Create and manage a digital catalog of cat fur patterns with features for adding, categorizing, searching, and viewing detailed information and images. Ideal for cat enthusiasts, breeders, and veterinarians.
The Cat Fur Pattern Tracker is a digital catalog application designed to help cat enthusiasts, breeders, and veterinarians document and organize various cat fur patterns. This tool allows users to add new patterns with detailed descriptions and images, categorize them, search for specific patterns, and view a grid of saved patterns with thumbnail images. The app provides a user-friendly interface for managing a comprehensive database of cat fur patterns, which can be valuable for breed identification, genetic studies, and aesthetic appreciation of feline diversity.
Adding a New Pattern:
Searching for Patterns:
Viewing Patterns:
Managing Patterns:
Cat fur patterns are typically categorized into several main groups:
The app allows for flexible categorization to accommodate various classification systems used by different cat associations and breed standards.
The Cat Fur Pattern Tracker employs several techniques to enable efficient pattern matching and searching:
Text-based search:
Category-based filtering:
Image-based search (advanced feature):
Tagging system:
The search functionality is designed to be fast and responsive, providing real-time results as the user types their query.
To ensure optimal performance and user experience, the Cat Fur Pattern Tracker adheres to the following image handling guidelines:
The Cat Fur Pattern Tracker has various applications in the feline world:
Breed Identification: Helps cat owners and enthusiasts identify potential breed matches based on fur patterns.
Genetic Studies: Assists researchers in documenting and analyzing the inheritance of fur patterns across generations.
Cat Shows and Competitions: Provides a reference for judges and participants to compare and evaluate cat coat patterns.
Veterinary Records: Allows veterinarians to maintain detailed records of patients' coat patterns, which can be useful for identification and tracking changes over time.
Animal Shelters: Helps shelter staff accurately describe and catalog rescued cats, potentially increasing adoption rates.
Educational Tool: Serves as a learning resource for students and the general public interested in feline genetics and diversity.
While the Cat Fur Pattern Tracker is specialized for feline coat patterns, there are other pet-related cataloging systems:
General Pet Photo Albums: Apps that allow users to organize photos of their pets without specific focus on coat patterns.
Breed Identification Apps: Tools that use AI to identify dog or cat breeds based on photos, but may not specialize in fur patterns.
Veterinary Management Software: Comprehensive systems for managing pet health records, which may include basic coat information.
Wildlife Tracking Apps: Applications designed for identifying and cataloging wild animals, which may include some domestic cat data.
The study and classification of cat fur patterns have evolved alongside the development of cat fancy and genetics:
Here are some code examples demonstrating key functionalities of the Cat Fur Pattern Tracker:
1// Example of adding a new cat fur pattern
2function addNewPattern(name, description, category, imageUrl) {
3 const pattern = {
4 id: Date.now().toString(),
5 name,
6 description,
7 category,
8 imageUrl
9 };
10
11 patterns.push(pattern);
12 savePatterns();
13 renderPatternGrid();
14}
15
16// Example of searching for patterns
17function searchPatterns(query) {
18 return patterns.filter(pattern =>
19 pattern.name.toLowerCase().includes(query.toLowerCase()) ||
20 pattern.category.toLowerCase().includes(query.toLowerCase())
21 );
22}
23
24// Example of rendering the pattern grid
25function renderPatternGrid() {
26 const grid = document.getElementById('pattern-grid');
27 grid.innerHTML = '';
28
29 patterns.forEach(pattern => {
30 const tile = document.createElement('div');
31 tile.className = 'pattern-tile';
32 tile.innerHTML = `
33 <img src="${pattern.imageUrl}" alt="${pattern.name}">
34 <h3>${pattern.name}</h3>
35 <p>${pattern.category}</p>
36 `;
37 tile.addEventListener('click', () => showPatternDetails(pattern));
38 grid.appendChild(tile);
39 });
40}
41
42// Example of showing pattern details
43function showPatternDetails(pattern) {
44 const modal = document.getElementById('pattern-modal');
45 modal.innerHTML = `
46 <img src="${pattern.imageUrl}" alt="${pattern.name}">
47 <h2>${pattern.name}</h2>
48 <p>Category: ${pattern.category}</p>
49 <p>${pattern.description}</p>
50 <button onclick="closeModal()">Close</button>
51 `;
52 modal.style.display = 'block';
53}
541# Example of image processing for pattern matching
2import cv2
3import numpy as np
4
5def compare_patterns(image1, image2):
6 # Convert images to grayscale
7 gray1 = cv2.cvtColor(image1, cv2.COLOR_BGR2GRAY)
8 gray2 = cv2.cvtColor(image2, cv2.COLOR_BGR2GRAY)
9
10 # Compute histograms
11 hist1 = cv2.calcHist([gray1], [0], None, [256], [0, 256])
12 hist2 = cv2.calcHist([gray2], [0], None, [256], [0, 256])
13
14 # Compare histograms
15 similarity = cv2.compareHist(hist1, hist2, cv2.HISTCMP_CORREL)
16
17 return similarity
18
19# Usage
20image1 = cv2.imread('pattern1.jpg')
21image2 = cv2.imread('pattern2.jpg')
22similarity = compare_patterns(image1, image2)
23print(f"Pattern similarity: {similarity}")
24These examples demonstrate basic functionality for adding patterns, searching, displaying a grid of patterns, showing detailed views, and comparing patterns using image processing techniques.
Classic Tabby:
Tuxedo:
Tortoiseshell:
Colorpoint:
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