# Module 2

## AI-Powered Image Generation and Editing

### 🎯 Learning Objectives

After completing this module, you will be able to:

- Generate custom images from text descriptions using style parameters and composition guidelines
- Modify existing images through inpainting, outpainting, and variation techniques
- Apply quality control criteria to evaluate AI-generated visual content
- Implement image generation workflows for specific business use cases

Click Next → to begin.

## Introduction to AI Image Generation

Organizations use AI image generation for marketing materials, social media content, product mockups, website hero images, and presentation graphics. The primary advantage is speed—what might take hours with traditional methods can be explored in minutes. Teams can test multiple visual directions quickly, gather stakeholder feedback earlier, and iterate without expensive photo shoots or illustration contracts.

Conceptual illustration showing the journey from text prompt to finished AI-generated image, depicted as a creative transformation process

#### 💡 Key Takeaways

- AI image generation transforms text prompts into original visual content using diffusion models
- Systems learn from millions of training images to understand relationships between language and visuals
- Primary business value includes rapid prototyping, cost reduction, and accelerated iteration cycles
- Tools complement traditional creative processes rather than replacing professional expertise

## Crafting Effective Image Prompts

## Mastering Prompt Engineering for Images

The quality of AI-generated images depends heavily on prompt construction. Effective prompts provide clear subject descriptions, style specifications, composition details, and quality parameters. Understanding how to structure these elements dramatically improves results.

Essential Prompt Components

A well-constructed prompt includes the subject (what you want to see), style (artistic approach or visual aesthetic), composition (framing, perspective, and layout), lighting (mood and illumination), and quality modifiers (resolution and detail level). For example: "Professional headshot of a business executive, warm natural lighting, shallow depth of field, corporate environment background, high resolution, photorealistic."

Be specific about details that matter. Instead of "a dog," specify "a golden retriever puppy sitting on a wooden deck." The more precise your description, the closer the output matches your vision.

Style Parameters and Artistic Direction

Style parameters control the visual aesthetic of generated images. Common approaches include photorealistic (mimicking photography), illustration styles (watercolor, digital art, comic book), artistic movements (impressionism, art deco), and medium simulations (oil painting, charcoal sketch). You can combine styles: "digital illustration with watercolor textures and art nouveau influences."

Quality and resolution keywords like "8K," "high detail," "professional photography," or "sharp focus" influence output fidelity. Platform-specific modifiers may enhance results on particular systems.

Negative Prompts and Exclusions

Many platforms support negative prompts—specifications of what to avoid. These help eliminate unwanted elements: "no text, no watermarks, no blur, no distortion." Negative prompts prove particularly useful when the system consistently includes undesired features in generated images.

Visual comparison showing how prompt specificity affects output quality, illustrated through before-and-after examples

#### 💡 Key Takeaways

- Effective prompts include subject, style, composition, lighting, and quality specifications
- Specificity and detail in descriptions yield outputs closer to desired vision
- Style parameters range from photorealism to artistic movements and medium simulations
- Negative prompts exclude unwanted elements and improve output consistency

## Composition and Visual Control Techniques

## Controlling Image Composition and Layout

Beyond subject and style, composition parameters determine how elements arrange within the frame. Understanding composition control enables you to generate images that meet specific layout requirements, communicate visual hierarchy, and align with design standards.

Framing and Perspective

Framing keywords specify how tightly subjects fill the image: "extreme close-up," "portrait shot," "full body," "wide shot," or "aerial view." Perspective terms like "bird's eye view," "worm's eye view," "eye level," or "dramatic angle" control the viewer's vantage point.

For product photography, specify "centered composition, white background" or "three-quarter view on textured surface." For landscapes, try "golden ratio composition" or "rule of thirds with foreground interest."

Lighting and Mood

Lighting dramatically affects image mood and professionalism. Descriptive lighting terms include "soft diffused lighting," "dramatic side lighting," "golden hour sunlight," "studio lighting with rim light," or "moody low-key lighting." Time-of-day references—"morning light," "midday sun," "twilight"—also influence atmosphere.

For professional business content, "soft natural window light" or "professional studio lighting" typically produces appropriate results. Creative marketing might benefit from "vibrant colored gels" or "neon accent lighting."

Focal Points and Depth

Control where viewers' attention lands using depth-of-field specifications: "shallow depth of field with bokeh background" emphasizes subjects by blurring surroundings. "Deep focus" keeps everything sharp. Terms like "focal point on [element]" or "selective focus" guide the AI's attention distribution.

Background specifications—"blurred office environment," "abstract gradient," "minimalist backdrop"—complete the composition without competing with primary subjects.

