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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(): | |
url = 'http://fonts.gstatic.com/s/opensans/v17/mem8YaGs126MiZpBA-U1UpcaXcl0Aw.ttf' # Open Sans regular | |
return dnnlib.util.open_url(url, return_filename=True) | |
#---------------------------------------------------------------------------- | |
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) | |
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 | |
#---------------------------------------------------------------------------- | |
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) | |
#---------------------------------------------------------------------------- | |
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) | |
#---------------------------------------------------------------------------- | |
def get_texture(string, bilinear=True, mipmap=True, **kwargs): | |
return gl_utils.Texture(image=get_array(string, **kwargs), bilinear=bilinear, mipmap=mipmap) | |
#---------------------------------------------------------------------------- | |