Mike Wichers
24dcb44af4
Primary sync: replace PersistenceActor JSON file with SwiftData + CloudKit - Add SavedCardModel (@Model class) and PersistenceController (ModelContainer with .automatic CloudKit, fallback to local). BackgroundPersistenceActor (@ModelActor) handles all DB I/O off the main thread. - One-time migration imports user_collection.json into SwiftData and renames the original file to prevent re-import. - Inject modelContainer into SwiftUI environment in IYmtgApp. Image storage: Documents/UserContent/ subfolder (blueprint requirement) - ImageManager.dir now targets iCloud Documents/UserContent/ (or local equiv). - migrateImagesToUserContent() moves existing JPGs to the new subfolder on first launch; called during the SwiftData migration. Firebase: demoted to optional manual backup (metadata only, no images) - Remove all automatic CloudEngine.save/delete/batchUpdatePrices calls from CollectionViewModel mutations. - Add backupAllToFirebase() for user-triggered metadata sync. - Add isFirebaseBackupEnabled to AppConfig (default false). - Add Cloud Backup section in Library settings with iCloud vs Firebase explanation and "Backup Metadata to Firebase Now" button. Also: full modular refactor (Data/, Features/, Services/ directories) and README updated with CloudKit setup steps and revised release checklist. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
99 lines
4.1 KiB
Python
99 lines
4.1 KiB
Python
import os, sys, argparse
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# Dependency Check
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try:
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from PIL import Image, ImageOps
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except ImportError:
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print("❌ Error: Pillow library not found.")
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print("👉 Please run: pip install Pillow")
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sys.exit(1)
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# Configuration
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# Paths are relative to where the script is run, assuming run from root or automation folder
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BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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SOURCE_DIR = os.path.join(BASE_DIR, "Raw_Assets")
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OUTPUT_DIR = os.path.join(BASE_DIR, "Ready_Assets")
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# Target Dimensions (Width, Height)
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ASSETS = {
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"AppIcon": (1024, 1024),
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"logo_header": (300, 80),
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"scanner_frame": (600, 800),
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"empty_library": (800, 800),
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"share_watermark": (400, 100),
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"card_placeholder": (600, 840),
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}
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# Assets whose target aspect ratio differs significantly from a typical AI square output.
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# These use thumbnail+pad (letterbox) instead of center-crop to preserve full image content.
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PAD_ASSETS = {"logo_header", "share_watermark"}
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def resize_fit(img, size):
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"""Center-crop and scale to exact size. Best when source matches target aspect ratio."""
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return ImageOps.fit(img, size, method=Image.Resampling.LANCZOS)
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def resize_pad(img, size, bg_color=(0, 0, 0, 0)):
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"""Scale to fit within size, then pad with bg_color to reach exact dimensions.
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Preserves the full image — nothing is cropped. Ideal for logos and banners."""
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img.thumbnail(size, Image.Resampling.LANCZOS)
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canvas = Image.new("RGBA", size, bg_color)
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offset = ((size[0] - img.width) // 2, (size[1] - img.height) // 2)
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canvas.paste(img, offset)
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return canvas
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def process_assets(force_pad=False, force_crop=False):
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print(f"📂 Working Directory: {BASE_DIR}")
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# Create directories if they don't exist
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if not os.path.exists(SOURCE_DIR):
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os.makedirs(SOURCE_DIR)
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print(f"✅ Created source folder: {SOURCE_DIR}")
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print("👉 ACTION REQUIRED: Place your raw AI images here (e.g., 'AppIcon.png') and run this script again.")
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return
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if not os.path.exists(OUTPUT_DIR):
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os.makedirs(OUTPUT_DIR)
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print(f"✅ Created output folder: {OUTPUT_DIR}")
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print(f"🚀 Processing images from 'Raw_Assets'...")
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for name, size in ASSETS.items():
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found = False
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# Check for common image extensions
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for ext in [".png", ".jpg", ".jpeg", ".webp"]:
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source_path = os.path.join(SOURCE_DIR, name + ext)
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if os.path.exists(source_path):
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try:
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img = Image.open(source_path)
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if img.mode != 'RGBA': img = img.convert('RGBA')
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# Choose resize strategy:
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# - PAD_ASSETS (and --pad flag) use thumbnail+letterbox to avoid cropping banner images.
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# - Everything else uses center-crop (ImageOps.fit) for a clean full-bleed fill.
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use_pad = (name in PAD_ASSETS or force_pad) and not force_crop
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if use_pad:
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processed_img = resize_pad(img, size)
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mode_label = "pad"
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else:
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processed_img = resize_fit(img, size)
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mode_label = "crop"
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output_path = os.path.join(OUTPUT_DIR, name + ".png")
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processed_img.save(output_path, "PNG")
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print(f"✅ Generated: {name}.png ({size[0]}x{size[1]}, {mode_label})")
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found = True
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break
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except Exception as e:
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print(f"❌ Error processing {name}: {e}")
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if not found:
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print(f"⚠️ Skipped: {name} (File not found in Raw_Assets)")
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Resize raw AI assets to Xcode-ready dimensions.")
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group = parser.add_mutually_exclusive_group()
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group.add_argument("--pad", action="store_true", help="Force thumbnail+pad for ALL assets (no cropping).")
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group.add_argument("--crop", action="store_true", help="Force center-crop for ALL assets (overrides default pad assets).")
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args = parser.parse_args()
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process_assets(force_pad=args.pad, force_crop=args.crop)
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