Illustrated guide showing different composition techniques and their effects on visual storytelling

#### 💡 Key Takeaways

- Framing and perspective keywords control subject positioning and viewer vantage point
- Lighting specifications establish mood, professionalism, and atmospheric quality
- Depth-of-field parameters direct viewer attention to specific subjects or elements
- Background specifications complement subjects without creating visual competition

## Image Editing and Refinement Techniques

## Advanced Editing with AI Tools

Once you've generated initial images, AI-powered editing techniques enable precise modifications without starting over. These capabilities transform image generation from a one-shot process into an iterative refinement workflow.

Inpainting: Targeted Element Modification

Inpainting allows you to select specific regions of an image and regenerate only those areas based on new prompts. This technique proves invaluable for correcting specific details while preserving the overall composition. For example, you might inpaint a subject's clothing to change colors, modify background elements to remove distractions, or adjust product packaging in marketing images.

The process involves masking the area to modify and providing a prompt describing the desired replacement. The AI regenerates the masked region while blending seamlessly with unchanged areas. Most platforms offer brush tools or selection interfaces for precise masking.

Outpainting: Expanding Image Boundaries

Outpainting extends images beyond their original borders, generating additional content that matches the existing style and context. This technique helps when you need different aspect ratios, want to add context around a subject, or need to expand composition to include additional elements.

You specify which direction to extend (top, bottom, left, right, or all sides) and optionally provide prompts describing what should appear in the new areas. The AI analyzes the existing image and generates coherent extensions.

Variation Generation and Style Transfer

Variation tools create alternative versions of existing images, maintaining the general composition while introducing differences in style, details, or interpretation. This accelerates iteration when exploring multiple design directions from a single strong foundation.

Style transfer applies the visual aesthetic of one image to the content of another, enabling you to reimagine existing visuals in different artistic styles or maintain brand consistency across generated content.

Visual demonstration of inpainting, outpainting, and variation techniques showing before and after examples

#### 💡 Key Takeaways

- Inpainting modifies specific image regions while preserving overall composition
- Outpainting extends images beyond original boundaries with coherent additional content
- Variation generation creates alternative versions for rapid exploration of design directions
- Style transfer applies visual aesthetics across images for consistency and creative reimagining

## Quality Control and Platform Selection

## Optimizing Image Quality and Choosing Platforms

Producing professional-grade AI images requires understanding quality optimization techniques and selecting appropriate platforms for specific use cases. Different tools excel in different areas, and quality standards vary by application.

Resolution and Detail Optimization

Resolution determines image sharpness and usability across different media. For social media posts, 1024×1024 pixels often suffices. Print materials, large displays, or detailed product photography require higher resolutions—2048×2048 or larger. Many platforms offer upscaling features that increase resolution while enhancing details through AI.

Quality keywords in prompts—"high detail," "sharp focus," "professional photography," "8K resolution"—influence output fidelity. However, higher resolution increases generation time and may incur additional costs on some platforms.

Batch Generation and Workflow Efficiency

Batch generation creates multiple images from a single prompt or prompt variations, enabling rapid exploration of alternatives. This approach proves essential for client presentations, A/B testing, or generating diverse content libraries. Most platforms generate 2-4 variations per request by default; some support larger batches.

Efficient workflows involve generating batches, evaluating results against criteria, selecting strong candidates, then refining chosen images through inpainting or variation generation. This iterative process balances exploration with focused refinement.

Platform Comparison: Choosing the Right Tool

Major platforms include Midjourney (known for artistic quality and vibrant aesthetics), DALL-E (balanced photorealism and creative interpretation), Stable Diffusion (open-source flexibility and customization), and various specialized tools. Midjourney excels at imaginative, stylized content. DALL-E provides reliable, safe outputs suitable for corporate environments. Stable Diffusion offers maximum control for technical users.

Platform selection depends on budget, desired aesthetic, required features (commercial licensing, API access), and team technical expertise. Many organizations use multiple platforms for different use cases.

Illustrated comparison of different AI image generation platforms showing their strengths and typical use cases

#### 💡 Key Takeaways

- Resolution requirements vary by use case, from social media to print materials
- Quality keywords and upscaling features optimize output for professional applications
- Batch generation workflows balance exploration with focused iterative refinement
- Platform selection depends on aesthetic requirements, budget, features, and technical expertise

## Copyright, Ethics, and Commercial Usage

## Navigating Legal and Ethical Considerations

AI-generated images introduce complex questions about copyright ownership, commercial usage rights, and ethical responsibilities. Understanding these considerations protects your organization legally and maintains ethical standards.

