Elevate Your Living Space with Data-Driven Interior Design

import numpy as np
from PIL import Image

def analyze_color_palette(image_path):
    img = Image.open(image_path)
    img = img.convert('RGB')
    pixels = np.array(img)
    dominant_color = np.mean(pixels, axis=(0, 1))
    return dominant_color

# Example usage:
image_path = 'path/to/image.jpg'
dominant_color = analyze_color_palette(image_path)
print(dominant_color)

class Graph {
  constructor() {
    this.vertices = {};
  }

  addVertex(vertex) {
    this.vertices[vertex] = {};
  }

  addEdge(vertex1, vertex2) {
    this.vertices[vertex1][vertex2] = 1;
  }

  dijkstra(start) {
    const distances = {};
    const previous = {};

    for (const vertex in this.vertices) {
      distances[vertex] = Infinity;
      previous[vertex] = null;
    }

    distances[start] = 0;

    const queue = [start];

    while (queue.length > 0) {
      const vertex = queue.shift();

      for (const neighbor in this.vertices[vertex]) {
        const distance = distances[vertex] + this.vertices[vertex][neighbor];

        if (distance < distances[neighbor]) {
          distances[neighbor] = distance;
          previous[neighbor] = vertex;
          queue.push(neighbor);
        }
      }
    }

    return distances;
  }
}

// Example usage:
const graph = new Graph();
graph.addVertex('A');
graph.addVertex('B');
graph.addEdge('A', 'B');
const distances = graph.dijkstra('A');
console.log(distances);