How to Copy Any Art Style From a Single Image (Complete Guide)

Want to recreate a specific art style but only have one reference image? You don’t need dozens of examples or complex training. A single high-quality reference contains enough visual information to build a reusable style template.

This guide gives you a practical, step-by-step method for extracting style from any image and turning it into a reliable prompt that works across different subjects.

Step 1: Pick a Reference Image That Actually Works

Your reference image determines your success. Choose wisely:

What to look for: Choose a clear, consistent style shot with one visual technique throughout (no mixed media), high resolution (minimum 512x512px, ideally 1024x1024px or higher), visible details like brush strokes and line work, strong lighting with clear shadows and highlights, and a simple subject that isolates style from content.

Avoid: Photographs of physical artwork with creases or reflections, overly complex scenes with conflicting techniques, and watermarked or heavily compressed images.

Pro tip: Save the image with a descriptive filename (e.g., “watercolor-botanical-ref.jpg”) and note where you found it. You’ll want to track your sources.

Step 2: Break Down the 6 Core Style Elements

Look past the subject matter and identify these six visual signals:

1. Line Quality

Document line thickness (0.5pt thin, 2pt medium, 5pt bold), consistency (uniform width vs varied pressure), texture (smooth, rough, jagged, or broken), and edge definition (sharp vs soft).

2. Color Palette

Note color count (3-5 colors vs 20+), temperature (warm reds/oranges vs cool blues/greens), saturation (muted/pastel vs vibrant/neon), contrast (high black/white vs low gray/gray), and dominant colors.

3. Shading Technique

Identify the style (flat, cel-shaded, gradient, cross-hatch, stippling), light direction (consistent source vs ambient), and intensity (subtle vs dramatic chiaroscuro).

4. Texture & Surface

Observe digital textures (smooth vector, pixel art, noise) or traditional surfaces (canvas weave, paper grain, brush strokes), plus scale (fine detail vs broad strokes) and density.

5. Composition

Study framing (tight crop vs generous negative space), perspective (eye-level, bird’s eye, extreme angles), and depth (flat layers vs strong foreground/background separation).

6. Medium & Technique

Recognize digital approaches (3D render, vector illustration, pixel art) or traditional media (oil paint, watercolor, ink, colored pencil, collage), plus era/style cues like Art Nouveau or 80s airbrush.

Action step: Write each observation as specific bullet points. Instead of “soft lines,” write “lines with textured edges, varied thickness 1-3pt.”

Step 3: Build Your JSON Style Template

Convert your observations into a structured JSON template from the start:

{
  "preset_name": "Watercolor Botanical Style",
  "description": "Based on botanical watercolor with ink outlines",
  "subject": "{subject}",
  "positive_prompt": "{subject}, watercolor illustration, delicate ink outlines with thin consistent lines, muted green and brown palette with one accent color, soft gradient washes, visible paper grain and watercolor bleed, soft ambient lighting from above, centered composition on white background",
  "negative_prompt": "photorealistic, digital smooth, harsh shadows, neon colors, signature, watermark, text, low quality, blurry",
  "technical_settings": {
    "image_size": "1024x1024",
    "reference_image": "watercolor-botanical-ref.jpg"
  }
}

JSON structure explained:

• preset_name: Clear identifier for your style
• description: What the style is based on
• subject: Use {subject} as a variable placeholder
• positive_prompt: The complete prompt with subject slot
• negative_prompt: What to avoid (add to this as you test)
• technical_settings: Image requirements and reference tracking

Key principle: Build the JSON template immediately rather than writing a text prompt first. This keeps your style organized and reusable from day one.

Step 4: Use Your Reference as a Style Anchor

Most AI tools support reference images. Upload the reference to your tool’s “style reference” or “image prompt” field, add your positive_prompt and negative_prompt from the JSON template, and lock the seed value for consistent testing if needed.

Test sequence: Generate with reference image + your JSON prompts. If style is too weak, make your positive prompt more specific. If it’s copying the subject too literally, add subject-specific negatives. Always adjust one variable at a time.

Step 5: Document and Test Your Template

A JSON template only works if you test it thoroughly. Update your JSON with test information:

{
  "preset_name": "Watercolor Botanical Style",
  "testing": {
    "test_subjects": [
      "raven",
      "teacup",
      "elderly woman",
      "mountain lake",
      "joy"
    ],
    "evaluation_criteria": [
      "color_palette",
      "line_quality",
      "texture",
      "lighting",
      "mood"
    ],
    "status": "in_testing"
  }
}

Test set: Use an animal (e.g., “raven”), object (e.g., “teacup”), portrait (e.g., “elderly woman”), landscape (e.g., “mountain lake”), and abstract concept (e.g., “joy”).

Evaluation checklist:

• Color palette matches your reference
• Line quality is consistent
• Texture appears in all generations
• Lighting direction is uniform
• Overall mood matches the original

If your style breaks, update your JSON:

{
  "issues": [
    {
      "problem": "Color drift on abstract subjects",
      "fix": "Added specific hex codes to positive_prompt",
      "date": "2026-01-24"
    }
  ]
}

Tool: Speed Up Style Extraction

The tool below analyzes your reference image and generates a complete JSON preset with color palette, descriptive keywords, and a ready-to-use template.

Common Problems & Solutions

“The style keeps drifting between generations” Your prompt is too vague. Add specific measurements (line weight in points, color hex codes, texture scale), lock your seed value during testing, and make your positive prompt more descriptive.

“It keeps copying the specific subject from my reference” Add subject-specific negatives to your JSON template, increase specificity of your positive prompt, and test with a different reference image.

“Colors are wrong” Extract actual hex codes from your reference, add color count limits (“exactly 5 colors”) to your positive prompt, and add unwanted hues to negative_prompt.

“Textures are inconsistent” Describe texture scale: “large visible brush strokes” vs. “fine paper grain”. Add material specifications: “canvas texture” vs. “smooth paper”. Specify texture location: “texture visible in background only”.

“Style works on some subjects but not others” Your style may have subject bias (common with portraits). Test with minimum viable prompt (remove non-essential descriptors), and create separate JSON templates for different subject categories.

Ethical Guidelines & Best Practices

Respect the source: Use references as technique guides, not for copying specific artworks. Credit inspiration sources when sharing your work. Never use copyrighted works for commercial style replication without permission. Build a personal reference library from public domain or licensed sources.

Focus on technique, not identity: Study “watercolor technique” not “Van Gogh style”. Describe visual elements, not artist names. Transform and combine multiple influences.

Document your process: Keep a style journal with reference images and successful JSON presets. Track what works and what doesn’t. Share your methodology, not just your results.

Key Takeaway

A single reference image contains complete style data if you know how to extract it. The process is systematic: observe precisely, describe literally, test methodically, and document thoroughly in JSON.

Your style template becomes a reusable asset. Once built, it generates consistent results across any subject - no luck required.

Start with one strong reference today, and you’ll have a style preset you can use for months to come.