# Visual Evidence — Gemma 4 Multimodal Scene Description Generator ## Test Image: Coffee Beans (Macro Photo) ### Gemma 4 Vision Analysis (via Ollama) **Model:** gemma4:latest (8B, Q4_K_M) **Input:** sample_photo.jpg (46KB JPEG) **Structured Output (JSONL):** ```json { "mood": "dark", "colors": ["dark brown", "espresso", "black"], "composition": "close-up", "camera": "static", "lighting": "soft", "description": "An extreme close-up shot captures a dense pile of roasted coffee beans. The beans are a uniform, deep dark brown and appear slightly oily, filling the entire frame. The focus emphasizes the rich texture and individual shapes of the beans." } ``` ### Hermes Vision Analysis (Cross-Validation) **Scene ID:** COFFEE_MACRO_001 **Mood:** Warm, aromatic, and comforting **Dominant Colors:** Deep umber, burnt sienna, espresso black, mahogany **Composition:** Full-frame fill, centrally weighted **Camera:** High-angle, close-up (Macro) **Lighting:** Soft, diffused top-lighting ## Test Image: Abstract Geometric Composition ### Gemma 4 Vision Analysis **Input:** scene1.jpg (10KB, PIL-generated) **Structured Output (JSONL):** ```json { "mood": "energetic", "colors": ["deep blue", "yellow", "coral"], "composition": "wide-shot", "camera": "static", "lighting": "artificial", "description": "This is an abstract graphic composition set against a solid, deep blue background. A bright yellow square is placed in the upper left quadrant, while a large, solid coral-colored circle occupies the lower right quadrant. The geometric shapes create a high-contrast, minimalist visual balance." } ``` ## Verification Summary | Test | Status | Details | |------|--------|---------| | Model detection | ✅ PASS | `gemma4:latest` auto-detected | | Image scanning | ✅ PASS | 2 images found recursively | | Vision analysis | ✅ PASS | Both images described accurately | | JSON parsing | ✅ PASS | Structured output with all fields | | Training format | ✅ PASS | JSONL with source, model, timestamp | | ShareGPT format | ⚠️ PARTIAL | Works but needs retry on rate limit | ## Running the Generator ```bash # Check model availability python scripts/generate_scene_descriptions.py --check-model # Generate scene descriptions from assets python scripts/generate_scene_descriptions.py --input ./assets --output training-data/scene-descriptions-auto.jsonl # Limit to 10 files with specific model python scripts/generate_scene_descriptions.py --input ./assets --model gemma4:latest --limit 10 # ShareGPT format for training pipeline python scripts/generate_scene_descriptions.py --input ./assets --format sharegpt ```