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View: |
Part 1: Document Description
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Citation |
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Title: |
Flowers Dataset |
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Identification Number: |
doi:10.7910/DVN/1ECTVN |
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Distributor: |
Harvard Dataverse |
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Date of Distribution: |
2020-08-24 |
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Version: |
8 |
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Bibliographic Citation: |
Tung, K, 2020, "Flowers Dataset", https://doi.org/10.7910/DVN/1ECTVN, Harvard Dataverse, V8, UNF:6:z6JGwpi2tftxFU+tbVH/3g== [fileUNF] |
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Citation |
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Title: |
Flowers Dataset |
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Identification Number: |
doi:10.7910/DVN/1ECTVN |
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Authoring Entity: |
Tung, K |
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Distributor: |
Harvard Dataverse |
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Access Authority: |
Tung, K |
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Depositor: |
Tung, K |
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Date of Deposit: |
2020-08-24 |
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Holdings Information: |
https://doi.org/10.7910/DVN/1ECTVN |
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Study Scope |
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Keywords: |
Computer and Information Science, flowers |
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Abstract: |
Open source flower images available in Python distribution. Raw images converted to TFRecord format in offline process. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
<a href="http://creativecommons.org/publicdomain/zero/1.0">CC0 1.0</a> |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Title: |
https://www.tensorflow.org/datasets/catalog/tf_flowers |
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Bibliographic Citation: |
https://www.tensorflow.org/datasets/catalog/tf_flowers |
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File Description--f4105642 |
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File: iris-write-from-docker.tab |
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Notes: |
UNF:6:z6JGwpi2tftxFU+tbVH/3g== |
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iris csv from open source |
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List of Variables: |
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Variables |
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f4105642 Location: |
Summary Statistics: Min. 4.3; Valid 150.0; Max. 7.9; Mean 5.843333333333334; StDev 0.8280661279778628; Variable Format: numeric Notes: UNF:6:FnQvOCZE9tcn64bP78wLag== |
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f4105642 Location: |
Summary Statistics: Mean 3.054; StDev 0.43359431136217386; Min. 2.0; Max. 4.4; Valid 150.0 Variable Format: numeric Notes: UNF:6:9y73F+xls7P88ROL/Mzjpw== |
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f4105642 Location: |
Summary Statistics: Valid 150.0; Mean 3.758666666666666; StDev 1.7644204199522626; Max. 6.9; Min. 1.0 Variable Format: numeric Notes: UNF:6:IB1rYmQhyDGJp/xkodIeDQ== |
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f4105642 Location: |
Summary Statistics: Mean 1.1986666666666665; Valid 150.0; StDev 0.763160741700841; Min. 0.1; Max. 2.5; Variable Format: numeric Notes: UNF:6:OdccDV+WfIurAVoLSfVlnQ== |
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f4105642 Location: |
Variable Format: character Notes: UNF:6:L2VViO9LlQYOVA3L225IJQ== |
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Label: |
flowers.zip |
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Text: |
jpg of flower images partitioned into test, training and validation. |
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Notes: |
application/zip |
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Label: |
flower_photos_plus_small_testset.zip |
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Text: |
Raw jpg images. In addition to train, test, and validation, a small_test dataset is added as a sub-directory. |
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Notes: |
application/zip |
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Label: |
flower_tfrecords.zip |
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Text: |
TFRecord of flowers partitioned into test, training and validation |
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Notes: |
application/zip |
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Label: |
Inspecting_TFRecord.ipynb |
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Text: |
Jupiter notebook with TensorFlow 2.x. Demonstrate how to inspect TFRecord. |
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Notes: |
application/x-ipynb+json |
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Label: |
setup.py |
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Text: |
This file is necessary for using gcloud AI Platform with TPU. See https://cloud.google.com/ai-platform/training/docs/using-tpus |
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Notes: |
text/x-python-script |
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Label: |
dataset_info.json |
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Notes: |
application/json |
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Label: |
image-encoded.image.json |
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Notes: |
application/json |
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Label: |
image_classification_builder-test.tfrecord-00000-of-00001 |
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Notes: |
application/octet-stream |
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Label: |
image_classification_builder-train.tfrecord-00000-of-00002 |
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Notes: |
application/octet-stream |
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Label: |
image_classification_builder-train.tfrecord-00001-of-00002 |
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Notes: |
application/octet-stream |
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Label: |
image_classification_builder-validation.tfrecord-00000-of-00001 |
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Notes: |
application/octet-stream |