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  1. README.md +12 -4
README.md CHANGED
@@ -4,7 +4,7 @@ language:
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  - en
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  task_categories:
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  - image-to-text
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- pretty_name: IAM
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  dataset_info:
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  features:
@@ -20,12 +20,18 @@ dataset_info:
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  - name: test
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  num_examples: 2915
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  dataset_size: 10373
 
 
 
 
 
 
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  ---
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- # IAM Dataset
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  ## Table of Contents
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- - [IAM Dataset](#iam-dataset)
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  - [Table of Contents](#table-of-contents)
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  - [Dataset Description](#dataset-description)
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  - [Dataset Summary](#dataset-summary)
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  The IAM Handwriting Database contains forms of handwritten English text which can be used to train and test handwritten text recognizers and to perform writer identification and verification experiments.
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  ### Languages
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  All the documents in the dataset are written in English.
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  ### Data Fields
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- - `image`: A 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].
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  - `text`: the label transcription of the image.
 
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  - en
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  task_categories:
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  - image-to-text
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+ pretty_name: IAM-line
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  dataset_info:
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  features:
 
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  - name: test
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  num_examples: 2915
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  dataset_size: 10373
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+ tags:
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+ - atr
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+ - htr
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+ - ocr
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+ - modern
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+ - handwritten
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  ---
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+ # IAM - line level
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  ## Table of Contents
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+ - [IAM - line level](#iam-line-level)
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  - [Table of Contents](#table-of-contents)
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  - [Dataset Description](#dataset-description)
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  - [Dataset Summary](#dataset-summary)
 
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  The IAM Handwriting Database contains forms of handwritten English text which can be used to train and test handwritten text recognizers and to perform writer identification and verification experiments.
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+ Note that all images are resized to a fixed height of 128 pixels.
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+
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  ### Languages
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  All the documents in the dataset are written in English.
 
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  ### Data Fields
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+ - `image`: a PIL.Image.Image object containing the image. Note that when accessing the image column (using 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].
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  - `text`: the label transcription of the image.