12950, 15048, 18925, 11648, 12120, 12322, 2530, 1452, ...
140	640	640	{ "id": [ 1868, 1869, 1870, 1871, 1872, 1873, 1874, 1875, 1876, 1877, 1878, 1879, 1880, 1881 ], "area": [ 16538, 14140, 12412, 13824, 16568, 12495, 13824, 17149, 10933, 9880, 11040, 12397, 12740, 61085 ...

End of preview. Expand in Data Studio

Dataset Card for bccd-ouzjz

** The original COCO dataset is stored at dataset.tar.gz**

Dataset Summary

bccd-ouzjz

Supported Tasks and Leaderboards

object-detection: The dataset can be used to train a model for Object Detection.

Languages

English

Dataset Structure

Data Instances

A data point comprises an image and its object annotations.

{
  'image_id': 15,
  'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=640x640 at 0x2373B065C18>,
  '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 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/bccd-ouzjz

Citation Information

@misc{ bccd-ouzjz,
    title = { bccd ouzjz Dataset },
    type = { Open Source Dataset },
    author = { Roboflow 100 },
    howpublished = { \url{ https://universe.roboflow.com/object-detection/bccd-ouzjz } },
    url = { https://universe.roboflow.com/object-detection/bccd-ouzjz },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { nov },
    note = { visited on 2023-03-29 },
}"

Contributions

Thanks to @mariosasko for adding this dataset.

Downloads last month: 173

Homepage:

universe.roboflow.com

Point of Contact:

francesco.zuppichini@gmail.com

Size of downloaded dataset files:

9.63 MB

Size of the auto-converted Parquet files:

9.63 MB

Number of rows:

364