import sys
sys.path.insert(0, "services/recolor")
import numpy as np
from PIL import Image
import cv2

from fabric_recolor.segmentation.birefnet import BirefnetMatteSegmenter
from fabric_recolor.segmentation.prompts import NEGATIVE_PROMPTS, CAVITY_PROMPTS
from fabric_recolor.masks import (
    alpha_hysteresis, clean_binary, largest_component, fill_small_holes,
    recessed_pocket_labels, cavity_anchors, _silhouette_bands,
)

src = "data/media/originals/fd/fd12e584a23312c7c5edda1015fe9715d3f5fd19a2ef3d375d635cefab91f54b.jpg"
img = Image.open(src).convert("RGB")
W0, H0 = img.width, img.height
scale = min(1.0, 1600 / max(H0, W0))
seg = img.resize((round(W0*scale), round(H0*scale)), Image.BILINEAR)
arr = np.asarray(seg)

sb = BirefnetMatteSegmenter()
sb._load()
matte = alpha_hysteresis(sb._matte(seg), ramp_px=max(4, round(8*scale)))
mask = clean_binary((matte >= 0.5).astype(np.uint8), 0.002)
mask = largest_component(mask)
mask = fill_small_holes(mask, 0.01)

depth = sb._depth_map(seg)
iso = Image.fromarray(arr * mask[..., None].astype(np.uint8))
raw = sb._neg_segmenter().negatives_instances(iso, NEGATIVE_PROMPTS)
cav_ids = {i for i,p in enumerate(NEGATIVE_PROMPTS) if p in CAVITY_PROMPTS}
inst = [(m, idx in cav_ids) for m, idx in raw]
anchors = cavity_anchors(inst, mask)
print("anchors px:", int(anchors.sum()))
if anchors.any():
    print("anchor depth: med=%.3f p10=%.3f p90=%.3f" % (
        np.median(depth[anchors>0]), np.percentile(depth[anchors>0],10), np.percentile(depth[anchors>0],90)))

for th in (0.25, 0.3, 0.35, 0.4):
    pockets = recessed_pocket_labels(mask, depth, rim_frac=0.10, deficit_min=th)
    n = int(pockets.max())
    big = []
    for i in range(1, n+1):
        c = (pockets == i) & (mask > 0)
        a = int(c.sum())
        if a > 3000:
            anch = int((c & (anchors>0)).sum())
            band,_ = _silhouette_bands(mask, 6)
            tb = bool((c & (band>0)).any())
            big.append((i, a, f"anch={anch}", f"band={tb}", f"d_med={np.median(depth[c]):.2f}"))
    print(f"th={th}: {big}")

pockets = recessed_pocket_labels(mask, depth, rim_frac=0.10, deficit_min=0.3)
viz = arr.copy()
viz[pockets > 0] = (viz[pockets > 0] * 0.35 + np.array([255,40,40])*0.65).astype(np.uint8)
viz[anchors > 0] = [0, 255, 255]
Image.fromarray(viz).save("tmp/dbg-pocket-6413.png")
print("saved dbg-pocket-6413.png")