Visual Layer - Getting Started Guide

Welcome to Visual Layer! This guide will help you quickly get started with using Visual Layer's API and tools for visual data management. Below, you'll find links to Jupyter notebooks that demonstrate different functionalities.

Finding and Exporting data:

1. Image Search via API

This notebook demonstrates how to use the Visual Layer API to search for images based on similarity.

• 📘 Visual Layer API Example

2. Parse Exported JSON into CSV

If you need to process metadata exported from Visual Layer, this notebook helps convert JSON files into CSV format.

• 📘 Parse JSON Export
• 📘 Parse Image Data, Duplicates and Mislabels

3. Export Data via API

These notebooks show how to extract data using Visual Layer's API.

• 📘 API Simplified Python

Preparing Visual Layer input data:

4. Creating Input Bounding Box Data: from voc2012 to Visual Layer Objec Detection

• 📘 VL Bounding Boxes

This tutorial explains how to convert XML annotations into a Visual Layer Bounding Box format. The script provided parses a fixed XML string and extracts object detection bounding boxes, storing them in a CSV file.

How to Use

1. Download the repository or access the notebooks directly.
2. Open the .ipynb files in Jupyter Notebook or JupyterLab.
3. Follow the instructions in each notebook to execute the code and interact with Visual Layer.

Requirements

• Python 3.8+
• Jupyter Notebook or JupyterLab
• Required dependencies (listed in each notebook)

Support

For any questions, feel free to reach out to our support team or check our documentation.

Happy coding! 🚀