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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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def get_default_font(): |
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url = 'http://fonts.gstatic.com/s/opensans/v17/mem8YaGs126MiZpBA-U1UpcaXcl0Aw.ttf' |
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return dnnlib.util.open_url(url, return_filename=True) |
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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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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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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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@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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@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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@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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