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text_utils.py
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text_utils.py
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from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
import scipy.io as sio
import os.path as osp
import random, os
import cv2
#import cPickle as cp
import _pickle as cp
import scipy.signal as ssig
import scipy.stats as sstat
import pygame, pygame.locals
from pygame import freetype
#import Image
from PIL import Image
import math
from common import *
import pickle
def sample_weighted(p_dict):
ps = list(p_dict.keys())
return p_dict[np.random.choice(ps,p=ps)]
def move_bb(bbs, t):
"""
Translate the bounding-boxes in by t_x,t_y.
BB : 2x4xn
T : 2-long np.array
"""
return bbs + t[:,None,None]
def crop_safe(arr, rect, bbs=[], pad=0):
"""
ARR : arr to crop
RECT: (x,y,w,h) : area to crop to
BBS : nx4 xywh format bounding-boxes
PAD : percentage to pad
Does safe cropping. Returns the cropped rectangle and
the adjusted bounding-boxes
"""
rect = np.array(rect)
rect[:2] -= pad
rect[2:] += 2*pad
v0 = [max(0,rect[0]), max(0,rect[1])]
v1 = [min(arr.shape[0], rect[0]+rect[2]), min(arr.shape[1], rect[1]+rect[3])]
arr = arr[v0[0]:v1[0],v0[1]:v1[1],...]
if len(bbs) > 0:
for i in range(len(bbs)):
bbs[i,0] -= v0[0]
bbs[i,1] -= v0[1]
return arr, bbs
else:
return arr
class BaselineState(object):
curve = lambda this, a: lambda x: a*x*x
differential = lambda this, a: lambda x: 2*a*x
a = [0.50, 0.05]
def get_sample(self):
"""
Returns the functions for the curve and differential for a and b
"""
sgn = 1.0
if np.random.rand() < 0.5:
sgn = -1
a = self.a[1]*np.random.randn() + sgn*self.a[0]
return {
'curve': self.curve(a),
'diff': self.differential(a),
}
class RenderFont(object):
"""
Outputs a rasterized font sample.
Output is a binary mask matrix cropped closesly with the font.
Also, outputs ground-truth bounding boxes and text string
"""
def __init__(self, data_dir='data', text_corpus_file='data/newsgroups/newsgroups.txt'):
# distribution over the type of text:
# whether to get a single word, paragraph or a line:
self.p_text = {0.0 : 'WORD',
0.0 : 'LINE',
1.0 : 'PARA'}
## TEXT PLACEMENT PARAMETERS:
self.f_shrink = 0.90
self.max_shrink_trials = 5 # 0.9^5 ~= 0.6
# the minimum number of characters that should fit in a mask
# to define the maximum font height.
self.min_nchar = 2
self.min_font_h = 16 #px : 0.6*12 ~ 7px <= actual minimum height
self.max_font_h = 120 #px
self.p_flat = 0.10
# curved baseline:
self.p_curved = 1.0
self.baselinestate = BaselineState()
# text-source : gets english text:
self.text_source = TextSource(min_nchar=self.min_nchar,
fn=text_corpus_file)
# get font-state object:
self.font_state = FontState(data_dir)
pygame.init()
def render_multiline(self,font,text):
"""
renders multiline TEXT on the pygame surface SURF with the
font style FONT.
A new line in text is denoted by \n, no other characters are
escaped. Other forms of white-spaces should be converted to space.
returns the updated surface, words and the character bounding boxes.
