Getting Started

This guide will help you install and start using ImgVisFeat.

Installation

Requirements

• Python >= 3.10

Install from PyPI

Install ImgVisFeat using pip:

pip install ImgVisFeat

Verify Installation

Verify that ImgVisFeat is installed correctly:

import imvf
print(imvf.__version__)

Quick Start

Using the All-in-One Visualizer

The simplest way to use ImgVisFeat is with the Visualizer class, which applies all visualization methods:

import imvf

# Create visualizer instance
visualizer = imvf.Visualizer()

# Visualize all features and save results
visualizer.visualize("path/to/image.jpg")

This will:

1. Display all visualizations in OpenCV windows
2. Save the results to a directory named after the image (e.g., path/to/image/)

Using Individual Visualizers

For more control, use individual visualizers:

import cv2
import imvf

# Load image
image = cv2.imread("path/to/image.jpg")

# Color channel visualization
color_visualizer = imvf.ColorChannelVisualizer()
result = color_visualizer(image)

# Access individual channels
cv2.imshow("Blue Channel", result.blue)
cv2.imshow("Green Channel", result.green)
cv2.imshow("Red Channel", result.red)
cv2.waitKey(0)

Using the Command Line Interface

ImgVisFeat provides a CLI for quick visualizations:

# Visualize all features
imvf path/to/image.jpg

# Visualize specific method
imvf path/to/image.jpg --method hog

Available methods:

• all - All visualization methods (default)
• color_channel - RGB channel visualization
• gradient - Gradient visualization
• hog - Histogram of Oriented Gradients
• lbp - Local Binary Patterns
• keypoint - Keypoint detection (SIFT, AKAZE, ORB)
• power_spectrum - Power spectrum analysis

Next Steps

• Explore the User Guide for detailed usage of each visualizer
• Check the CLI Reference for command-line options
• Browse the API Reference for complete documentation

Troubleshooting

Import Error

If you encounter import errors, ensure that:

1. ImgVisFeat is installed in your current environment
2. You're using Python >= 3.10
3. All dependencies are installed

OpenCV Display Issues

If images don't display:

1. Ensure you have a GUI backend available
2. Add cv2.waitKey(0) after cv2.imshow() calls
3. Use cv2.destroyAllWindows() to close all windows

Getting Help

If you encounter issues:

1. Check the documentation
2. Search existing GitHub issues
3. Open a new issue with details about your problem