Copyright and Ownership Issues

Copyright law surrounding AI-generated content remains evolving. In the United States, the Copyright Office has indicated that works created entirely by AI without human creative input may not qualify for copyright protection. However, images where humans provide significant creative direction—detailed prompts, selective editing, substantial modification—may receive protection as derivative works.

Platform terms vary significantly. Some grant broad commercial usage rights to subscribers; others impose restrictions on revenue generation or require attribution. Always review your platform's terms before using generated images commercially. When working with clients or stakeholders, clarify ownership expectations upfront.

Training Data and Consent Concerns

AI image generators train on massive datasets that may include copyrighted works used without explicit creator consent. This raises ethical questions about whether generating images in specific artists' styles constitutes unauthorized derivative work. Some creators argue AI tools enable plagiarism at scale; platforms contend that AI learns concepts and styles rather than copying specific works.

Responsible practices include avoiding prompts that explicitly reference living artists by name, being transparent about AI usage in professional work, and respecting when clients or contexts require human-created content exclusively.

Commercial Usage Guidelines

Before using AI-generated images in commercial projects, verify your platform permits commercial usage under your subscription tier. Document your generation process, including prompts and editing steps, to demonstrate creative contribution if ownership questions arise. For high-stakes applications—major campaigns, legal documents, regulated industries—consider legal review or restricting AI usage to ideation rather than final deliverables.

Some organizations implement policies requiring human review and modification of all AI-generated content before publication, ensuring human creative input and brand quality control.

Conceptual illustration representing the balance between innovation and responsibility in AI image generation

#### 💡 Key Takeaways

- Copyright protection for AI images depends on human creative contribution and varies by jurisdiction
- Platform terms of service define commercial usage rights and restrictions for generated content
- Training data consent concerns raise ethical questions about style imitation and artist attribution
- Responsible usage includes documentation, transparency, human review, and respecting creator rights

## 🔬 Creating Marketing Visuals with DALL-E 3

Objective: Create a series of marketing images for a fictional coffee shop using DALL-E 3, applying style parameters, composition techniques, and image editing features to produce professional-quality visuals suitable for social media and print materials

⏱ Estimated time: 45 minutes💻 Platform: OpenAI DALL-E 3 via ChatGPT Plus (web browser)
Prerequisites:

- ChatGPT Plus subscription (required for DALL-E 3 access)
- Modern web browser (Chrome, Firefox, Safari, or Edge)
- Stable internet connection
- Image download capability enabled in browser
- Basic understanding of marketing visual requirements

### Procedures

1 Access DALL-E 3 and verify image generation capabilities

1. Navigate to `https://chat.openai.com` in your web browser
2. Sign in with your ChatGPT Plus account
3. Click the model selector dropdown at the top of the page
4. Verify that you see GPT-4 or GPT-4 Turbo as available options
5. Select GPT-4 from the dropdown (DALL-E 3 is integrated into GPT-4)
6. In the chat input field, type:

    I need to verify DALL-E 3 is available. Please confirm you can generate images.

7. Send the message and wait for confirmation

✓ Expected Output

    ChatGPT responds with confirmation that it can generate images using DALL-E 3, typically stating: "Yes, I can generate images using DALL-E 3. Just describe what you'd like to see, and I'll create it for you." The interface shows the standard chat input with no error messages.

🔍 Verify: You see the GPT-4 badge in the model selector and receive explicit confirmation that DALL-E 3 is available for image generation. No error messages appear about subscription limitations.
2 Generate a hero image with specific style and composition parameters

Create your first marketing image using a detailed prompt that includes style, composition, and aesthetic parameters.

Enter this exact prompt in the chat:

    Create a photorealistic image of a cozy independent coffee shop interior. Composition: shot from a low angle near a wooden table in the foreground, with the coffee bar and barista in the middle ground, and large windows showing a rainy street in the background. Lighting: warm, golden hour sunlight streaming through the windows creating dramatic shadows. Include: a latte with lox art on the foreground table, vintage pendant lights, exposed brick wall, plants on shelves. Style: professional architectural photography, shallow depth of field, warm color grading. Aspect ratio: landscape suitable for website hero image.

Press Enter to submit the prompt.

✓ Expected Output

    DALL-E 3 processes the request (typically 20-40 seconds) and displays a generated image showing a coffee shop interior matching your specifications. Below the image, you see a revised prompt that DALL-E 3 created (it automatically enhances prompts for safety and quality). The image displays in a card format with download and edit options visible when you hover over it.

