Proof of concept of training a simple Region Classifier using PdfPig and ML.NET (LightGBM). The objective is to classify each text block in a pdf document page as either title, text, list, table and image.
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Updated
Mar 16, 2020 - C#
Proof of concept of training a simple Region Classifier using PdfPig and ML.NET (LightGBM). The objective is to classify each text block in a pdf document page as either title, text, list, table and image.
Detectron2 for Document Layout Analysis
ICDAR 2019: MaskRCNN on PubLayNet datasets. Paragraph detection, table detection, figure detection,...
Vision Based Document Layout Detection, Segmentation and context classification using MaskRCNN on Tensorflow-Keras, PyTorch & Detectron2.
Proof of concept of a simple SVM Region Classifier using PdfPig and Accord.Net. The objective is to classify each text block in a pdf document page as either title, text, list, table and image.
Trained Detectron2 object detection models for document layout analysis based on PubLayNet dataset
Trained Detectron2 object detection models for document layout analysis based on PubLayNet dataset
Using a MaskRCNN model trained on the PublayNet dataset with ML.Net in C# / .Net for Document layout analysis and page segmmentation task.
Diffusion Layout Transformer implementation.
PubLayNet for huggingface datasets
🔄 A tool for object detection and image segmentation dataset format conversion.
A Repo For Document AI
Integrate AI-powered Document Analysis Pipelines
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