CLAMS docTR Wrapper (v1.0)

About this version

About this app (See raw metadata.json)

CLAMS app wraps the docTR, End-to-End OCR model, available at https://pypi.org/project/python-doctr . The model is capable of detecting text regions in the input image and recognizing text in the regions. The text-localized regions are organized hierarchically by the model into “pages” > “blocks” > “lines” > “words”, and this CLAMS app translates them into TextDocument, Paragraphs, Sentence, and Token annotations to represent recognized text contents, then aligns them to BoundingBox annotations that represent the detected geometries. This hierarchical structure is also represented in the TextDocument annotation output as two newlines (\n\n) between “paragraphs”, one newline (\n) between the “lines”, and one space (“ “) between the “words”. For the text recognition, the model is internally configured to use the “parseq” recognition model, and only works with English text at the moment.

Inputs

(Note: “*” as a property value means that the property is required but can be any value.)

Configurable Parameters

(Note: Multivalued means the parameter can have one or more values.)

Name Description Type Multivalued Default Choices
tfLabel The label of the TimeFrame annotation to be processed. By default ([]), all TimeFrame annotations will be processed, regardless of their label property values. string Y []  
pretty The JSON body of the HTTP response will be re-formatted with 2-space indentation boolean N false false, true

Outputs

(Note: “*” as a property value means that the property is required but can be any value.)

(Note: Not all output annotations are always generated.)