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# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
import functools
from typing import Optional
import dnnlib
import numpy as np
import PIL.Image
import PIL.ImageFont
import scipy.ndimage
from . import gl_utils
# ----------------------------------------------------------------------------
def get_default_font():
# Open Sans regular
url = 'http://fonts.gstatic.com/s/opensans/v17/mem8YaGs126MiZpBA-U1UpcaXcl0Aw.ttf'
return dnnlib.util.open_url(url, return_filename=True)
# ----------------------------------------------------------------------------
@functools.lru_cache(maxsize=None)
def get_pil_font(font=None, size=32):
if font is None:
font = get_default_font()
return PIL.ImageFont.truetype(font=font, size=size)
# ----------------------------------------------------------------------------
def get_array(string, *, dropshadow_radius: int = None, **kwargs):
if dropshadow_radius is not None:
offset_x = int(np.ceil(dropshadow_radius*2/3))
offset_y = int(np.ceil(dropshadow_radius*2/3))
return _get_array_priv(string, dropshadow_radius=dropshadow_radius, offset_x=offset_x, offset_y=offset_y, **kwargs)
else:
return _get_array_priv(string, **kwargs)
@functools.lru_cache(maxsize=10000)
def _get_array_priv(
string: str, *,
size: int = 32,
max_width: Optional[int] = None,
max_height: Optional[int] = None,
min_size=10,
shrink_coef=0.8,
dropshadow_radius: int = None,
offset_x: int = None,
offset_y: int = None,
**kwargs
):
cur_size = size
array = None
while True:
if dropshadow_radius is not None:
# separate implementation for dropshadow text rendering
array = _get_array_impl_dropshadow(
string, size=cur_size, radius=dropshadow_radius, offset_x=offset_x, offset_y=offset_y, **kwargs)
else:
array = _get_array_impl(string, size=cur_size, **kwargs)
height, width, _ = array.shape
if (max_width is None or width <= max_width) and (max_height is None or height <= max_height) or (cur_size <= min_size):
break
cur_size = max(int(cur_size * shrink_coef), min_size)
return array
# ----------------------------------------------------------------------------
@functools.lru_cache(maxsize=10000)
def _get_array_impl(string, *, font=None, size=32, outline=0, outline_pad=3, outline_coef=3, outline_exp=2, line_pad: int = None):
pil_font = get_pil_font(font=font, size=size)
lines = [pil_font.getmask(line, 'L') for line in string.split('\n')]
lines = [np.array(line, dtype=np.uint8).reshape(
[line.size[1], line.size[0]]) for line in lines]
width = max(line.shape[1] for line in lines)
lines = [np.pad(line, ((0, 0), (0, width - line.shape[1])),
mode='constant') for line in lines]
line_spacing = line_pad if line_pad is not None else size // 2
lines = [np.pad(line, ((0, line_spacing), (0, 0)), mode='constant')
for line in lines[:-1]] + lines[-1:]
mask = np.concatenate(lines, axis=0)
alpha = mask
if outline > 0:
mask = np.pad(mask, int(np.ceil(outline * outline_pad)),
mode='constant', constant_values=0)
alpha = mask.astype(np.float32) / 255
alpha = scipy.ndimage.gaussian_filter(alpha, outline)
alpha = 1 - np.maximum(1 - alpha * outline_coef, 0) ** outline_exp
alpha = (alpha * 255 + 0.5).clip(0, 255).astype(np.uint8)
alpha = np.maximum(alpha, mask)
return np.stack([mask, alpha], axis=-1)
# ----------------------------------------------------------------------------
@functools.lru_cache(maxsize=10000)
def _get_array_impl_dropshadow(string, *, font=None, size=32, radius: int, offset_x: int, offset_y: int, line_pad: int = None, **kwargs):
assert (offset_x > 0) and (offset_y > 0)
pil_font = get_pil_font(font=font, size=size)
lines = [pil_font.getmask(line, 'L') for line in string.split('\n')]
lines = [np.array(line, dtype=np.uint8).reshape(
[line.size[1], line.size[0]]) for line in lines]
width = max(line.shape[1] for line in lines)
lines = [np.pad(line, ((0, 0), (0, width - line.shape[1])),
mode='constant') for line in lines]
line_spacing = line_pad if line_pad is not None else size // 2
lines = [np.pad(line, ((0, line_spacing), (0, 0)), mode='constant')
for line in lines[:-1]] + lines[-1:]
mask = np.concatenate(lines, axis=0)
alpha = mask
mask = np.pad(mask, 2*radius + max(abs(offset_x), abs(offset_y)),
mode='constant', constant_values=0)
alpha = mask.astype(np.float32) / 255
alpha = scipy.ndimage.gaussian_filter(alpha, radius)
alpha = 1 - np.maximum(1 - alpha * 1.5, 0) ** 1.4
alpha = (alpha * 255 + 0.5).clip(0, 255).astype(np.uint8)
alpha = np.pad(alpha, [(offset_y, 0), (offset_x, 0)],
mode='constant')[:-offset_y, :-offset_x]
alpha = np.maximum(alpha, mask)
return np.stack([mask, alpha], axis=-1)
# ----------------------------------------------------------------------------
@functools.lru_cache(maxsize=10000)
def get_texture(string, bilinear=True, mipmap=True, **kwargs):
return gl_utils.Texture(image=get_array(string, **kwargs), bilinear=bilinear, mipmap=mipmap)
# ----------------------------------------------------------------------------
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