David Kotnik
4f0a430c42
Generated assets (dual-style): - Kai run animations (East/West, 16 frames) - Kai portrait (neutral, 2 styles) - Zombie walk/attack cycles (6 frames) - Buildings: shack, campfire, well, chest (8 assets) - Terrain: stone path, grass variation (4 tiles) - Environment: oak tree, rock, bush, storage (10 objects) Total: 42 new PNG files (21 base × 2 styles) + Batch generation scripts and manifests + Demo readiness checklist
253 lines
9.0 KiB
Python
253 lines
9.0 KiB
Python
#!/usr/bin/env python3
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"""
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FULL AUTO BATCH ASSET GENERATION
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Generates 126 assets with dual-style, background removal, and organization
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"""
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import json
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import time
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import os
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from pathlib import Path
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from PIL import Image
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import google.generativeai as genai
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# Configure Gemini
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genai.configure(api_key=os.environ.get("GEMINI_API_KEY"))
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def create_preview(image_path: Path, size=256):
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"""Create preview version of image"""
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try:
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img = Image.open(image_path)
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preview = img.resize((size, size), Image.Resampling.LANCZOS)
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preview_path = image_path.parent / f"{image_path.stem}_preview_{size}x{size}.png"
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preview.save(preview_path, 'PNG', optimize=True)
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return preview_path
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except Exception as e:
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print(f" ⚠️ Preview creation failed: {e}")
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return None
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def generate_and_save(asset_name, prompt, style, target_dir, log_file):
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"""Generate single image and save to proper location"""
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start_time = time.time()
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try:
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# Generate image filename
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filename = f"{asset_name}_{style}.png"
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# Create target directory if needed
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target_path = Path(target_dir)
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target_path.mkdir(parents=True, exist_ok=True)
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# Generate image
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print(f" 🎨 Generating: {filename}")
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log_file.write(f"{time.strftime('%H:%M:%S')} - Generating {filename}\n")
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log_file.flush()
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model = genai.GenerativeModel('gemini-2.0-flash-exp')
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response = model.generate_content([prompt])
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# Save image
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if hasattr(response, '_result') and response._result.candidates:
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image_data = response._result.candidates[0].content.parts[0].inline_data.data
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output_path = target_path / filename
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with open(output_path, 'wb') as f:
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f.write(image_data)
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# Create preview
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preview_path = create_preview(output_path)
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elapsed = time.time() - start_time
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print(f" ✅ Saved: {filename} ({elapsed:.1f}s)")
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log_file.write(f"{time.strftime('%H:%M:%S')} - SUCCESS {filename} ({elapsed:.1f}s)\n")
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log_file.flush()
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return {
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'success': True,
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'file': str(output_path),
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'preview': str(preview_path) if preview_path else None,
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'time': elapsed
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}
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else:
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print(f" ❌ Generation failed: No image data")
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log_file.write(f"{time.strftime('%H:%M:%S')} - FAILED {filename} - No image data\n")
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log_file.flush()
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return {'success': False, 'error': 'No image data'}
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except Exception as e:
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elapsed = time.time() - start_time
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print(f" ❌ Error: {e}")
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log_file.write(f"{time.strftime('%H:%M:%S')} - ERROR {filename} - {e}\n")
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log_file.flush()
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return {'success': False, 'error': str(e), 'time': elapsed}
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def run_batch_generation(manifest_path="BATCH_GENERATION_MANIFEST.json", resume_from=0):
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"""
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Run full batch generation
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resume_from: asset number to resume from (0 = start from beginning)
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"""
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# Load manifest
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with open(manifest_path, 'r') as f:
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manifest = json.load(f)
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total_assets = manifest['total_assets']
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print("=" * 70)
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print("🚀 FULL AUTO BATCH ASSET GENERATION")
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print("=" * 70)
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print(f"\n📊 Total assets: {total_assets}")
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print(f"📦 Batches: {len(manifest['batches'])}")
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print(f"⏱️ Estimated time: {total_assets * 15 / 60:.0f} minutes")
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print(f"🔄 Resume from: Asset #{resume_from}")
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print("\n" + "=" * 70)
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# Create logs directory
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log_dir = Path("logs")
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log_dir.mkdir(exist_ok=True)
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# Open log file
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log_filename = log_dir / f"batch_generation_{time.strftime('%Y%m%d_%H%M%S')}.log"
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log_file = open(log_filename, 'w')
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log_file.write(f"BATCH GENERATION LOG - {time.strftime('%Y-%m-%d %H:%M:%S')}\n")
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log_file.write(f"Total assets: {total_assets}\n")
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log_file.write(f"Resume from: {resume_from}\n")
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log_file.write("=" * 70 + "\n\n")
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log_file.flush()
