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metadata
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': valentines-chocolate
                '1': sees-dark-almond-nougat
                '2': sees-dark-almonds
                '3': sees-dark-bordeaux
                '4': sees-dark-caramel-patties
                '5': sees-dark-chocolate-buttercream
                '6': sees-dark-marzipan
                '7': sees-dark-normandie
                '8': sees-dark-scotchmallow
                '9': sees-dark-walnut-square
                '10': sees-milk-almond-caramel
                '11': sees-milk-almonds
                '12': sees-milk-beverly
                '13': sees-milk-bordeaux
                '14': sees-milk-butterscotch-square
                '15': sees-milk-california-brittle
                '16': sees-milk-chelsea
                '17': sees-milk-chocolate-buttercream
                '18': sees-milk-coconut-cream
                '19': sees-milk-mayfair
                '20': sees-milk-mocha
                '21': sees-milk-molasses-chips
                '22': sees-milk-rum-nougat
annotations_creators:
  - crowdsourced
language_creators:
  - found
language:
  - en
license:
  - cc
multilinguality:
  - monolingual
size_categories:
  - 1K<n<10K
source_datasets:
  - original
task_categories:
  - object-detection
task_ids: []
pretty_name: valentines-chocolate
tags:
  - rf100

Dataset Card for valentines-chocolate

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

Dataset Description

Dataset Summary

valentines-chocolate

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/valentines-chocolate

Citation Information

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

Contributions

Thanks to @mariosasko for adding this dataset.