Spaces:
Sleeping
Sleeping
""" | |
Modified by Nikita Selin (OPHoperHPO)[https://github.com/OPHoperHPO]. | |
Source url: https://github.com/MarcoForte/FBA_Matting | |
License: MIT License | |
""" | |
import cv2 | |
import numpy as np | |
group_norm_std = [0.229, 0.224, 0.225] | |
group_norm_mean = [0.485, 0.456, 0.406] | |
def dt(a): | |
return cv2.distanceTransform((a * 255).astype(np.uint8), cv2.DIST_L2, 0) | |
def trimap_transform(trimap): | |
h, w = trimap.shape[0], trimap.shape[1] | |
clicks = np.zeros((h, w, 6)) | |
for k in range(2): | |
if np.count_nonzero(trimap[:, :, k]) > 0: | |
dt_mask = -dt(1 - trimap[:, :, k]) ** 2 | |
L = 320 | |
clicks[:, :, 3 * k] = np.exp(dt_mask / (2 * ((0.02 * L) ** 2))) | |
clicks[:, :, 3 * k + 1] = np.exp(dt_mask / (2 * ((0.08 * L) ** 2))) | |
clicks[:, :, 3 * k + 2] = np.exp(dt_mask / (2 * ((0.16 * L) ** 2))) | |
return clicks | |
def groupnorm_normalise_image(img, format="nhwc"): | |
""" | |
Accept rgb in range 0,1 | |
""" | |
if format == "nhwc": | |
for i in range(3): | |
img[..., i] = (img[..., i] - group_norm_mean[i]) / group_norm_std[i] | |
else: | |
for i in range(3): | |
img[..., i, :, :] = ( | |
img[..., i, :, :] - group_norm_mean[i] | |
) / group_norm_std[i] | |
return img | |