def depth(img, ver_lst, show_flag=False, wfp=None, with_bg_flag=True):
if with_bg_flag:
overlap = img.copy()
else:
overlap = np.zeros_like(img)
for ver_ in ver_lst:
ver = _to_ctype(ver_.T) # transpose
z = ver[:, 2]
z_min, z_max = min(z), max(z)
z = (z - z_min) / (z_max - z_min)
# expand
z = np.repeat(z[:, np.newaxis], 3, axis=1)
overlap = rasterize(ver, tri, z, bg=overlap)
if wfp is not None:
cv2.imwrite(wfp, overlap)
print(f'Save visualization result to {wfp}')
if show_flag:
plot_image(overlap)
return overlap
def uv_tex(img,
ver_lst,
uv_h=256,
uv_w=256,
uv_c=3,
show_flag=False,
wfp=None):
uv_coords = process_uv(g_uv_coords, uv_h=uv_h, uv_w=uv_w)
res_lst = []
for ver_ in ver_lst:
ver = _to_ctype(ver_.T) # transpose to m x 3
colors = bilinear_interpolate(img, ver[:, 0], ver[:, 1]) / 255.
# `rasterize` here serves as texture sampling, may need to optimization
res = rasterize(uv_coords,
tri,
colors,
height=uv_h,
width=uv_w,
channel=uv_c)
res_lst.append(res)
# concat if there more than one image
res = np.concatenate(res_lst, axis=1) if len(res_lst) > 1 else res_lst[0]
if wfp is not None:
cv2.imwrite(wfp, res)
print(f'Save visualization result to {wfp}')
if show_flag:
plot_image(res)
return res
def pncc(img, ver_lst, show_flag=False, wfp=None, with_bg_flag=True):
ncc_code = _load(make_abs_path('../configs/ncc_code.npy'))
if with_bg_flag:
overlap = img.copy()
else:
overlap = np.zeros_like(img)
# rendering pncc
for ver_ in ver_lst:
ver = _to_ctype(ver_.T) # transpose
overlap = rasterize(ver, tri, ncc_code.T, bg=overlap) # m x 3
if wfp is not None:
cv2.imwrite(wfp, overlap)
print(f'Save visualization result to {wfp}')
if show_flag:
plot_image(overlap)
return overlap