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example1_grouped.md

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+# **Example 1: Grouped vs Non-Grouped Prompts**
+
+## **Overview**
+This example demonstrates the impact of using grouping (`{}`) in prompts versus non-grouped prompts. Grouping treats multiple elements as a cohesive unit, balancing their presence in the generated image, whereas non-grouped prompts process each element independently, leading to varying levels of emphasis.
+
+---
+
+## **Prompt Details**
+
+### **Image 1** (Grouped Prompt)
+- **Prompt**: `{snowy mountain, clear lake, dense forest}`
+- **Behavior**: Grouping treats all elements (`snowy mountain`, `clear lake`, and `dense forest`) as a cohesive unit.
+- **Result**:
+  - The composition balances the visibility of all three elements.
+  - Snowy mountains dominate the background, the lake occupies the middle ground, and forests frame the scene evenly.
+  - Emphasis is distributed equally, creating a harmonious blend.
+
+### **Image 2** (Non-Grouped Prompt)
+- **Prompt**: `snowy mountain, clear lake, dense forest`
+- **Behavior**: Elements are processed independently without treating them as a single unit.
+- **Result**:
+  - The snowy mountain is prominently displayed in the center.
+  - The lake appears in the foreground with a less balanced representation of the forest.
+  - The scene emphasizes the mountain more strongly, reducing focus on other elements.
+
+---
+
+## **Comparison Table**
+
+| **Aspect**           | **Grouped (`{}`)**                                        | **Non-Grouped**                                         |
+|-----------------------|----------------------------------------------------------|--------------------------------------------------------|
+| **Mountain**          | Present but balanced with other elements                 | Dominates the composition, central and visually strong |
+| **Lake**              | Blends harmoniously with other elements                  | More prominent in the foreground                       |
+| **Forest**            | Framed evenly on the sides, balanced with the mountain   | Reduced visibility, primarily on the left              |
+| **Overall Balance**   | Equal representation of all elements                     | Heavily focused on the mountain                       |
+| **Visual Flow**       | Smooth flow between elements                             | Clear hierarchy with mountain as the focal point       |
+
+---
+
+## **How Grouping Affects Composition**
+
+### **1. Grouping (`{}`)**
+- Treats all specified elements as equally important.
+- Creates a balanced composition where no single element dominates.
+- Ensures that the viewer's attention is distributed across the entire image.
+
+### **2. Non-Grouped**
+- Processes elements independently, leading to varying levels of emphasis.
+- The strongest element (`snowy mountain`) dominates, while others are less prominent.
+- Results in a more hierarchical composition, which may focus on one or two elements.
+
+---
+
+## **Conclusion**
+Grouping (`{}`) is ideal for creating balanced scenes with equal representation of all elements. In contrast, non-grouped prompts give more weight to dominant elements, leading to less visual harmony but potentially stronger focal points.

example_images/01_Grouping/example 1_Grouped.txt

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+{snowy mountain, clear lake, dense forest}
+Steps: 30, Sampler: DPM++ 2M, Schedule type: Karras Exponential, CFG scale: 7, Seed: 26067899193, Size: 768x512, Model hash: 7be8cfbcd2, Model: FusionX-Realistic_v3_float16, Denoising strength: 0.7, Clip skip: 2, Hypertile U-Net: True, Hires upscale: 2, Hires steps: 30, Hires upscaler: R-ESRGAN 4x+ Anime6B, Version: v1.10.1, Hashes: {"model": "7be8cfbcd2"}

example_images/01_Grouping/example 1_UnGrouped.txt

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+snowy mountain, clear lake, dense forest,
+Steps: 30, Sampler: DPM++ 2M, Schedule type: Karras Exponential, CFG scale: 7, Seed: 26067899193, Size: 768x512, Model hash: 7be8cfbcd2, Model: FusionX-Realistic_v3_float16, Denoising strength: 0.7, Clip skip: 2, Hypertile U-Net: True, Hires upscale: 2, Hires steps: 30, Hires upscaler: R-ESRGAN 4x+ Anime6B, Version: v1.10.1, Hashes: {"model": "7be8cfbcd2"}