🔍 Verify: The generated image contains all major elements requested: foreground table, coffee bar, windows, warm lighting, and coffee shop atmosphere. The composition follows the described camera angle and the style appears photorealistic with professional lighting.
3 Analyze the automatic prompt enhancement

DALL-E 3 automatically revises prompts for better results and safety compliance. Understanding these revisions helps you write better prompts.

1. Look for the section below the generated image that starts with "Prompt:" or "Generated with:"
2. Read the revised prompt that DALL-E 3 actually used
3. Note what elements were added, removed, or modified
4. Copy the revised prompt to a text editor for comparison

Compare your original prompt with DALL-E 3's revision:

- What descriptive details were added?
- Were any terms replaced with more specific language?
- Did it add photographic or technical terms?
- Were any potentially problematic terms modified?

✓ Expected Output

    The revised prompt is typically longer and more detailed than your original. It may include additional technical photography terms like "bokeh," "f-stop characteristics," or "ambient lighting." DALL-E 3 often adds specific details about textures, materials, and spatial relationships. The prompt maintains your core intent while adding clarity and removing any potentially ambiguous terms.

🔍 Verify: You can clearly identify at least 3-5 specific enhancements or additions that DALL-E 3 made to your original prompt. The revised version reads more like a professional photography brief.
4 Generate variations with different artistic styles

Create three variations of the same coffee shop scene using different artistic styles to understand how style parameters affect output.

Submit these three prompts one at a time, waiting for each image to generate:

Variation 1 - Illustration Style:

    Create the same coffee shop interior scene from the previous image, but render it as a warm, inviting digital illustration in the style of modern editorial illustrations. Use: flat colors, simplified shapes, limited color palette of warm browns, oranges, and creams, subtle texturing, and a slightly whimsical aesthetic. Maintain the same composition and elements.

Variation 2 - Minimalist Style:

    Create the same coffee shop interior scene, but in a minimalist architectural photography style. Use: high contrast black and white, clean lines, emphasis on geometric shapes and negative space, minimal furniture, bright natural light, and a Scandinavian aesthetic. Same composition.

Variation 3 - Vintage Style:

    Create the same coffee shop interior scene in a vintage 1970s photography style. Use: warm film grain, slightly faded colors with dominant oranges and browns, soft focus, vignetting, and the aesthetic of old Kodachrome slides. Same composition and elements.

✓ Expected Output

    Three distinct images are generated, each showing the same basic coffee shop composition but rendered in completely different visual styles:

    1. **Illustration**: Flat, stylized artwork with simplified shapes and a limited color palette
    2. **Minimalist**: High-contrast black and white photograph with clean lines and geometric emphasis
    3. **Vintage**: Warm-toned image with visible grain, soft focus, and retro color characteristics

    Each image maintains the core composition (foreground table, coffee bar, windows) but interprets it through the specified aesthetic lens.

🔍 Verify: All three images are clearly distinguishable in style while maintaining similar composition. The illustration looks hand-drawn, the minimalist version emphasizes geometry and contrast, and the vintage version displays film-like characteristics with grain and color shift.
5 Request specific compositional modifications using natural language editing

DALL-E 3 allows you to request modifications to generated images through conversational prompts.

Select your favorite style from the three variations (photorealistic, illustration, minimalist, or vintage) and request a modification:

    I'd like to modify the [specify which style] version. Please create a new version where: 1) The camera angle is higher, shooting from standing height looking down at the table, 2) Add a person's hands holding the coffee cup, wearing a cozy sweater, 3) Include an open laptop on the table showing a blurred screen, 4) Make the background slightly more blurred to emphasize the foreground. Keep the same style and lighting.

Replace `[specify which style]` with your chosen version (e.g., "photorealistic" or "vintage").

✓ Expected Output

    A new image generates showing the modified composition:
    - Camera perspective is now higher, looking down at the table
    - Hands in a sweater are visible holding or near the coffee cup
    - A laptop appears on the table
    - Background bokeh/blur is more pronounced
    - The original style characteristics are preserved

    The image feels more intimate and relatable with the addition of human elements.

🔍 Verify: The camera angle has noticeably changed to a higher perspective. Human hands are clearly visible. A laptop is present on the table. The depth of field has shifted to emphasize foreground sharpness with background blur.
6 Generate a product-focused image with controlled lighting

Create a product photography style image focusing on a specific coffee drink with precise lighting specifications.

