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metadata
dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': '1'
            '1': '100'
            '2': '102'
            '3': '104'
            '4': '105'
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            '7': '113'
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            '9': '117'
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            '25': '148'
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            '27': '153'
            '28': '154'
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            '30': '157'
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            '32': '159'
            '33': '16'
            '34': '172'
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            '37': '181'
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            '92': '60'
            '93': '63'
            '94': '64'
            '95': '66'
            '96': '67'
            '97': '68'
            '98': '70'
            '99': '71'
            '100': '72'
            '101': '73'
            '102': '75'
            '103': '77'
            '104': '78'
            '105': '79'
            '106': '81'
            '107': '82'
            '108': '83'
            '109': '84'
            '110': '86'
            '111': '89'
            '112': '92'
            '113': '93'
            '114': '98'
    - name: masterID
      dtype: string
  splits:
    - name: train
      num_bytes: 1231725568.256
      num_examples: 19376
    - name: validation
      num_bytes: 185216574.826
      num_examples: 2418
    - name: test
      num_bytes: 144023269.65
      num_examples: 2385
  download_size: 1622096095
  dataset_size: 1560965412.732
license: apache-2.0
language:
  - en
tags:
  - medical
pretty_name: testing_only
size_categories:
  - n<1K

Dataset Card for "test"

This is a testing only dataset I created to open source some of the prior work we had in imaging space. The idea is to use DL algorithms to enable usage of low grade photos for self evaluation of specific use cases. Images are not fully captioned, I intend to open source the entire dataset once I have full clearance for its usage by the open source community

Images have been anonymized and any specific individual identifying characteristics have been removed. In case you find any still remaining, do ping me!