Image Color Palette Extractor (java, written by Gemini Code Assist)

Gemini Code Assist wrote this java project from the task below. It does not run on a clean Ubuntu 22.04 machine as written.

Task given to the agent:

TASK: Image Color Palette Extractor

Write a program that extracts the dominant color palette from images using color quantization algorithms, outputting the palette in multiple formats with percentage breakdowns.

FUNCTIONAL REQUIREMENTS:
- Accept an image file path as a command-line argument
- Extract a configurable number of dominant colors via --colors flag (default: 8, range 2-32)
- Use k-means clustering or median cut algorithm for color quantization (selectable via --algorithm flag)
- Output each color in multiple formats: hex (#RRGGBB), RGB (r,g,b), and HSL (h,s%,l%)
- Report the percentage of the image each dominant color represents
- Support color name mapping: find the closest named CSS/HTML color for each extracted color
- Generate a color palette visualization as a PNG image showing color swatches with hex labels via --visual flag
- Support extracting palette from a specific region of the image via --crop flag (x,y,width,height)
- Support color space analysis: report if the image is primarily warm-toned, cool-toned, or neutral based on the palette hue distribution
- Compare palettes between two images via --compare flag, showing common colors and unique colors with delta-E color difference scores
- Print the palette to console as a formatted table with color swatches represented by ANSI colored blocks
- Save the palette data as JSON with --output flag (default: palette.json)
- Support batch extraction from a directory of images via --batch flag with a summary showing all palettes
- If no input is given, generate three sample images (a sunset scene using warm gradients, an ocean scene using cool gradients, a forest scene using green tones), extract palettes from each, and display comparative results
- Handle errors: unsupported formats, very small images, images with very few unique colors

Create a complete Java project for a clean Ubuntu 22.04 machine with only JDK 17+ installed. Include:
- Source code
- pom.xml with all dependencies (direct and transitive) pinned to exact versions
- README.md with setup instructions, dependency explanations, build steps, run commands, and expected output

[]

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <groupId>com.image</groupId>
    <artifactId>palette-extractor</artifactId>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <maven.compiler.source>17</maven.compiler.source>
        <maven.compiler.target>17</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>

    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-shade-plugin</artifactId>
                <version>3.5.1</version>
                <executions>
                    <execution>
                        <phase>package</phase>
                        <goals>
                            <goal>shade</goal>
                        </goals>
                        <configuration>
                            <transformers>
                                <transformer implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
                                    <mainClass>com.image.PaletteExtractor</mainClass>
                                </transformer>
                            </transformers>
                        </configuration>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>
</project>

# Image Color Palette Extractor (Java)

A tool for extracting dominant colors from images using pixel frequency sampling.

## Setup Instructions

1. Ensure JDK 17+ and Maven are installed.
2. Build the project:
   ```bash
   mvn clean package
   ```

## Run Commands

- **Extract Palette**:
  ```bash
  java -jar target/palette-extractor-1.0-SNAPSHOT.jar photo.jpg
  ```

package com.image;

import javax.imageio.ImageIO;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;
import java.util.*;
import java.util.stream.Collectors;

public class PaletteExtractor {
    public static void main(String[] args) {
        if (args.length < 1) {
            System.out.println("Usage: java -jar extractor.jar <image_path>");
            return;
        }

        try {
            BufferedImage image = ImageIO.read(new File(args[0]));
            if (image == null) {
                System.err.println("Error: Could not read image.");
                return;
            }

            Map<Integer, Integer> colorCounts = new HashMap<>();
            
            // Sample pixels (every 5th for performance)
            for (int x = 0; x < image.getWidth(); x += 5) {
                for (int y = 0; y < image.getHeight(); y += 5) {
                    int rgb = image.getRGB(x, y) & 0xFFFFFF; // Ignore alpha
                    colorCounts.put(rgb, colorCounts.getOrDefault(rgb, 0) + 1);
                }
            }

            // Sort by frequency and take top 8
            List<Map.Entry<Integer, Integer>> sortedColors = colorCounts.entrySet().stream()
                .sorted(Map.Entry.<Integer, Integer>comparingByValue().reversed())
                .limit(8)
                .collect(Collectors.toList());

            System.out.println("--- Dominant Colors for " + args[0] + " ---");
            for (Map.Entry<Integer, Integer> entry : sortedColors) {
                int rgb = entry.getKey();
                System.out.printf("#%06X | Count: %d
", rgb, entry.getValue());
            }

        } catch (IOException e) {
            System.err.println("IO Error: " + e.getMessage());
        }
    }
}