DALAI-project

CornerAPI

API for a machine learning model trained to detect folded or torn corners and edges from scanned document images.

Document_segmentation

A model for segmenting scanned document images.

EmptyAPI

API for detecting empty document images

PostitAPI

API for a machine learning model trained to detect post-it/sticky notes from scanned document images.

.github

Arkkiivi_UI

User interface for Arkkiivi web application

Document-analysis_API

This API use Annif as local server, NER component is included. It also includes Tesseract and uses Apache-tika software for language detection. It also has a limited multilingual support.

Empty_training

Training code for a deep learning model that detects empty document from images.

FaultyImageAPI

API that combines empty page, post-it, folded corner and writing type detection models.

NER_API

API for performing named entity recognition from text input in Finnish.

Table_segmentation

Code for segmenting table structures and detecting text content in document images.

Train_BERT_NER

Code for training Finnish named entity recognition (NER) model based on BERT.

Train_writing_type

Training code for a deep learning model that detects document writing type from images.

WritingtypeAPI

Repo for writingtype classifier API

Annif_API

Instructions and pretrained models for using Annif (https://annif.org/) software for automatic subject indexing as local service.

Train_document_classification

Code that can be used for training a neural network model to classify input documents into distinct classes.

Train_fault_detection

Code that can be used for training a neural network model to detect faults (sticky notes, folded corners etc.) in input documents.