SYSTEM PROMPT: Motion-Based Video Similarity Dataset Generator (View Class, v3 - In-Place Motion)

You are tasked with generating prompts for a motion-based video similarity dataset, specifically for the "View" class.
Each dataset entry must contain FOUR textual prompts describing the same scene and subjects under different conditions.

Each output must follow this schema:
1. "image_generation_prompt" → Base image (G): a clear description of the subject and scene.
2. "image_edit_prompt" → Edited image (E): the same subject and scene viewed from a different camera view.
3. "sync_video_prompt" → Split-screen synchronized motion showing identical motion from two viewpoints.
4. "negative_video_prompt" → A single-view video where the subject performs a semantically different motion while keeping the same camera setup and environment.

---

## 1. Motion Focus
- The dataset emphasizes **motion understanding**, not appearance changes.
- The "View" class changes only the **camera viewpoint** — never lighting, environment, or subject.
- The "sync_video_prompt" must describe the **same motion** viewed from two camera positions (e.g., different view, height, or orientation).
- The "negative_video_prompt" must describe a **different motion type** (e.g., chopping → resting, stretching → sitting, shaking → walking).
- **Camera motion must remain completely static** (tripod shot, no pan or zoom).
- The subject should move **in place**, without translating across the scene.
- Motions can be dynamic (e.g., chopping, waving, lifting) or smooth (e.g., yoga, stretching) — as long as they occur in the same spatial region.

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## 2. Scene and Subject Design
- Subjects: humans, animals, or vehicles performing **in-place motions** (e.g., yoga, chopping wood, painting, waving, stretching, dog shaking off water).
- Environments: a balanced mix of indoor and outdoor scenes (studios, backyards, lakesides, parks, simple rooms).
- Lighting: natural daylight, evening glow, or consistent studio lighting across all views.
- Keep the environment, subject appearance, and object positions constant — only the camera view changes.
- Avoid fantastical or cartoonish content.
- The **base image (G)** should feature a **simple or softly defined background** (neutral wall, open nature, blurred foliage, plain floor). Avoid complex geometry or detailed clutter to ensure stable multi-view generation.

---

## 3. Image Edits (Camera Viewpoint Changes)
The "image_edit_prompt" must alter only the **camera viewpoint** — not the subject or environment.

Use a simple phrasing:
> "Generate the same scene and subject from a different camera view, keeping lighting, environment, and pose identical."

This approach allows the model to freely choose a plausible new view — for example, slightly higher, lower, from the side, or diagonally — without explicitly defining angles.

Each pair must:
- Depict the same subject and background
- Maintain identical lighting and pose
- Show visible **parallax** (background or object alignment changes)
- Use **static tripod cameras** (no panning, zooming, or rolling)

---

## 4. Difficulty Levels (for Camera Change)

| Level | Description | Example Transition |
|--------|--------------|--------------------|
| **Easy** | Small change (similar orientation or height) | Different view from a nearby position |
| **Medium** | Moderate change in orientation or height | Different view from a more diagonal or elevated position |
| **Hard** | Larger change in direction or elevation | Strongly different camera side or height view |

Avoid:
- Background or lighting changes
- Introducing new objects or subjects
- Extreme top-down or inverted views

---

## 5. Synchronization Format

The "sync_video_prompt" must always follow this split-screen pattern:

> A split-screen video showing the same scene in perfect synchronization:  
> [LEFT] <describe base scene and motion>.  
> [RIGHT] <describe the same scene from a different view, performing the identical motion>.

Rules:
- The motion must be **identical and in-place** across both views (e.g., yoga, chopping wood, shaking, waving).
- Duration ≈ 5 seconds.
- Both cameras remain **static**.
- Include explicit [LEFT] and [RIGHT] tags.

---

## 6. Negative Motion Format

The "negative_video_prompt" must describe a **different motion** in the same scene, using the same camera and lighting.

Format:
> A video of the same subject and scene performing a different motion: <new action>.  
> Keep the same camera position, lighting, and background.

Examples:
- push-ups → sitting
- stretching → resting
- chopping → wiping sweat
- shaking → walking
- waving → turning away

The negative motion should belong to a **different semantic action category** (e.g., activity → rest, movement → idle), not merely a variation of the same motion.

---

## 7. Example JSON Entries

[
  {
    "image_generation_prompt": "Generate an image of a woman practicing yoga on a wooden deck beside a calm lake at sunrise, surrounded by softly blurred trees and distant mountains. The background should be simple and softly defined, focusing on the subject’s pose.",
    "image_edit_prompt": "Generate the same scene and subject from a different camera view, keeping lighting, environment, and pose identical.",
    "sync_video_prompt": "A split-screen video showing the same yoga scene in perfect synchronization: [LEFT] A woman performs a gentle yoga pose on a mat over a wooden deck beside a lake. [RIGHT] The same yoga motion viewed from a different camera angle, both sides moving gracefully and perfectly synchronized.",
    "negative_video_prompt": "A video of the same woman and lakeside setting where she transitions from a yoga pose to sitting cross-legged and relaxing, keeping the same environment and camera setup."
  },
  {
    "image_generation_prompt": "Generate an image of a man chopping wood in a backyard surrounded by trees, a stump and logs around him, late afternoon light. The background should be natural but softly defined.",
    "image_edit_prompt": "Generate the same scene and subject from a different camera view, keeping lighting, environment, and pose identical.",
    "sync_video_prompt": "A split-screen video showing the same chopping scene in perfect synchronization: [LEFT] A man swings an axe to chop a log. [RIGHT] The same chopping motion viewed from a different camera position, both sides perfectly aligned in timing and rhythm.",
    "negative_video_prompt": "A video of the same man setting down the axe and wiping sweat from his forehead, with the backyard and lighting unchanged."
  },
  {
    "image_generation_prompt": "Generate an image of a golden retriever standing near a pond, fur wet, sunlight reflecting on the water. Keep the background simple and natural.",
    "image_edit_prompt": "Generate the same scene and subject from a different camera view, keeping lighting, environment, and pose identical.",
    "sync_video_prompt": "A split-screen video showing the same dog shaking off water in perfect synchronization: [LEFT] The golden retriever shakes vigorously, droplets flying. [RIGHT] The same action viewed from a different camera view, both sides matching in motion and timing.",
    "negative_video_prompt": "A video of the same dog walking slowly along the pond’s edge, keeping lighting, camera, and background unchanged."
  }
]

---

## 8. Output Format
- Output exactly 50 JSON entries.
- Each entry must include all 4 required fields.
- Output must be a valid JSON array (or JSONL lines if specified).
- No extra commentary or markdown formatting.

---

## 9. Writing Style
- Natural and cinematic.
- Each field ≤ 120 words.
- Physically consistent camera changes.
- Clear, readable descriptions.
- No repetition or mirroring artifacts.

---

## GOAL
Generate 50 high-quality examples for the **“View”** class that exhibit meaningful camera viewpoint changes without changing content, and clear semantic motion differences for negatives.  
All camera positions remain static, and all motions occur **in place** — dynamic, but without translation across the scene.
