David Kotnik
efe3280df5
VERTEX AI SETUP SUCCESS (01.01.2026 21:00): ✅ gcloud CLI installed (v550.0.0) ✅ Authentication configured (ADC) ✅ Vertex AI API enabled ✅ Test generation successful (2 skull PNG) ✅ Credits confirmed: €1,121.80 available CHARACTER TESTS: ⚠️ edit_image blocked by safety filters (face generation) ⚠️ seed parameter blocked by watermark 📝 Character animations need alternative approach NEW FILES: ✅ reference_images/kai_master_stylea.png - Kai cartoon reference ✅ reference_images/kai_master_styleb.png - Kai noir reference ✅ scripts/test_character_consistency.py - Image edit test ✅ scripts/test_character_seed.py - Seed-based test TEST OUTPUTS: ✅ test_vertex_output.png (Style A skull - 2.4MB) ✅ test_vertex_output_styleb.png (Style B skull) PRODUCTION PLAN: 📊 Complete game: ~3,121-12,400 PNG 💰 Cost: €56-€223 (fully covered by credits!) ⏱️ Time: 8-34 hours for full generation 🎯 Ready for bulk asset generation NEXT STEPS: 1. Decide generation scope (unique vs full production) 2. Run bulk generation script 3. Background removal post-processing 4. Git commit batches during generation STATUS: Infrastructure ready, awaiting generation start 🚀
69 lines
2.6 KiB
Python
69 lines
2.6 KiB
Python
#!/usr/bin/env python3
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"""
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Test Character Consistency - Generate Kai walking animation frames
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"""
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import vertexai
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from vertexai.preview.vision_models import ImageGenerationModel, Image
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from pathlib import Path
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# Initialize
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vertexai.init(project="gen-lang-client-0428644398", location="us-central1")
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# Load Kai reference (Style A - Cartoon)
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kai_reference_path = Path("reference_images/kai_master_stylea.png")
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kai_reference = Image.load_from_file(str(kai_reference_path))
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print("="*60)
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print("🎮 KAI CHARACTER CONSISTENCY TEST")
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print("="*60)
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print(f"📸 Reference: {kai_reference_path}")
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print()
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# Animation frames to generate
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frames = [
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{
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"name": "kai_walk_frame1",
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"prompt": "Same character Kai exactly as shown, walking animation, left leg forward step, right arm forward. Maintain exact same face, green hair, backpack, blue jeans, and brown boots. Cartoon vector style with bold outlines. Solid bright green background (#00FF00)."
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},
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{
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"name": "kai_walk_frame2",
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"prompt": "Same character Kai exactly as shown, walking animation, standing upright neutral pose, both feet together. Maintain exact same face, green hair, backpack, blue jeans, and brown boots. Cartoon vector style with bold outlines. Solid bright green background (#00FF00)."
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},
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{
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"name": "kai_walk_frame3",
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"prompt": "Same character Kai exactly as shown, walking animation, right leg forward step, left arm forward. Maintain exact same face, green hair, backpack, blue jeans, and brown boots. Cartoon vector style with bold outlines. Solid bright green background (#00FF00)."
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}
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]
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model = ImageGenerationModel.from_pretrained("imagegeneration@006")
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# Generate frames
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for i, frame in enumerate(frames, 1):
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print(f"\n🎨 Generating Frame {i}/3: {frame['name']}")
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print(f"📝 Prompt: {frame['prompt'][:80]}...")
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try:
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# Use edit_image with reference for consistency
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response = model.edit_image(
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base_image=kai_reference,
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prompt=frame['prompt'],
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edit_mode="inpainting-insert",
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negative_prompt="different character, different face, different hair color, different clothing, different proportions, watermark, text"
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)
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output_path = Path(f"test_character/{frame['name']}.png")
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output_path.parent.mkdir(exist_ok=True)
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response.images[0].save(location=str(output_path))
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print(f"✅ Saved: {output_path}")
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except Exception as e:
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print(f"❌ Error: {e}")
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print("\n" + "="*60)
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print("✅ TEST COMPLETE!")
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print("📁 Check: test_character/ folder")
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print("="*60)
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