"""
# get the number of lines
lines = text.split('\n')
lengths = [len(l) for l in lines]
# font parameters:
line_spacing = font.get_sized_height() + 1
# initialize the surface to proper size:
line_bounds = font.get_rect(lines[np.argmax(lengths)])
fsize = (round(2.0*line_bounds.width), round(1.25*line_spacing*len(lines)))
surf = pygame.Surface(fsize, pygame.locals.SRCALPHA, 32)
bbs = []
space = font.get_rect('O')
x, y = 0, 0
for l in lines:
x = 0 # carriage-return
y += line_spacing # line-feed
for ch in l: # render each character
if ch.isspace(): # just shift
x += space.width
else:
# render the character
ch_bounds = font.render_to(surf, (x,y), ch)
ch_bounds.x = x + ch_bounds.x
ch_bounds.y = y - ch_bounds.y
x += ch_bounds.width
bbs.append(np.array(ch_bounds))
# get the union of characters for cropping:
r0 = pygame.Rect(bbs[0])
rect_union = r0.unionall(bbs)
# get the words:
words = ' '.join(text.split())
# crop the surface to fit the text:
bbs = np.array(bbs)
surf_arr, bbs = crop_safe(pygame.surfarray.pixels_alpha(surf), rect_union, bbs, pad=5)
surf_arr = surf_arr.swapaxes(0,1)
#self.visualize_bb(surf_arr,bbs)
return surf_arr, words, bbs
def render_curved(self, font, word_text):
"""
use curved baseline for rendering word
"""
wl = len(word_text)
isword = len(word_text.split())==1
# do curved iff, the length of the word <= 10
if not isword or wl > 10 or np.random.rand() > self.p_curved:
return self.render_multiline(font, word_text)
# create the surface:
lspace = font.get_sized_height() + 1
lbound = font.get_rect(word_text)
fsize = (round(2.0*lbound.width), round(3*lspace))
surf = pygame.Surface(fsize, pygame.locals.SRCALPHA, 32)
# baseline state
mid_idx = wl//2
BS = self.baselinestate.get_sample()
curve = [BS['curve'](i-mid_idx) for i in range(wl)]
curve[mid_idx] = -np.sum(curve) / (wl-1)
rots = [-int(math.degrees(math.atan(BS['diff'](i-mid_idx)/(font.size/2)))) for i in range(wl)]
bbs = []
# place middle char
rect = font.get_rect(word_text[mid_idx])
rect.centerx = surf.get_rect().centerx
rect.centery = surf.get_rect().centery + rect.height
rect.centery += curve[mid_idx]
ch_bounds = font.render_to(surf, rect, word_text[mid_idx], rotation=rots[mid_idx])
ch_bounds.x = rect.x + ch_bounds.x
ch_bounds.y = rect.y - ch_bounds.y
mid_ch_bb = np.array(ch_bounds)
# render chars to the left and right:
last_rect = rect
ch_idx = []
for i in range(wl):
#skip the middle character
if i==mid_idx:
bbs.append(mid_ch_bb)
ch_idx.append(i)
continue
if i < mid_idx: #left-chars
i = mid_idx-1-i
elif i==mid_idx+1: #right-chars begin
last_rect = rect
ch_idx.append(i)
ch = word_text[i]
newrect = font.get_rect(ch)
newrect.y = last_rect.y
if i > mid_idx:
newrect.topleft = (last_rect.topright[0]+2, newrect.topleft[1])
else:
newrect.topright = (last_rect.topleft[0]-2, newrect.topleft[1])
newrect.centery = max(newrect.height, min(fsize[1] - newrect.height, newrect.centery + curve[i]))
try:
bbrect = font.render_to(surf, newrect, ch, rotation=rots[i])
except ValueError:
bbrect = font.render_to(surf, newrect, ch)
bbrect.x = newrect.x + bbrect.x
bbrect.y = newrect.y - bbrect.y
bbs.append(np.array(bbrect))
last_rect = newrect
# correct the bounding-box order:
bbs_sequence_order = [None for i in ch_idx]
for idx,i in enumerate(ch_idx):
bbs_sequence_order[i] = bbs[idx]
bbs = bbs_sequence_order
# get the union of characters for cropping:
r0 = pygame.Rect(bbs[0])
rect_union = r0.unionall(bbs)
# crop the surface to fit the text:
bbs = np.array(bbs)
surf_arr, bbs = crop_safe(pygame.surfarray.pixels_alpha(surf), rect_union, bbs, pad=5)
surf_arr = surf_arr.swapaxes(0,1)
return surf_arr, word_text, bbs
def get_nline_nchar(self,mask_size,font_height,font_width):
"""
Returns the maximum number of lines and characters which can fit
in the MASK_SIZED image.
"""
H,W = mask_size
nline = int(np.ceil(H/(2*font_height)))
nchar = int(np.floor(W/font_width))
return nline,nchar
def place_text(self, text_arrs, back_arr, bbs):
areas = [-np.prod(ta.shape) for ta in text_arrs]
order = np.argsort(areas)
locs = [None for i in range(len(text_arrs))]
out_arr = np.zeros_like(back_arr)
for i in order:
ba = np.clip(back_arr.copy().astype(np.float), 0, 255)
ta = np.clip(text_arrs[i].copy().astype(np.float), 0, 255)
ba[ba > 127] = 1e8
intersect = ssig.fftconvolve(ba,ta[::-1,::-1],mode='valid')
safemask = intersect < 1e8
if not np.any(safemask): # no collision-free position:
#warn("COLLISION!!!")
