Index

A

add() (kraken.lib.dataset.BaselineSet method) (kraken.lib.dataset.GroundTruthDataset method) (kraken.lib.dataset.PolygonGTDataset method) add_codec() (kraken.lib.vgsl.TorchVGSLModel method) add_labels() (kraken.lib.codec.PytorchCodec method) add_page() (kraken.transcribe.TranscriptionInterface method)

alphabet (kraken.lib.dataset.GroundTruthDataset attribute) (kraken.lib.dataset.PolygonGTDataset attribute) append() (kraken.lib.vgsl.TorchVGSLModel method) aug (kraken.lib.dataset.BaselineSet attribute) (kraken.lib.dataset.GroundTruthDataset attribute) (kraken.lib.dataset.PolygonGTDataset attribute)

B

base_dir (kraken.rpred.ocr_record attribute) BaselineSet (class in kraken.lib.dataset) beam_decoder() (in module kraken.lib.ctc_decoder) bidi_record() (in module kraken.rpred) bidi_reordering (kraken.rpred.mm_rpred attribute) blank_threshold_decoder() (in module kraken.lib.ctc_decoder) bounds (kraken.rpred.mm_rpred attribute) build_addition() (kraken.lib.vgsl.TorchVGSLModel method) build_conv() (kraken.lib.vgsl.TorchVGSLModel method)

build_dropout() (kraken.lib.vgsl.TorchVGSLModel method) build_groupnorm() (kraken.lib.vgsl.TorchVGSLModel method) build_identity() (kraken.lib.vgsl.TorchVGSLModel method) build_maxpool() (kraken.lib.vgsl.TorchVGSLModel method) build_output() (kraken.lib.vgsl.TorchVGSLModel method) build_parallel() (kraken.lib.vgsl.TorchVGSLModel method) build_reshape() (kraken.lib.vgsl.TorchVGSLModel method) build_rnn() (kraken.lib.vgsl.TorchVGSLModel method) build_series() (kraken.lib.vgsl.TorchVGSLModel method)

C

c_sorted (kraken.lib.codec.PytorchCodec attribute) calculate_polygonal_environment() (in module kraken.lib.segmentation) class_mapping (kraken.lib.dataset.BaselineSet attribute) class_stats (kraken.lib.dataset.BaselineSet attribute) codec (kraken.lib.models.TorchSeqRecognizer attribute) (kraken.lib.vgsl.TorchVGSLModel attribute)

compute_error() (in module kraken.lib.dataset) compute_polygon_section() (in module kraken.lib.segmentation) confidences (kraken.rpred.ocr_record attribute) criterion (kraken.lib.vgsl.TorchVGSLModel attribute), [1] cuts (kraken.rpred.ocr_record attribute)

D

decode() (kraken.lib.codec.PytorchCodec method) decoder (kraken.lib.models.TorchSeqRecognizer attribute)

denoising_hysteresis_thresh() (in module kraken.lib.segmentation) device (kraken.lib.models.TorchSeqRecognizer attribute)

E

encode() (kraken.lib.codec.PytorchCodec method) (kraken.lib.dataset.GroundTruthDataset method) (kraken.lib.dataset.PolygonGTDataset method)

eval() (kraken.lib.vgsl.TorchVGSLModel method) extract_polygons() (in module kraken.lib.segmentation)

F

fit() (kraken.lib.train.KrakenTrainer method)

font (kraken.transcribe.TranscriptionInterface attribute) forward() (kraken.lib.models.TorchSeqRecognizer method)

G

greedy_decoder() (in module kraken.lib.ctc_decoder)

GroundTruthDataset (class in kraken.lib.dataset)

H

height (kraken.lib.exceptions.KrakenCairoSurfaceException attribute), [1]

hyper_params (kraken.lib.vgsl.TorchVGSLModel property)

I

idx (kraken.lib.vgsl.TorchVGSLModel attribute) im (kraken.rpred.mm_rpred attribute) im_mode (kraken.lib.dataset.BaselineSet attribute) (kraken.lib.dataset.GroundTruthDataset attribute) (kraken.lib.dataset.PolygonGTDataset attribute)

imgs (kraken.lib.dataset.BaselineSet attribute) init_weights() (kraken.lib.vgsl.TorchVGSLModel method) input (kraken.lib.vgsl.TorchVGSLModel attribute), [1] is_valid (kraken.lib.codec.PytorchCodec property)

K

kind (kraken.lib.models.TorchSeqRecognizer attribute) KrakenCairoSurfaceException (class in kraken.lib.exceptions) KrakenCodecException (class in kraken.lib.exceptions) KrakenEncodeException (class in kraken.lib.exceptions) KrakenInputException (class in kraken.lib.exceptions)

KrakenInvalidModelException (class in kraken.lib.exceptions) KrakenRecordException (class in kraken.lib.exceptions) KrakenRepoException (class in kraken.lib.exceptions) KrakenStopTrainingException (class in kraken.lib.exceptions) KrakenTrainer (class in kraken.lib.train)

L

l2c (kraken.lib.codec.PytorchCodec attribute) line_idx (kraken.transcribe.TranscriptionInterface attribute) line_width (kraken.lib.dataset.BaselineSet attribute)

load_any() (in module kraken.lib.models) load_clstm_model() (kraken.lib.vgsl.TorchVGSLModel class method) load_model() (kraken.lib.vgsl.TorchVGSLModel class method) load_pronn_model() (kraken.lib.vgsl.TorchVGSLModel class method)

