Files
BGfilter/bgfilter/despill.py
T
2026-06-30 16:25:56 +08:00

62 lines
2.2 KiB
Python

from __future__ import annotations
import numpy as np
from .chroma import BackgroundModel
from .settings import DespillSettings
def despill_green(
rgb: np.ndarray,
alpha: np.ndarray,
bg_confidence: np.ndarray,
model: BackgroundModel,
settings: DespillSettings,
) -> tuple[np.ndarray, np.ndarray]:
rgb_f = rgb.astype(np.float32) / 255.0
if not settings.enabled:
return rgb.copy(), np.zeros(alpha.shape, dtype=np.float32)
edge = (alpha > settings.edge_low) & (alpha < settings.edge_high)
if settings.edge_expand_radius > 0:
from .deps import require_cv2
cv2 = require_cv2()
radius = settings.edge_expand_radius
kernel = cv2.getStructuringElement(
cv2.MORPH_ELLIPSE, (radius * 2 + 1, radius * 2 + 1)
)
edge = cv2.dilate(edge.astype(np.uint8), kernel).astype(bool)
r = rgb_f[..., 0]
g = rgb_f[..., 1]
b = rgb_f[..., 2]
neutral_green = np.maximum(r, b) + settings.green_excess_margin
excess = np.maximum(g - neutral_green, 0.0)
alpha_weight = np.maximum(
np.clip((1.0 - np.abs(alpha - 0.5) * 2.0), 0.0, 1.0),
settings.alpha_weight_floor,
)
bg_weight = (
settings.bg_confidence_weight * np.clip(bg_confidence, 0.0, 1.0)
+ (1.0 - settings.bg_confidence_weight)
)
green_weight = np.clip(excess / max(settings.green_excess_margin * 8.0, 1e-6), 0.0, 1.0)
mask = edge.astype(np.float32) * alpha_weight * bg_weight * green_weight
out = rgb_f.copy()
target_green = np.minimum(g, neutral_green)
out[..., 1] = g * (1.0 - mask * settings.strength) + target_green * (
mask * settings.strength
)
# Light foreground color approximation: green spill usually removed too much
# luminance from thin hair edges, so redistribute part of the removed green
# into red/blue without changing fully opaque pixels.
bg_green = float(model.rgb_center[1])
compensation = excess * mask * settings.strength * min(0.25, bg_green * 0.15)
out[..., 0] = np.clip(out[..., 0] + compensation * 0.5, 0.0, 1.0)
out[..., 2] = np.clip(out[..., 2] + compensation * 0.5, 0.0, 1.0)
return np.clip(out * 255.0, 0, 255).astype(np.uint8), mask.astype(np.float32)