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2.69k
2.69k
class_id
class label
11 classes
bbox
sequencelengths
4
4
9verde_cogollo
[ 76, 0, 2413, 980 ]
0verde_plastico
[ 141, 160, 2469, 1167 ]
0verde_plastico
[ 365, 338, 2004, 884 ]
0verde_plastico
[ 1517, 433, 882, 875 ]
7roja_eldulze
[ 0, 227, 2688, 1256 ]
7roja_eldulze
[ 192, 398, 2218, 926 ]
7roja_eldulze
[ 266, 396, 2067, 849 ]
7roja_eldulze
[ 201, 379, 2209, 935 ]
7roja_eldulze
[ 154, 420, 2274, 883 ]
7roja_eldulze
[ 261, 344, 2103, 920 ]
7roja_eldulze
[ 289, 435, 2032, 812 ]
7roja_eldulze
[ 106, 345, 2384, 911 ]
3negro_carton
[ 115, 432, 2465, 1088 ]
3negro_carton
[ 289, 559, 2117, 881 ]
3negro_carton
[ 340, 559, 2014, 822 ]
3negro_carton
[ 249, 503, 2201, 944 ]
3negro_carton
[ 203, 456, 2271, 914 ]
3negro_carton
[ 275, 516, 2138, 896 ]
3negro_carton
[ 346, 537, 1991, 819 ]
3negro_carton
[ 265, 511, 2158, 913 ]
3negro_carton
[ 142, 437, 2406, 977 ]
9verde_cogollo
[ 18, 376, 2533, 1144 ]
9verde_cogollo
[ 195, 433, 2175, 1087 ]
9verde_cogollo
[ 317, 429, 1932, 949 ]
9verde_cogollo
[ 211, 388, 2139, 1068 ]
9verde_cogollo
[ 194, 451, 2180, 1013 ]
9verde_cogollo
[ 0, 198, 2688, 1322 ]
9verde_cogollo
[ 76, 306, 2403, 1119 ]
9verde_cogollo
[ 211, 405, 2148, 1047 ]
9verde_cogollo
[ 237, 410, 2101, 1015 ]
9verde_cogollo
[ 139, 385, 2295, 1120 ]
0verde_plastico
[ 1531, 274, 899, 873 ]
0verde_plastico
[ 1520, 455, 838, 771 ]
9verde_cogollo
[ 68, 0, 2417, 1077 ]
9verde_cogollo
[ 92, 0, 2375, 861 ]
9verde_cogollo
[ 146, 79, 2273, 1046 ]
9verde_cogollo
[ 258, 0, 2050, 861 ]
9verde_cogollo
[ 62, 0, 2453, 971 ]
4roja_plastico
[ 171, 627, 2373, 893 ]
4roja_plastico
[ 123, 679, 2440, 841 ]
4roja_plastico
[ 162, 614, 2356, 906 ]
1azul
[ 77, 639, 2557, 881 ]
1azul
[ 150, 548, 2444, 972 ]
0verde_plastico
[ 162, 686, 2506, 834 ]
0verde_plastico
[ 229, 625, 2369, 895 ]
0verde_plastico
[ 144, 549, 2516, 971 ]
4roja_plastico
[ 212, 631, 2310, 889 ]
4roja_plastico
[ 119, 0, 2477, 868 ]
4roja_plastico
[ 40, 617, 2648, 903 ]
4roja_plastico
[ 108, 623, 2455, 897 ]
4roja_plastico
[ 45, 519, 2538, 1001 ]
4roja_plastico
[ 193, 638, 2349, 882 ]
4roja_plastico
[ 152, 547, 2369, 973 ]
4roja_plastico
[ 47, 508, 2627, 1012 ]
4roja_plastico
[ 198, 0, 2332, 1001 ]
0verde_plastico
[ 160, 685, 2449, 835 ]
1azul
[ 170, 613, 2416, 907 ]
1azul
[ 182, 598, 2357, 922 ]
1azul
[ 227, 586, 2294, 934 ]
1azul
[ 161, 644, 2419, 876 ]
1azul
[ 177, 564, 2420, 956 ]
1azul
[ 133, 618, 2437, 902 ]
1azul
[ 40, 634, 2461, 886 ]
1azul
[ 128, 400, 2455, 1120 ]
1azul
[ 169, 613, 2372, 907 ]
1azul
[ 106, 662, 2489, 858 ]
1azul
[ 160, 622, 2404, 898 ]
1azul
[ 151, 563, 2415, 957 ]
1azul
[ 215, 630, 2299, 890 ]
1azul
[ 187, 612, 2370, 908 ]
1azul
[ 158, 636, 2402, 884 ]
1azul
[ 207, 618, 2331, 902 ]
1azul
[ 152, 595, 2442, 925 ]
1azul
[ 210, 643, 2315, 877 ]
1azul
[ 187, 491, 2377, 1029 ]
1azul
[ 160, 582, 2385, 938 ]
1azul
[ 160, 541, 2402, 979 ]
1azul
[ 236, 621, 2312, 899 ]
1azul
[ 141, 466, 2463, 1054 ]
1azul
[ 115, 669, 2448, 851 ]
1azul
[ 232, 687, 2232, 833 ]
1azul
[ 78, 564, 2579, 956 ]
1azul
[ 134, 586, 2469, 934 ]
1azul
[ 160, 553, 2442, 967 ]
0verde_plastico
[ 154, 634, 2437, 886 ]
0verde_plastico
[ 125, 654, 2466, 866 ]
1azul
[ 149, 696, 2460, 824 ]
1azul
[ 229, 665, 2336, 855 ]
1azul
[ 190, 660, 2397, 860 ]
1azul
[ 201, 695, 2355, 825 ]
1azul
[ 208, 625, 2355, 895 ]
1azul
[ 188, 668, 2415, 852 ]
1azul
[ 154, 597, 2447, 923 ]
1azul
[ 163, 697, 2437, 823 ]
1azul
[ 201, 643, 2361, 877 ]
0verde_plastico
[ 174, 668, 2294, 852 ]
0verde_plastico
[ 177, 713, 2394, 807 ]
0verde_plastico
[ 194, 683, 2411, 837 ]
0verde_plastico
[ 250, 0, 2281, 883 ]
4roja_plastico
[ 121, 527, 2476, 993 ]
End of preview. Expand in Data Studio

The IndustrialLateralLoads dataset is divided into a single split: loads. This split contains the following:

  • A folder with all the images: imgs
  • A folder that includes for each image a .txt file that holds a single line with the bounding box annotation of the main load in the image: annotations

Remark: Each row in a .txt file follows this format:

<class_name> <instance_id> <x_min> <y_min> <weight> <height>,

where the field <instance_id> is not relevant in the currently published dataset.


Install Hugging Face datasets package:

pip install datasets

Download the dataset:

from datasets import load_dataset
dataset = load_dataset("jjldo21/IndustrialLateralLoads")
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