---
dataset_info:
  features:
  - name: image_id
    dtype: int64
  - name: image
    dtype: image
  - name: width
    dtype: int64
  - name: height
    dtype: int64
  - name: objects
    sequence:
    - name: bbox_id
      dtype: int64
    - name: category
      dtype:
        class_label:
          names:
            '0': person
            '1': bicycle
            '2': car
            '3': motorcycle
            '4': airplane
            '5': bus
            '6': train
            '7': truck
            '8': boat
            '9': traffic light
            '10': fire hydrant
            '11': stop sign
            '12': parking meter
            '13': bench
            '14': bird
            '15': cat
            '16': dog
            '17': horse
            '18': sheep
            '19': cow
            '20': elephant
            '21': bear
            '22': zebra
            '23': giraffe
            '24': backpack
            '25': umbrella
            '26': handbag
            '27': tie
            '28': suitcase
            '29': frisbee
            '30': skis
            '31': snowboard
            '32': sports ball
            '33': kite
            '34': baseball bat
            '35': baseball glove
            '36': skateboard
            '37': surfboard
            '38': tennis racket
            '39': bottle
            '40': wine glass
            '41': cup
            '42': fork
            '43': knife
            '44': spoon
            '45': bowl
            '46': banana
            '47': apple
            '48': sandwich
            '49': orange
            '50': broccoli
            '51': carrot
            '52': hot dog
            '53': pizza
            '54': donut
            '55': cake
            '56': chair
            '57': couch
            '58': potted plant
            '59': bed
            '60': dining table
            '61': toilet
            '62': tv
            '63': laptop
            '64': mouse
            '65': remote
            '66': keyboard
            '67': cell phone
            '68': microwave
            '69': oven
            '70': toaster
            '71': sink
            '72': refrigerator
            '73': book
            '74': clock
            '75': vase
            '76': scissors
            '77': teddy bear
            '78': hair drier
            '79': toothbrush
    - name: bbox
      sequence: float64
      length: 4
    - name: area
      dtype: float64
  - name: od_string
    dtype: string
  splits:
  - name: train
    num_bytes: 19253514712.75
    num_examples: 117266
  - name: val
    num_bytes: 811554160.0
    num_examples: 4952
  download_size: 19991132145
  dataset_size: 20065068872.75
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: val
    path: data/val-*
---

Processed the bounding boxes from coco to paligemma like.
Reference dataset -> [`detection-datasets/coco`](https://huggingface.co/datasets/detection-datasets/coco)