return back_arr,locs[:i],bbs[:i],order[:i]
minloc = np.transpose(np.nonzero(safemask))
loc = minloc[np.random.choice(minloc.shape[0]),:]
locs[i] = loc
# update the bounding-boxes:
bbs[i] = move_bb(bbs[i],loc[::-1])
# blit the text onto the canvas
w,h = text_arrs[i].shape
out_arr[loc[0]:loc[0]+w,loc[1]:loc[1]+h] += text_arrs[i]
return out_arr, locs, bbs, order
def robust_HW(self,mask):
m = mask.copy()
m = (~mask).astype('float')/255
rH = np.median(np.sum(m,axis=0))
rW = np.median(np.sum(m,axis=1))
return rH,rW
def sample_font_height_px(self,h_min,h_max):
if np.random.rand() < self.p_flat:
rnd = np.random.rand()
else:
rnd = np.random.beta(2.0,2.0)
h_range = h_max - h_min
f_h = np.floor(h_min + h_range*rnd)
return f_h
def bb_xywh2coords(self,bbs):
"""
Takes an nx4 bounding-box matrix specified in x,y,w,h
format and outputs a 2x4xn bb-matrix, (4 vertices per bb).
"""
n,_ = bbs.shape
coords = np.zeros((2,4,n))
for i in range(n):
coords[:,:,i] = bbs[i,:2][:,None]
coords[0,1,i] += bbs[i,2]
coords[:,2,i] += bbs[i,2:4]
coords[1,3,i] += bbs[i,3]
return coords
def render_sample(self,font,mask):
"""
Places text in the "collision-free" region as indicated
in the mask -- 255 for unsafe, 0 for safe.
The text is rendered using FONT, the text content is TEXT.
"""
#H,W = mask.shape
H,W = self.robust_HW(mask)
f_asp = self.font_state.get_aspect_ratio(font)
# find the maximum height in pixels:
max_font_h = min(0.9*H, (1/f_asp)*W/(self.min_nchar+1))
max_font_h = min(max_font_h, self.max_font_h)
if max_font_h < self.min_font_h: # not possible to place any text here
return #None
# let's just place one text-instance for now
## TODO : change this to allow multiple text instances?
i = 0
while i < self.max_shrink_trials and max_font_h > self.min_font_h:
# if i > 0:
# print colorize(Color.BLUE, "shrinkage trial : %d"%i, True)
# sample a random font-height:
f_h_px = self.sample_font_height_px(self.min_font_h, max_font_h)
#print "font-height : %.2f (min: %.2f, max: %.2f)"%(f_h_px, self.min_font_h,max_font_h)
# convert from pixel-height to font-point-size:
f_h = self.font_state.get_font_size(font, f_h_px)
# update for the loop
max_font_h = f_h_px
i += 1
font.size = f_h # set the font-size
# compute the max-number of lines/chars-per-line:
nline,nchar = self.get_nline_nchar(mask.shape[:2],f_h,f_h*f_asp)
#print " > nline = %d, nchar = %d"%(nline, nchar)
assert nline >= 1 and nchar >= self.min_nchar
# sample text:
text_type = sample_weighted(self.p_text)
text = self.text_source.sample(nline,nchar,text_type)
if len(text)==0 or np.any([len(line)==0 for line in text]):
continue
#print colorize(Color.GREEN, text)
# render the text:
txt_arr,txt,bb = self.render_curved(font, text)
bb = self.bb_xywh2coords(bb)
# make sure that the text-array is not bigger than mask array:
if np.any(np.r_[txt_arr.shape[:2]] > np.r_[mask.shape[:2]]):
#warn("text-array is bigger than mask")
continue
# position the text within the mask:
text_mask,loc,bb, _ = self.place_text([txt_arr], mask, [bb])
if len(loc) > 0:#successful in placing the text collision-free:
return text_mask,loc[0],bb[0],text
return #None
def visualize_bb(self, text_arr, bbs):
ta = text_arr.copy()
for r in bbs:
cv.rectangle(ta, (r[0],r[1]), (r[0]+r[2],r[1]+r[3]), color=128, thickness=1)
plt.imshow(ta,cmap='gray')
plt.show()
class FontState(object):
"""
Defines the random state of the font rendering
"""
size = [50, 10] # normal dist mean, std
underline = 0.05
strong = 0.5
oblique = 0.2
wide = 0.5
strength = [0.05, 0.1] # uniform dist in this interval
underline_adjustment = [1.0, 2.0] # normal dist mean, std
kerning = [2, 5, 0, 20] # beta distribution alpha, beta, offset, range (mean is a/(a+b))
border = 0.25
random_caps = -1 ## don't recapitalize : retain the capitalization of the lexicon
capsmode = [str.lower, str.upper, str.capitalize] # lower case, upper case, proper noun
curved = 0.2
