2021-10-13 12:00:23 +02:00
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# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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2021-10-07 11:55:26 +02:00
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#
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# NVIDIA CORPORATION and its licensors retain all intellectual property
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# and proprietary rights in and to this software, related documentation
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# and any modifications thereto. Any use, reproduction, disclosure or
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# distribution of this software and related documentation without an express
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# license agreement from NVIDIA CORPORATION is strictly prohibited.
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import functools
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from typing import Optional
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import dnnlib
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import numpy as np
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import PIL.Image
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import PIL.ImageFont
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import scipy.ndimage
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from . import gl_utils
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#----------------------------------------------------------------------------
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def get_default_font():
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url = 'http://fonts.gstatic.com/s/opensans/v17/mem8YaGs126MiZpBA-U1UpcaXcl0Aw.ttf' # Open Sans regular
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return dnnlib.util.open_url(url, return_filename=True)
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#----------------------------------------------------------------------------
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@functools.lru_cache(maxsize=None)
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def get_pil_font(font=None, size=32):
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if font is None:
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font = get_default_font()
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return PIL.ImageFont.truetype(font=font, size=size)
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#----------------------------------------------------------------------------
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def get_array(string, *, dropshadow_radius: int=None, **kwargs):
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if dropshadow_radius is not None:
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offset_x = int(np.ceil(dropshadow_radius*2/3))
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offset_y = int(np.ceil(dropshadow_radius*2/3))
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return _get_array_priv(string, dropshadow_radius=dropshadow_radius, offset_x=offset_x, offset_y=offset_y, **kwargs)
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else:
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return _get_array_priv(string, **kwargs)
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@functools.lru_cache(maxsize=10000)
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def _get_array_priv(
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string: str, *,
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size: int = 32,
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max_width: Optional[int]=None,
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max_height: Optional[int]=None,
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min_size=10,
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shrink_coef=0.8,
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dropshadow_radius: int=None,
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offset_x: int=None,
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offset_y: int=None,
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**kwargs
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):
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cur_size = size
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array = None
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while True:
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if dropshadow_radius is not None:
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# separate implementation for dropshadow text rendering
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array = _get_array_impl_dropshadow(string, size=cur_size, radius=dropshadow_radius, offset_x=offset_x, offset_y=offset_y, **kwargs)
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else:
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array = _get_array_impl(string, size=cur_size, **kwargs)
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height, width, _ = array.shape
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if (max_width is None or width <= max_width) and (max_height is None or height <= max_height) or (cur_size <= min_size):
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break
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cur_size = max(int(cur_size * shrink_coef), min_size)
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return array
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#----------------------------------------------------------------------------
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@functools.lru_cache(maxsize=10000)
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def _get_array_impl(string, *, font=None, size=32, outline=0, outline_pad=3, outline_coef=3, outline_exp=2, line_pad: int=None):
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pil_font = get_pil_font(font=font, size=size)
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lines = [pil_font.getmask(line, 'L') for line in string.split('\n')]
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lines = [np.array(line, dtype=np.uint8).reshape([line.size[1], line.size[0]]) for line in lines]
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width = max(line.shape[1] for line in lines)
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lines = [np.pad(line, ((0, 0), (0, width - line.shape[1])), mode='constant') for line in lines]
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line_spacing = line_pad if line_pad is not None else size // 2
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lines = [np.pad(line, ((0, line_spacing), (0, 0)), mode='constant') for line in lines[:-1]] + lines[-1:]
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mask = np.concatenate(lines, axis=0)
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alpha = mask
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if outline > 0:
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mask = np.pad(mask, int(np.ceil(outline * outline_pad)), mode='constant', constant_values=0)
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alpha = mask.astype(np.float32) / 255
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alpha = scipy.ndimage.gaussian_filter(alpha, outline)
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alpha = 1 - np.maximum(1 - alpha * outline_coef, 0) ** outline_exp
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alpha = (alpha * 255 + 0.5).clip(0, 255).astype(np.uint8)
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alpha = np.maximum(alpha, mask)
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return np.stack([mask, alpha], axis=-1)
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#----------------------------------------------------------------------------
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@functools.lru_cache(maxsize=10000)
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def _get_array_impl_dropshadow(string, *, font=None, size=32, radius: int, offset_x: int, offset_y: int, line_pad: int=None, **kwargs):
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assert (offset_x > 0) and (offset_y > 0)
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pil_font = get_pil_font(font=font, size=size)
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lines = [pil_font.getmask(line, 'L') for line in string.split('\n')]
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lines = [np.array(line, dtype=np.uint8).reshape([line.size[1], line.size[0]]) for line in lines]
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width = max(line.shape[1] for line in lines)
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lines = [np.pad(line, ((0, 0), (0, width - line.shape[1])), mode='constant') for line in lines]
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line_spacing = line_pad if line_pad is not None else size // 2
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lines = [np.pad(line, ((0, line_spacing), (0, 0)), mode='constant') for line in lines[:-1]] + lines[-1:]
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mask = np.concatenate(lines, axis=0)
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alpha = mask
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mask = np.pad(mask, 2*radius + max(abs(offset_x), abs(offset_y)), mode='constant', constant_values=0)
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alpha = mask.astype(np.float32) / 255
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alpha = scipy.ndimage.gaussian_filter(alpha, radius)
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alpha = 1 - np.maximum(1 - alpha * 1.5, 0) ** 1.4
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alpha = (alpha * 255 + 0.5).clip(0, 255).astype(np.uint8)
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alpha = np.pad(alpha, [(offset_y, 0), (offset_x, 0)], mode='constant')[:-offset_y, :-offset_x]
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alpha = np.maximum(alpha, mask)
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return np.stack([mask, alpha], axis=-1)
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#----------------------------------------------------------------------------
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@functools.lru_cache(maxsize=10000)
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def get_texture(string, bilinear=True, mipmap=True, **kwargs):
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return gl_utils.Texture(image=get_array(string, **kwargs), bilinear=bilinear, mipmap=mipmap)
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#----------------------------------------------------------------------------
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