M

max_label (kraken.lib.codec.PytorchCodec property) mbl_dict (kraken.lib.dataset.BaselineSet attribute) merge() (kraken.lib.codec.PytorchCodec method) message (kraken.lib.exceptions.KrakenCairoSurfaceException attribute), [1]

mm_rpred (class in kraken.rpred) mode (kraken.lib.dataset.BaselineSet attribute) model_type (kraken.lib.vgsl.TorchVGSLModel property) mreg_dict (kraken.lib.dataset.BaselineSet attribute)

N

named_spec (kraken.lib.vgsl.TorchVGSLModel attribute) nets (kraken.rpred.mm_rpred attribute) nlbin() (in module kraken.binarization) nn (kraken.lib.models.TorchSeqRecognizer attribute) (kraken.lib.vgsl.TorchVGSLModel attribute), [1]

no_encode() (kraken.lib.dataset.GroundTruthDataset method) (kraken.lib.dataset.PolygonGTDataset method) num_classes (kraken.lib.dataset.BaselineSet attribute)

O

ocr_record (class in kraken.rpred) on_validation_end() (kraken.lib.train.KrakenTrainer method) one_channel_mode (kraken.lib.models.TorchSeqRecognizer attribute) (kraken.lib.vgsl.TorchVGSLModel attribute) (kraken.lib.vgsl.TorchVGSLModel property)

ops (kraken.lib.vgsl.TorchVGSLModel attribute)

P

pad (kraken.rpred.mm_rpred attribute) page_idx (kraken.transcribe.TranscriptionInterface attribute) pages (kraken.transcribe.TranscriptionInterface attribute) parse() (kraken.lib.dataset.GroundTruthDataset method) (kraken.lib.dataset.PolygonGTDataset method) parse_alto() (in module kraken.lib.xml) parse_page() (in module kraken.lib.xml) parse_xml() (in module kraken.lib.xml)

polygonal_reading_order() (in module kraken.lib.segmentation) PolygonGTDataset (class in kraken.lib.dataset) predict() (kraken.lib.models.TorchSeqRecognizer method) predict_labels() (kraken.lib.models.TorchSeqRecognizer method) predict_string() (kraken.lib.models.TorchSeqRecognizer method) prediction (kraken.rpred.ocr_record attribute) preparse_xml_data() (in module kraken.lib.dataset) PytorchCodec (class in kraken.lib.codec)

R

reading_order() (in module kraken.lib.segmentation) render_report() (in module kraken.serialization)

resize_output() (kraken.lib.vgsl.TorchVGSLModel method) rpred() (in module kraken.rpred)

S

save_model() (kraken.lib.vgsl.TorchVGSLModel method) scale_polygonal_lines() (in module kraken.lib.segmentation) scale_regions() (in module kraken.lib.segmentation) seg_idx (kraken.transcribe.TranscriptionInterface attribute) seg_type (kraken.lib.dataset.BaselineSet attribute) (kraken.lib.dataset.GroundTruthDataset attribute) (kraken.lib.dataset.PolygonGTDataset attribute) (kraken.lib.models.TorchSeqRecognizer attribute) (kraken.lib.vgsl.TorchVGSLModel property)

segment() (in module kraken.blla) (in module kraken.pageseg) serialize() (in module kraken.serialization) serialize_segmentation() (in module kraken.serialization) set_num_threads() (kraken.lib.vgsl.TorchVGSLModel method) spec (kraken.lib.vgsl.TorchVGSLModel attribute) split (kraken.lib.dataset.GroundTruthDataset attribute) strict (kraken.lib.codec.PytorchCodec attribute) suffix (kraken.lib.dataset.GroundTruthDataset attribute)

T

tags (kraken.rpred.ocr_record attribute) tags_ignore (kraken.rpred.mm_rpred attribute) targets (kraken.lib.dataset.BaselineSet attribute) text_direction (kraken.transcribe.TranscriptionInterface attribute) text_transforms (kraken.lib.dataset.GroundTruthDataset attribute) (kraken.lib.dataset.PolygonGTDataset attribute) tmpl (kraken.transcribe.TranscriptionInterface attribute) to() (kraken.lib.models.TorchSeqRecognizer method) (kraken.lib.vgsl.TorchVGSLModel method) TorchSeqRecognizer (class in kraken.lib.models)

TorchVGSLModel (class in kraken.lib.vgsl) train (kraken.lib.models.TorchSeqRecognizer attribute) train() (kraken.lib.vgsl.TorchVGSLModel method) TranscriptionInterface (class in kraken.transcribe) transform() (kraken.lib.dataset.BaselineSet method) transforms (kraken.lib.dataset.BaselineSet attribute) (kraken.lib.dataset.GroundTruthDataset attribute) (kraken.lib.dataset.PolygonGTDataset attribute) ts (kraken.rpred.mm_rpred attribute) type (kraken.rpred.ocr_record attribute)

U

user_metadata (kraken.lib.vgsl.TorchVGSLModel attribute), [1]

V

valid_baselines (kraken.lib.dataset.BaselineSet attribute)

valid_regions (kraken.lib.dataset.BaselineSet attribute) vectorize_lines() (in module kraken.lib.segmentation)

W

width (kraken.lib.exceptions.KrakenCairoSurfaceException attribute), [1]

write() (kraken.transcribe.TranscriptionInterface method)