random_kerning = 0.2
random_kerning_amount = 0.1
def __init__(self, data_dir='data'):
char_freq_path = osp.join(data_dir, 'models/char_freq.cp')
font_model_path = osp.join(data_dir, 'models/font_px2pt.cp')
# get character-frequencies in the English language:
with open(char_freq_path,'rb') as f:
#self.char_freq = cp.load(f)
u = pickle._Unpickler(f)
u.encoding = 'latin1'
p = u.load()
self.char_freq = p
# get the model to convert from pixel to font pt size:
with open(font_model_path,'rb') as f:
#self.font_model = cp.load(f)
u = pickle._Unpickler(f)
u.encoding = 'latin1'
p = u.load()
self.font_model = p
# get the names of fonts to use:
self.FONT_LIST = osp.join(data_dir, 'fonts/fontlist.txt')
self.fonts = [os.path.join(data_dir,'fonts',f.strip()) for f in open(self.FONT_LIST)]
def get_aspect_ratio(self, font, size=None):
"""
Returns the median aspect ratio of each character of the font.
"""
if size is None:
size = 12 # doesn't matter as we take the RATIO
chars = ''.join(self.char_freq.keys())
w = np.array(self.char_freq.values())
# get the [height,width] of each character:
try:
sizes = font.get_metrics(chars,size)
good_idx = [i for i in range(len(sizes)) if sizes[i] is not None]
sizes,w = [sizes[i] for i in good_idx], w[good_idx]
sizes = np.array(sizes).astype('float')[:,[3,4]]
r = np.abs(sizes[:,1]/sizes[:,0]) # width/height
good = np.isfinite(r)
r = r[good]
w = w[good]
w /= np.sum(w)
r_avg = np.sum(w*r)
return r_avg
except:
return 1.0
def get_font_size(self, font, font_size_px):
"""
Returns the font-size which corresponds to FONT_SIZE_PX pixels font height.
"""
m = self.font_model[font.name]
return m[0]*font_size_px + m[1] #linear model
def sample(self):
"""
Samples from the font state distribution
"""
return {
'font': self.fonts[int(np.random.randint(0, len(self.fonts)))],
'size': self.size[1]*np.random.randn() + self.size[0],
'underline': np.random.rand() < self.underline,
'underline_adjustment': max(2.0, min(-2.0, self.underline_adjustment[1]*np.random.randn() + self.underline_adjustment[0])),
'strong': np.random.rand() < self.strong,
'oblique': np.random.rand() < self.oblique,
'strength': (self.strength[1] - self.strength[0])*np.random.rand() + self.strength[0],
'char_spacing': int(self.kerning[3]*(np.random.beta(self.kerning[0], self.kerning[1])) + self.kerning[2]),
'border': np.random.rand() < self.border,
'random_caps': np.random.rand() < self.random_caps,
'capsmode': random.choice(self.capsmode),
'curved': np.random.rand() < self.curved,
'random_kerning': np.random.rand() < self.random_kerning,
'random_kerning_amount': self.random_kerning_amount,
}
def init_font(self,fs):
"""
Initializes a pygame font.
FS : font-state sample
"""
font = freetype.Font(fs['font'], size=fs['size'])
font.underline = fs['underline']
font.underline_adjustment = fs['underline_adjustment']
font.strong = fs['strong']
font.oblique = fs['oblique']
font.strength = fs['strength']
char_spacing = fs['char_spacing']
font.antialiased = True
font.origin = True
return font
class TextSource(object):
"""
Provides text for words, paragraphs, sentences.
"""
def __init__(self, min_nchar, fn):
"""
TXT_FN : path to file containing text data.
"""
self.min_nchar = min_nchar
self.fdict = {'WORD':self.sample_word,
'LINE':self.sample_line,
'PARA':self.sample_para}
with open(fn,'r', encoding='utf-8') as f:
self.txt = [l.strip() for l in f.readlines()]
# distribution over line/words for LINE/PARA:
self.p_line_nline = np.array([0.85, 0.10, 0.05])
self.p_line_nword = [4,3,12] # normal: (mu, std)
self.p_para_nline = [1.0,1.0]#[1.7,3.0] # beta: (a, b), max_nline
self.p_para_nword = [1.7,3.0,10] # beta: (a,b), max_nword
# probability to center-align a paragraph:
self.center_para = 0.5
def check_symb_frac(self, txt, f=0.35):
"""
T/F return : T iff fraction of symbol/special-charcters in
txt is less than or equal to f (default=0.25).
