# 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) #---------------------------------------------------------------------------- @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) #----------------------------------------------------------------------------