from pathlib import Path
from PIL import Image, ImageFilter
from collections import deque

ROOT = Path(__file__).resolve().parents[1]
web = ROOT / 'work' / 'assets' / 'web'
out = ROOT / 'work' / 'assets' / 'generated'
out.mkdir(parents=True, exist_ok=True)

src = web / 'p16_719A1022.jpg'
im = Image.open(src).convert('RGB')
w, h = im.size
# Crop the complete product set with generous margin; no product-body cutout is used.
# This preserves the cup, saucer, spoon and package pixels, while avoiding the full studio border.
crop = im.crop((190, 360, 1250, 1270))
w, h = crop.size
pix = crop.load()
# Harmonize only the border-connected studio background to the page color, so the photo
# does not appear as a white rectangle. Product surfaces are not segmented or made transparent.
page_bg = (247, 246, 242)  # Liangzhu bone white
corners = [pix[0,0], pix[w-1,0], pix[0,h-1], pix[w-1,h-1]]
bg = tuple(sum(c[i] for c in corners)//4 for i in range(3))

def dist(c):
    return sum((c[i]-bg[i])**2 for i in range(3)) ** 0.5

visited = bytearray(w*h)
mask = Image.new('L', (w,h), 0)
mp = mask.load()
q = deque()
for x in range(w):
    q.append((x,0)); q.append((x,h-1))
for y in range(h):
    q.append((0,y)); q.append((w-1,y))
# only border-connected pale studio background
while q:
    x,y = q.popleft()
    if x < 0 or x >= w or y < 0 or y >= h:
        continue
    idx = y*w+x
    if visited[idx]:
        continue
    visited[idx] = 1
    r,g,b = pix[x,y]
    if dist((r,g,b)) <= 34 and min(r,g,b) > 210:
        mp[x,y] = 255
        q.append((x+1,y)); q.append((x-1,y)); q.append((x,y+1)); q.append((x,y-1))
# soften transition so there is no hard mask edge; this does not remove/erase product pixels.
soft = mask.filter(ImageFilter.GaussianBlur(2.0))
base = Image.new('RGB', (w,h), page_bg)
# composite original product over page color where mask says background
result = Image.composite(base, crop, soft)
# very light crop-margin feather: outer background remains same color as page
out_path = out / 'closing_product_complete_v05.jpg'
result.save(out_path, quality=95)
print({'output': str(out_path), 'size': result.size, 'bg_sample': bg, 'mask_extrema': soft.getextrema()})