"""
return np.sum([not ch.isalnum() for ch in txt])/(len(txt)+0.0) <= f
def is_good(self, txt, f=0.35):
"""
T/F return : T iff the lines in txt (a list of txt lines)
are "valid".
A given line l is valid iff:
1. It is not empty.
2. symbol_fraction > f
3. Has at-least self.min_nchar characters
4. Not all characters are i,x,0,O,-
"""
def is_txt(l):
char_ex = ['i','I','o','O','0','-']
chs = [ch in char_ex for ch in l]
return not np.all(chs)
return [ (len(l)> self.min_nchar
and self.check_symb_frac(l,f)
and is_txt(l)) for l in txt ]
def center_align(self, lines):
"""
PADS lines with space to center align them
lines : list of text-lines.
"""
ls = [len(l) for l in lines]
max_l = max(ls)
for i in range(len(lines)):
l = lines[i].strip()
dl = max_l-ls[i]
lspace = dl//2
rspace = dl-lspace
lines[i] = ' '*lspace+l+' '*rspace
return lines
def get_lines(self, nline, nword, nchar_max, f=0.35, niter=100):
def h_lines(niter=100):
lines = ['']
iter = 0
while not np.all(self.is_good(lines,f)) and iter < niter:
iter += 1
line_start = np.random.choice(len(self.txt)-nline)
lines = [self.txt[line_start+i] for i in range(nline)]
return lines
lines = ['']
iter = 0
while not np.all(self.is_good(lines,f)) and iter < niter:
iter += 1
lines = h_lines(niter=100)
# get words per line:
nline = len(lines)
for i in range(nline):
words = lines[i].split()
dw = len(words)-nword[i]
if dw > 0:
first_word_index = random.choice(range(dw+1))
lines[i] = ' '.join(words[first_word_index:first_word_index+nword[i]])
while len(lines[i]) > nchar_max: #chop-off characters from end:
if not np.any([ch.isspace() for ch in lines[i]]):
lines[i] = ''
else:
lines[i] = lines[i][:len(lines[i])-lines[i][::-1].find(' ')].strip()
if not np.all(self.is_good(lines,f)):
return #None
else:
return lines
def sample(self, nline_max,nchar_max,kind='WORD'):
return self.fdict[kind](nline_max,nchar_max)
def sample_word(self,nline_max,nchar_max,niter=100):
rand_line = self.txt[np.random.choice(len(self.txt))]
words = rand_line.split()
rand_word = random.choice(words)
iter = 0
while iter < niter and (not self.is_good([rand_word])[0] or len(rand_word)>nchar_max):
rand_line = self.txt[np.random.choice(len(self.txt))]
words = rand_line.split()
rand_word = random.choice(words)
iter += 1
if not self.is_good([rand_word])[0] or len(rand_word)>nchar_max:
return []
else:
return rand_word
def sample_line(self,nline_max,nchar_max):
nline = nline_max+1
while nline > nline_max:
nline = np.random.choice([1,2,3], p=self.p_line_nline)
# get number of words:
nword = [self.p_line_nword[2]*sstat.beta.rvs(a=self.p_line_nword[0], b=self.p_line_nword[1])
for _ in range(nline)]
nword = [max(1,int(np.ceil(n))) for n in nword]
lines = self.get_lines(nline, nword, nchar_max, f=0.35)
if lines is not None:
return '\n'.join(lines)
else:
return []
def sample_para(self,nline_max,nchar_max):
# get number of lines in the paragraph:
nline = nline_max*sstat.beta.rvs(a=self.p_para_nline[0], b=self.p_para_nline[1])
nline = max(1, int(np.ceil(nline)))
# get number of words:
nword = [self.p_para_nword[2]*sstat.beta.rvs(a=self.p_para_nword[0], b=self.p_para_nword[1])
for _ in range(nline)]
nword = [max(1,int(np.ceil(n))) for n in nword]
lines = self.get_lines(nline, nword, nchar_max, f=0.35)
if lines is not None:
# center align the paragraph-text:
if np.random.rand() < self.center_para:
lines = self.center_align(lines)
return '\n'.join(lines)
else:
return []