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import argparse
import multiprocessing as mp
import os
import numpy as np
from dataclasses import dataclass
from tqdm import tqdm
def numericalize(cmd, n=64):
"""NOTE: shall only be called after normalization"""
cmd = ((cmd) / 30 * n).round().clip(min=0, max=n-1).astype(int)
return cmd
def denumericalize(cmd, n=64):
cmd = cmd / n * 30
return cmd
def cal_aux_bezier_pts(font_seq, opts):
"""
calculate aux pts along bezier curves
"""
pts_aux_all = []
for j in range(opts.char_num):
char_seq = font_seq[j] # shape: opts.max_len ,12
pts_aux_char = []
for k in range(opts.max_seq_len):
stroke_seq = char_seq[k]
stroke_cmd = np.argmax(stroke_seq[:4], -1)
stroke_seq[4:] = denumericalize(numericalize(stroke_seq[4:]))
p0, p1, p2, p3 = stroke_seq[4:6], stroke_seq[6:8], stroke_seq[8:10], stroke_seq[10:12]
pts_aux_stroke = []
if stroke_cmd == 0:
for t in range(6):
pts_aux_stroke.append(0)
elif stroke_cmd == 1: # move
for t in [0.25, 0.5, 0.75]:
coord_t = p0 + t*(p3-p0)
pts_aux_stroke.append(coord_t[0])
pts_aux_stroke.append(coord_t[1])
elif stroke_cmd == 2: # line
for t in [0.25, 0.5, 0.75]:
coord_t = p0 + t*(p3-p0)
pts_aux_stroke.append(coord_t[0])
pts_aux_stroke.append(coord_t[1])
elif stroke_cmd == 3: # curve
for t in [0.25, 0.5, 0.75]:
coord_t = (1-t)*(1-t)*(1-t)*p0 + 3*t*(1-t)*(1-t)*p1 + 3*t*t*(1-t)*p2 + t*t*t*p3
pts_aux_stroke.append(coord_t[0])
pts_aux_stroke.append(coord_t[1])
pts_aux_stroke = np.array(pts_aux_stroke)
pts_aux_char.append(pts_aux_stroke)
pts_aux_char = np.array(pts_aux_char)
pts_aux_all.append(pts_aux_char)
pts_aux_all = np.array(pts_aux_all)
return pts_aux_all
def relax_rep(opts):
"""
relaxing the sequence representation, details are shown in paper
"""
data_path = os.path.join(opts.output_path, opts.language, opts.split)
font_dirs = os.listdir(data_path)
font_dirs.sort()
num_fonts = len(font_dirs)
print(f"Number {opts.split} fonts before processing", num_fonts)
num_processes = mp.cpu_count() - 1
# num_processes = 1
fonts_per_process = num_fonts // num_processes + 1
def process(process_id):
for i in tqdm(range(process_id * fonts_per_process, (process_id + 1) * fonts_per_process)):
if i >= num_fonts:
break
font_dir = os.path.join(data_path, font_dirs[i])
font_seq = np.load(os.path.join(font_dir, 'sequence.npy')).reshape(opts.char_num, opts.max_seq_len, -1)
font_len = np.load(os.path.join(font_dir, 'seq_len.npy')).reshape(-1)
cmd = font_seq[:, :, :4]
args = font_seq[:, :, 4:]
ret = []
for j in range(opts.char_num):
char_cmds = cmd[j]
char_args = args[j]
char_len = font_len[j]
new_args = []
for k in range(char_len):
cur_cls = np.argmax(char_cmds[k], -1)
cur_arg = char_args[k]
if k - 1 > -1:
pre_arg = char_args[k - 1]
if cur_cls == 1: # when k == 0, cur_cls == 1
cur_arg = np.concatenate((np.array([cur_arg[-2], cur_arg[-1]]), cur_arg), -1)
else:
cur_arg = np.concatenate((np.array([pre_arg[-2], pre_arg[-1]]), cur_arg), -1)
new_args.append(cur_arg)
while(len(new_args)) < opts.max_seq_len:
new_args.append(np.array([0, 0, 0, 0, 0, 0, 0, 0]))
new_args = np.array(new_args)
new_seq = np.concatenate((char_cmds, new_args),-1)
ret.append(new_seq)
ret = np.array(ret)
# write relaxed version of sequence.npy
np.save(os.path.join(font_dir, 'sequence_relaxed.npy'), ret.reshape(opts.char_num, -1))
pts_aux = cal_aux_bezier_pts(ret, opts)
np.save(os.path.join(font_dir, 'pts_aux.npy'), pts_aux)
processes = [mp.Process(target=process, args=[pid]) for pid in range(num_processes)]
for p in processes:
p.start()
for p in processes:
p.join()
def main():
parser = argparse.ArgumentParser(description="relax representation")
parser.add_argument("--language", type=str, default='eng', choices=['eng', 'chn', 'tha'])
parser.add_argument("--data_path", type=str, default='./Font_Dataset', help="Path to Dataset")
parser.add_argument("--output_path", type=str, default='../data/vecfont_dataset_/', help="Path to write the database to")
parser.add_argument("--split", type=str, default='train')
opts = parser.parse_args()
relax_rep(opts)
if __name__ == "__main__":
main() |