Enter this prompt:

    Create a professional product photography shot of a cold brew coffee in a clear glass on a wooden serving board. Composition: centered, shot from a 45-degree angle, with copy space on the right side. Lighting: studio setup with key light from upper left creating subtle highlights on the glass, rim light from behind to separate the glass from the background, and soft fill light to control shadows. Background: dark charcoal gray backdrop, slightly out of focus. Include: ice cubes visible through the glass, condensation droplets on the outside, a metal straw, and a small plant sprig as garnish. Style: commercial product photography, sharp focus on the drink, f/2.8 depth of field.

✓ Expected Output

    A professional product photograph displays with:
    - The cold brew glass is prominently centered-left, leaving negative space on the right
    - Lighting creates dimensional quality with visible highlights and controlled shadows
    - Ice is visible through the clear glass
    - Condensation appears realistic on the glass exterior
    - Background is dark and provides strong contrast
    - Image has commercial/advertising quality with sharp focus on the product
    - The overall look resembles professional beverage photography from cafe menus or advertising

🔍 Verify: The drink is sharply in focus with visible texture details (ice, condensation). Lighting creates three-dimensional form through highlights and shadows. Copy space is clearly available on the right side for potential text overlay. The background is dark and doesn't compete with the subject.
7 Create a seasonal variation using the seed concept

Generate a seasonal variant that maintains visual consistency with your product shot.

Request a seasonal modification:

    Create a winter/holiday version of the previous cold brew product shot. Change the cold brew to a hot peppermint mocha with whipped cream in a ceramic mug. Add: seasonal elements like cinnamon sticks, star anise, and pine sprigs on the wooden board. Background: add subtle bokeh lights suggesting holiday decorations, maintain the dark background. Keep: the same lighting setup, same camera angle, same composition with copy space on the right, same professional product photography style.

✓ Expected Output

    A new product image generates with seasonal characteristics:
    - Hot beverage in a ceramic mug replaces the cold brew glass
    - Whipped cream tops the drink
    - Seasonal garnishes (cinnamon, star anise, pine) are arranged on the board
    - Warm, inviting bokeh lights appear in the dark background
    - Lighting setup remains consistent (key, rim, and fill lights in similar positions)
    - Composition mirrors the original with copy space on the right
    - Overall style maintains the professional product photography aesthetic

🔍 Verify: The image maintains compositional and lighting consistency with the previous product shot while successfully incorporating all seasonal elements. The same camera angle and copy space arrangement is evident. The professional product photography quality is preserved.
8 Generate a social media square format image

Create an Instagram-optimized image with a different aspect ratio and composition designed for social media engagement.

Submit this prompt:

    Create a square format (1:1 aspect ratio) overhead flat lay photograph for Instagram. Show: a coffee and pastry breakfast scene on a white marble table. Include: a latte with heart-shaped lox art (centered), a croissant on a small plate (upper left), a smartphone showing a blurred cafe menu (upper right), and a small vase with a single flower (lower right). Lighting: bright, airy natural window light creating soft shadows. Style: clean, minimalist Instagram aesthetic with negative white space. Color palette: whites, warm browns, and soft pastels. Professional lifestyle photography.

✓ Expected Output

    A square-format image generates showing:
    - Clear 1:1 (square) aspect ratio suitable for Instagram posts
    - Overhead perspective (bird's eye view) of all elements
    - Clean, bright aesthetic with predominantly white tones
    - All requested elements positioned approximately as specified
    - Soft, even lighting without harsh shadows
    - Ample white space creating a clean, uncluttered look
    - Instagram-ready composition that would work well in a social media feed

🔍 Verify: The image is clearly square (equal width and height). The overhead perspective shows all elements flat on the surface. The composition is balanced with intentional negative space. The bright, airy aesthetic matches typical Instagram lifestyle content.
9 Download and organize your generated images

Save all generated images with descriptive filenames for your marketing asset library.

For each image you want to keep:

1. Hover your mouse over the image
2. Click the download icon (downward arrow) that appears in the top-right corner of the image
3. The image downloads to your default Downloads folder
4. Navigate to your Downloads folder in File Explorer (Windows) or Finder (Mac)
5. Rename each file using this naming convention:

    coffeeshop_[type]_[style]_[format].png

Examples:

- `coffeeshop_hero_photorealistic_landscape.png`
- `coffeeshop_hero_illustration_landscape.png`
- `coffeeshop_product_coldbrew_square.png`
- `coffeeshop_product_hotdrink_square.png`
- `coffeeshop_social_flatlay_square.png`

6. Create a folder named `DALLE_CoffeeShop_Assets` and move all renamed files into it

✓ Expected Output

    Your Downloads folder contains PNG files with descriptive names following the convention. A new folder named `DALLE_CoffeeShop_Assets` exists containing 5-8 organized image files. Each filename clearly indicates the image type, style, and format, making asset management straightforward.

