# Document_Layout_Analysis-MonkAI

**Repository Path**: zetingh/Document_Layout_Analysis-MonkAI

## Basic Information

- **Project Name**: Document_Layout_Analysis-MonkAI
- **Description**: DL models that take a document image file as input, locate the position of paragraphs, lines, images, etc. with their labels and confidence scores.
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-03-09
- **Last Updated**: 2021-03-09

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Document Layout Detection using MonkAI Object Detection Library

Deep learning models that take a document image file as input, locate the position of paragraphs, lines, images, etc. with their labels and confidence scores.

## Choice of architecture
-Inspiration from the blog- https://medium.com/@Intellica.AI/a-comparative-study-of-custom-object-detection-algorithms-9e7ddf6e765e

Yolov3, FasterRCNN & SSD are broadly top 3 model architectures that are used for Object detection. So, for this task, prediction and confidence on inference images of these 3 architectures have been compared.


# Tutorial Blog
https://medium.com/@swapnil.ahlawat/object-detection-document-layout-analysis-using-monk-object-detection-toolkit-6c57200bde5