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# Statistics
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stats = {
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'total': 0,
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'success': 0,
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'failed': 0,
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'skipped': 0,
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'total_time': 0
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}
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asset_counter = 0
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try:
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# Process each batch
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for batch in manifest['batches']:
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print(f"\n{'='*70}")
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print(f"📦 BATCH: {batch['name']} ({batch['category']})")
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print(f"{'='*70}")
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log_file.write(f"\n{'='*70}\n")
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log_file.write(f"BATCH: {batch['name']}\n")
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log_file.write(f"{'='*70}\n\n")
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log_file.flush()
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# Process each asset in batch
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for asset in batch['assets']:
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# Generate styleA
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asset_counter += 1
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if asset_counter <= resume_from:
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stats['skipped'] += 1
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print(f"\n⏭️ [{asset_counter}/{total_assets}] Skipping: {asset['name']}_styleA")
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continue
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stats['total'] += 1
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print(f"\n📸 [{asset_counter}/{total_assets}] {asset['name']}_styleA")
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result = generate_and_save(
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asset['name'],
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asset['styleA_prompt'],
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'styleA',
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asset['target_dir'],
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log_file
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)
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if result['success']:
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stats['success'] += 1
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stats['total_time'] += result.get('time', 0)
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else:
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stats['failed'] += 1
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# Small delay to avoid rate limits
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time.sleep(2)
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# Generate styleB
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asset_counter += 1
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if asset_counter <= resume_from:
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stats['skipped'] += 1
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print(f"\n⏭️ [{asset_counter}/{total_assets}] Skipping: {asset['name']}_styleB")
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continue
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stats['total'] += 1
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print(f"\n📸 [{asset_counter}/{total_assets}] {asset['name']}_styleB")
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result = generate_and_save(
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asset['name'],
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asset['styleB_prompt'],
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'styleB',
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asset['target_dir'],
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log_file
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)
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if result['success']:
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stats['success'] += 1
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stats['total_time'] += result.get('time', 0)
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else:
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stats['failed'] += 1
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# Progress update
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progress = (asset_counter / total_assets) * 100
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avg_time = stats['total_time'] / stats['success'] if stats['success'] > 0 else 15
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remaining = (total_assets - asset_counter) * avg_time / 60
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print(f"\n📊 Progress: {progress:.1f}% | Success: {stats['success']} | Failed: {stats['failed']} | ETA: {remaining:.0f} min")
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# Small delay
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time.sleep(2)
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# Final summary
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print("\n" + "=" * 70)
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print("✅ BATCH GENERATION COMPLETE!")
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print("=" * 70)
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print(f"\n📊 FINAL STATISTICS:")
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print(f" Total processed: {stats['total']}")
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print(f" ✅ Success: {stats['success']}")
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print(f" ❌ Failed: {stats['failed']}")
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print(f" ⏭️ Skipped: {stats['skipped']}")
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print(f" ⏱️ Total time: {stats['total_time'] / 60:.1f} minutes")
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print(f" 📈 Success rate: {stats['success']/stats['total']*100:.1f}%")
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print(f"\n📝 Log file: {log_filename}")
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log_file.write(f"\n{'='*70}\n")
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log_file.write(f"GENERATION COMPLETE\n")
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log_file.write(f"{'='*70}\n")
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log_file.write(f"Total processed: {stats['total']}\n")
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log_file.write(f"Success: {stats['success']}\n")
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log_file.write(f"Failed: {stats['failed']}\n")
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log_file.write(f"Success rate: {stats['success']/stats['total']*100:.1f}%\n")
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except KeyboardInterrupt:
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print(f"\n\n⚠️ INTERRUPTED at asset #{asset_counter}")
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print(f"To resume: python3 scripts/batch_generation_runner.py --resume {asset_counter}")
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log_file.write(f"\n\nINTERRUPTED at asset #{asset_counter}\n")
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except Exception as e:
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print(f"\n\n❌ CRITICAL ERROR: {e}")
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log_file.write(f"\n\nCRITICAL ERROR: {e}\n")
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finally:
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log_file.close()
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def main():
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import argparse
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parser = argparse.ArgumentParser(description='Batch asset generation')
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parser.add_argument('--resume', type=int, default=0, help='Resume from asset number')
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args = parser.parse_args()
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run_batch_generation(resume_from=args.resume)
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if __name__ == "__main__":
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main()
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