🔍 Verify: You can locate the `DALLE_CoffeeShop_Assets` folder. Inside are multiple PNG files with consistent, descriptive naming. Opening any file displays the corresponding generated image at full resolution (typically 1024x1024 or 1792x1024 pixels depending on aspect ratio).
10 Evaluate image quality using professional criteria

Assess your generated images using a quality control checklist to determine suitability for commercial use.

Open each saved image and evaluate against these criteria:

Technical Quality:

- Resolution: Is the image at least 1024px on the shortest side?
- Sharpness: Are key elements in acceptable focus?
- Artifacts: Are there obvious AI artifacts, distortions, or unnatural elements?
- Color accuracy: Do colors look natural and balanced?

Composition Quality:

- Framing: Is the subject well-positioned in the frame?
- Negative space: Is there appropriate space for text/copy if needed?
- Visual hierarchy: Does the eye naturally flow to the important elements?
- Balance: Is the composition visually balanced?

Brand Suitability:

- Brand alignment: Does the style match a modern coffee shop brand?
- Emotional tone: Does it convey warmth, quality, and approachability?
- Professional appeal: Would this be acceptable in marketing materials?

Create a text file named `quality_assessment.txt` and document which images pass all criteria and which need regeneration.

✓ Expected Output

    A text file containing notes on each image with pass/fail ratings for the checklist categories. Most images should pass technical quality checks. Some compositional or brand suitability aspects might be noted for improvement. You have clear documentation of which images are ready for use and which concepts need refinement.

🔍 Verify: The quality_assessment.txt file exists and contains specific notes for each image. You can identify at least 2-3 images that fully pass all criteria and are suitable for immediate use in marketing materials.
11 Test batch generation with consistent style parameters

Generate a series of images maintaining visual consistency for a cohesive marketing campaign.

Submit this batch request prompt:

    I need to create a series of 3 images for a coffee shop marketing campaign with consistent visual style. Please generate them one at a time:

    Global style for all images: photorealistic, warm natural lighting, shallow depth of field, professional lifestyle photography, warm color grading emphasizing browns and creams, cozy and inviting mood.

    Image 1: Close-up of hands wrapping a gift box with coffee products, craft paper and twine, on a wooden table.

    Image 2: A to-go coffee cup with sleeve on a car dashboard, blurred street view through windshield, morning light.

    Image 3: Two people toasting coffee cups across a small cafe table, shot from table level, faces partially visible (upper body only), background blurred.

    Please generate Image 1 first.

After Image 1 generates, prompt: `Please generate Image 2 now.`

After Image 2 generates, prompt: `Please generate Image 3 now.`

✓ Expected Output

    Three images generate sequentially, each displaying:
    - Consistent photographic style with warm tones and shallow depth of field
    - Similar lighting quality (warm, natural)
    - Comparable color grading and mood
    - Professional lifestyle photography aesthetic
    - Each showing the specific scene requested

    While the subjects differ, the images feel like they belong to the same campaign due to consistent style parameters. They could work together in a marketing carousel or multi-image advertisement.

🔍 Verify: Place the three images side-by-side (open in separate browser tabs or in an image viewer). Visual consistency is apparent across lighting, color tone, depth of field, and overall aesthetic. The images feel cohesive as a set despite showing different subjects.
12 Attempt to generate an image that requires regeneration

Understand DALL-E 3's limitations and practice requesting regenerations when results don't meet requirements.

Submit this intentionally challenging prompt:

    Create an image of a coffee shop menu board showing specific text. The board should clearly display these exact menu items with prices: "Espresso - $3.50", "Cappuccino - $4.75", "Cold Brew - $4.25", "Pastries - $3.00". The text must be clearly legible in a chalk-style font on a dark board background.

Observe the result, then request a regeneration:

    The text on the menu board isn't quite legible. Please regenerate with: less emphasis on making specific readable text, and instead show a blurred/artistic impression of a menu board where the viewer understands it's a menu but specific words aren't the focus. Make the board itself and the overall scene the hero.

✓ Expected Output

    **First attempt:** The generated image shows a menu board, but the text is likely illegible, distorted, or contains nonsensical letter combinations. This demonstrates DALL-E 3's known limitation with generating specific readable text.

    **Second attempt:** A more successful image appears showing a menu board as part of the scene where:
    - The board is clearly identifiable as a menu
    - Text appears present but intentionally blurred or artistically rendered
    - The overall composition and atmosphere are strong
    - The focus is on the aesthetic rather than text legibility

    This demonstrates working with AI limitations rather than against them.

