NVision Demo

Watch a demonstration of the NVision Python program

Demo Video
Watch a demonstration of NVision in action
Download NVision
Get the NVision software from GitHub

NVision is available as a Python package that you can download from our GitHub repository. The package includes:

  • Core NVision detection algorithm
  • Visualization tools for FSM scan data
  • Example datasets and scripts
  • Comprehensive documentation

System Requirements

  • Python 3.7 or higher
  • NumPy, SciPy, Matplotlib
  • scikit-image for peak detection
Download from GitHub

How NVision Works

NVision is a Python-based algorithm designed to identify Nitrogen-Vacancy (NV) centers in Fluorescence Scanning Microscopy (FSM) scans of diamond samples. The software processes JSON-formatted scan data through several key steps:

Key Features

  • 1

    Data Import

    Loads FSM scan data from JSON files containing scan counts and position information.

  • 2

    Noise Reduction

    Applies Gaussian filtering to reduce noise while preserving signal features

  • 3

    Peak Detection

    Identifies local maxima using statistical thresholding to locate NV centers

  • 4

    Visualization

    Generates comprehensive plots showing original data, processed data, and detected centers

Getting Started

# Basic usage of NVision
import json
from nvision import detect_nv_centers, visualize_results

# Load FSM scan data
with open('fsm_scan.json', 'r') as f:
    data = json.load(f)

# Detect NV centers
results = detect_nv_centers(
    data, 
    threshold_factor=2.5,
    min_distance=10
)

# Print detection results
print(f"Detected {len(results['coordinates'])} NV centers")
print(f"Threshold: {results['threshold']:.1f} counts/s")

# Visualize the results
fig = visualize_results(data, results)
fig.savefig('nv_centers_analysis.png')