#!/usr/bin/env python3 """Normalize category background images for Poiana Fermecată. For product-on-white-background images: detects the product bounding box, scales it to fill ~75 % of the target height, and centres it on a light-grey canvas — matching the consistent look used across the official site. For natural/scene photos: falls back to a smart centre-crop at 4:5 ratio. Target output: 800 × 1000 px, JPEG quality 88. Usage: python3 scripts/normalize_category_images.py # process public/images/ python3 scripts/normalize_category_images.py --dry-run python3 scripts/normalize_category_images.py --input /tmp --output public/images/ """ from __future__ import annotations import argparse import numpy as np from pathlib import Path from PIL import Image, ImageEnhance, ImageFilter try: RESAMPLE = Image.Resampling.LANCZOS except AttributeError: RESAMPLE = Image.LANCZOS # type: ignore[attr-defined] TARGET_W, TARGET_H = 800, 1000 PRODUCT_FILL = 0.75 # product occupies this fraction of target height BG_THRESHOLD = 218 # pixels brighter than this on all channels = background CORNER_SAMPLE = 60 # sample this many px from each corner to detect bg CATEGORY_IMAGE_PREFIXES = ( "cat-dulceata", "cat-sirop", "cat-serbet", "cat-ceai", "cat-zacusca", "cat-gourmet", "cat-atelier", "cat-gusturi", "cat-gatim", ) # ── helpers ────────────────────────────────────────────────────────────────── def is_white_bg_image(img: Image.Image) -> bool: """Return True when the image has uniform bright corners (product-on-white style).""" rgb = img.convert("RGB") w, h = rgb.size s = min(CORNER_SAMPLE, w // 6, h // 6) arr = np.array(rgb, dtype=np.float32) corners = [arr[:s, :s], arr[:s, w-s:], arr[h-s:, :s], arr[h-s:, w-s:]] for patch in corners: if patch.mean() < BG_THRESHOLD or patch.std() > 20: return False return True def product_bbox(img: Image.Image) -> tuple[int, int, int, int]: """Return bounding box (left, top, right, bottom) of the non-background content.""" rgb = img.convert("RGB") arr = np.array(rgb, dtype=np.float32) bg_mask = np.all(arr > BG_THRESHOLD, axis=2) content_mask = ~bg_mask rows = np.any(content_mask, axis=1) cols = np.any(content_mask, axis=0) if not rows.any(): w, h = img.size return 0, 0, w, h top = int(np.argmax(rows)) bottom = int(len(rows) - np.argmax(rows[::-1])) left = int(np.argmax(cols)) right = int(len(cols) - np.argmax(cols[::-1])) return left, top, right, bottom def normalize_white_bg(img: Image.Image) -> Image.Image: """Center the product on a uniform light-grey canvas at TARGET_W × TARGET_H.""" img = img.convert("RGB") left, top, right, bottom = product_bbox(img) # Add a small safety margin margin = max(8, int((right - left) * 0.04)) left = max(0, left - margin) top = max(0, top - margin) right = min(img.width, right + margin) bottom = min(img.height, bottom + margin) product = img.crop((left, top, right, bottom)) pw, ph = product.size # Scale so product height = PRODUCT_FILL × TARGET_H scale = (TARGET_H * PRODUCT_FILL) / ph new_pw = max(1, int(pw * scale)) new_ph = max(1, int(ph * scale)) # Never exceed canvas width if new_pw > TARGET_W - 20: scale2 = (TARGET_W - 20) / new_pw new_pw = max(1, int(new_pw * scale2)) new_ph = max(1, int(new_ph * scale2)) product = product.resize((new_pw, new_ph), RESAMPLE) # Build canvas with a neutral grey matching the WP site style canvas_color = (242, 242, 242) canvas = Image.new("RGB", (TARGET_W, TARGET_H), canvas_color) # Centre the product both horizontally and vertically (slightly above centre) paste_x = (TARGET_W - new_pw) // 2 paste_y = max(0, (TARGET_H - new_ph) // 2 - int(TARGET_H * 0.03)) canvas.paste(product, (paste_x, paste_y)) return canvas def center_crop_scene(img: Image.Image) -> Image.Image: """Centre-crop a natural/scene photo to TARGET_W × TARGET_H.""" img = img.convert("RGB") sw, sh = img.size tr = TARGET_W / TARGET_H sr = sw / sh if sr > tr: nw = int(sh * tr) left = (sw - nw) // 2 img = img.crop((left, 0, left + nw, sh)) elif sr < tr: nh = int(sw / tr) top = (sh - nh) // 2 img = img.crop((0, top, sw, top + nh)) return img.resize((TARGET_W, TARGET_H), RESAMPLE) def enhance(img: Image.Image) -> Image.Image: img = ImageEnhance.Contrast(img).enhance(1.06) img = ImageEnhance.Sharpness(img).enhance(1.10) return img def process(src: Path, dst: Path, dry_run: bool, quality: int) -> None: img = Image.open(src) # Flatten transparency if img.mode in ("RGBA", "LA", "P"): bg = Image.new("RGB", img.size, (242, 242, 242)) if img.mode == "P": img = img.convert("RGBA") mask = img.split()[-1] if img.mode in ("RGBA", "LA") else None bg.paste(img.convert("RGB"), mask=mask) img = bg elif img.mode != "RGB": img = img.convert("RGB") if is_white_bg_image(img): result = normalize_white_bg(img) mode = "white-bg→centred" else: result = center_crop_scene(img) mode = "scene→crop" result = enhance(result) if dry_run: print(f"[dry-run] {src.name:35s} mode={mode} → {dst.name}") return dst.parent.mkdir(parents=True, exist_ok=True) result.save(dst, quality=quality, optimize=True, progressive=True) print(f" ✓ {src.name:35s} mode={mode}") def iter_category_images(root: Path): for path in sorted(root.iterdir()): if not path.is_file(): continue if path.suffix.lower() not in (".jpg", ".jpeg", ".png", ".webp"): continue if any(path.name.startswith(p) for p in CATEGORY_IMAGE_PREFIXES): yield path def main() -> None: parser = argparse.ArgumentParser(description=__doc__) parser.add_argument("--input", default="public/images") parser.add_argument("--output", default="public/images") parser.add_argument("--quality", type=int, default=88) parser.add_argument("--dry-run", action="store_true") args = parser.parse_args() in_dir = Path(args.input) out_dir = Path(args.output) images = list(iter_category_images(in_dir)) if not images: print(f"No category images found in {in_dir}") return print(f"Processing {len(images)} image(s) → {TARGET_W}×{TARGET_H}\n") for src in images: out_name = src.stem + ".jpg" dst = out_dir / out_name try: process(src, dst, args.dry_run, args.quality) if not args.dry_run and src.suffix.lower() != ".jpg" and dst != src: src.unlink() print(f" removed: {src.name}") except Exception as exc: print(f" ✗ {src.name}: {exc}") if __name__ == "__main__": main()