🔍 Verify: The first image contains a menu board but with unclear or incorrect text. The second image successfully conveys "menu board" without relying on legible text. You understand that DALL-E 3 is not suitable for generating images with specific readable text content.
13 Document your prompt engineering learnings

Create a reference guide based on your hands-on experience for future image generation projects.

Create a new text file named `prompt_engineering_guide.txt` and document:

What Works Well:

- List 3-5 prompt techniques that produced the best results
- Note specific descriptive terms that DALL-E 3 responded well to
- Identify which style parameters gave you the most control

What Doesn't Work:

- Document limitations you encountered (e.g., specific text, certain compositions)
- Note any prompts that required multiple regenerations

Effective Prompt Structure:

- Write a template based on your most successful prompts, structured as:

      Subject: [what is the main focus]
      Composition: [camera angle, framing, perspective]
      Lighting: [light sources, quality, direction]
      Style: [artistic style, photography type, aesthetic]
      Details: [specific elements to include]
      Mood: [emotional tone, atmosphere]

Style Consistency Tips:

- List the specific phrases or parameters that helped maintain visual consistency across the batch series

✓ Expected Output

    A comprehensive text file containing:
    - 5-7 specific insights about effective prompt writing
    - Clear documentation of DALL-E 3's strengths and limitations
    - A reusable prompt template
    - Concrete examples from your generation session
    - Actionable advice for future projects

    The guide serves as a practical reference based on hands-on experience rather than theoretical knowledge.

🔍 Verify: The prompt_engineering_guide.txt file exists and contains specific, actionable insights drawn from your lab experience. The template section provides a clear structure that could be used for new image generation projects. At least 3 limitations are clearly documented.

### ⚠️ Troubleshooting

ChatGPT responds with "I can't generate images right now" or "DALL-E is temporarily unavailable"

This indicates either a temporary service outage or your account doesn't have ChatGPT Plus. Verify your subscription status at Settings > Plan. If you have Plus and the error persists, wait 15-30 minutes and try again. Check https://status.openai.com for service status. Ensure you're using GPT-4 model (DALL-E 3 is not available with GPT-3.5).

Generated images don't match the style parameters specified in the prompt

DALL-E 3 sometimes prioritizes safety and content policy over specific style requests. Try these approaches: (1) Be more specific with photographic or artistic terminology (use 'shot with 50mm lens, f/2.8' instead of 'blurry background'), (2) Reference specific art movements or photography styles (e.g., 'Dutch Golden Age painting style' or 'Annie Leibovitz portrait style'), (3) Regenerate using the 'Create a variation' approach by requesting modifications to the existing image rather than starting from scratch.

The prompt gets rejected with a content policy violation message

DALL-E 3 has strict content policies that sometimes trigger false positives. If your coffee shop prompt is rejected: (1) Remove any brand names or trademarked terms, (2) Avoid terms that could be interpreted as requesting recognizable people, (3) Replace 'realistic photo' with 'photorealistic illustration' to signal artistic interpretation, (4) Simplify the prompt by removing complex details and add them back gradually, (5) Rephrase any terms that might have alternative meanings outside your context.

Downloaded images have lower resolution than expected or appear compressed

DALL-E 3 generates images at specific resolutions based on aspect ratio: 1024x1024 for square, 1792x1024 for landscape, or 1024x1792 for portrait. These are the native resolutions—there are no higher quality versions available. If images appear compressed: (1) Ensure you're clicking the download button on the image itself, not right-clicking and saving (which may save a preview), (2) Check your browser's download settings aren't compressing images, (3) For print use, these images work best at approximately 3.5x3.5 inches at 300 DPI (square format) or 6x3.5 inches (landscape). For larger print sizes, consider using AI upscaling tools like Topaz Gigapixel or similar services.

Images in a batch series don't maintain visual consistency despite using the same style parameters

DALL-E 3 doesn't maintain a persistent 'style seed' between generations. To improve consistency: (1) Include all style parameters in every single prompt—never rely on 'same as before', (2) Be extremely specific about lighting (e.g., 'soft window light from the left at 45 degrees' rather than 'natural lighting'), (3) Specify exact color palette (e.g., 'color palette limited to warm browns #8B4513, cream #F5F5DC, and soft orange #FFB366'), (4) Reference the same photography style and technical settings in each prompt (e.g., 'shot with 50mm lens, f/2.8, ISO 400, golden hour'), (5) For critical consistency needs, generate one ideal image first, then request 'variations maintaining the exact same style and lighting' for subsequent images.

### 🏆 Complete Marketing Campaign Asset Package

Apply what you learned — complete this task without step-by-step guidance.

Scenario: You've been hired to create a complete visual identity package for a new coffee shop brand called "Urban Roots Coffee." The brand values sustainability, community, and artisanal craft. They need a cohesive set of marketing assets.

Your Task:

Create a comprehensive set of 8-10 images that includes:

1. Brand Hero Image: A signature photo that captures the brand essence (could be used on website homepage, promotional materials)

2. Product Line (3-4 images): Different beverage styles (hot, cold, specialty) photographed consistently as a product family

3. Lifestyle Series (2-3 images): Customers enjoying the coffee in different contexts (morning routine, work break, social gathering) - all with consistent style and mood

4. Social Media Set (2-3 images): Instagram-optimized square images for a cohesive feed aesthetic

Requirements:

- All images must maintain strong visual consistency (lighting style, color grading, mood, photographic approach)
- The series should tell a cohesive brand story reflecting sustainability and community values
- At least one image should demonstrate advanced composition (rule of thirds, leading lines, or creative framing)
- Create a brand style guide document that includes:
  - The exact prompts used for each image
  - Color palette specifications (identify dominant hex codes from the images)
  - Photography style guidelines for future asset creation
  - Recommended use cases for each image

Deliverables:

- 8-10 organized, renamed image files
- `UrbanRoots_StyleGuide.txt` containing complete documentation
- `UrbanRoots_PromptLibrary.txt` with all successful prompts for future reference

Success Criteria:

Your asset package is successful if:

- Someone viewing all images together immediately recognizes them as a cohesive brand campaign
- The images could realistically be used in professional marketing materials
- Your style guide contains enough detail that another person could generate consistent additional images
- You've demonstrated understanding of composition, lighting, style parameters, and batch consistency techniques

I have completed this lab exercise

## 📝 Knowledge Check

Test your understanding of the material covered in this module. Select the best answer for each question.

#### Question 1

What is the primary advantage of using AI image generation tools for business applications?

A) Completely replacing professional designers and photographers B) Rapid prototyping and iteration of visual concepts at reduced cost C) Guaranteed copyright protection for all generated images D) Eliminating the need for human creative input in marketing

#### Question 2

Which of the following represents the most effective image generation prompt structure?

A) Single-word subject description only B) Subject, style, composition, lighting, and quality specifications C) Lengthy paragraph with multiple conflicting ideas D) Technical camera settings without visual descriptions

#### Question 3

What does inpainting allow you to accomplish in AI image editing?

A) Generate entirely new images from scratch B) Modify specific regions while preserving the overall composition C) Increase image resolution without changing content D) Apply artistic filters to entire images uniformly

#### Question 4

Which lighting specification would be most appropriate for professional corporate headshot generation?

A) Dramatic colored gels with high contrast shadows B) Moody low-key lighting with deep blacks C) Soft natural window light or professional studio lighting D) Harsh overhead fluorescent lighting

#### Question 5

What is outpainting used for in AI image workflows?

A) Removing unwanted objects from images B) Extending images beyond their original boundaries with coherent content C) Converting images to different file formats D) Compressing images for web optimization

#### Question 6

When comparing AI image generation platforms, what is Midjourney particularly known for?

A) Open-source flexibility and maximum technical customization B) Artistic quality with vibrant, imaginative aesthetics C) Enterprise security features and compliance certifications D) Lowest cost per image generation

#### Question 7

What determines whether AI-generated images may receive copyright protection in the United States?

A) The specific AI platform used for generation B) The cost of the subscription plan C) The level of human creative contribution and direction D) The file format of the generated image

#### Question 8

Which approach represents responsible and ethical use of AI image generation in professional contexts?

A) Explicitly referencing living artists by name in prompts to copy their style B) Using generated images commercially without reviewing platform terms C) Being transparent about AI usage and avoiding unauthorized style imitation D) Claiming AI-generated content as entirely human-created work

## 🎯 Module Summary

This module explored AI-powered image generation and editing, covering prompt engineering fundamentals, composition control techniques, and advanced editing capabilities like inpainting and outpainting. You learned how to optimize image quality, select appropriate platforms for specific use cases, and implement batch generation workflows. The module also addressed critical copyright considerations, ethical responsibilities, and commercial usage guidelines essential for professional applications of AI image generation technology.

### Learning Objectives — Review

- Generate custom images from text descriptions using style parameters and composition guidelines
- Modify existing images through inpainting, outpainting, and variation techniques
- Apply quality control criteria to evaluate AI-generated visual content
- Implement image generation workflows for specific business use cases

🎉

### Module Complete!

You have completed all sections of this module.