1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
|
import os
import sys
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../live-cortex/rpc/'))
from options.test_options import TestOptions
from options.dataset_options import DatasetOptions
from data import CreateRecursiveDataLoader
from models import create_model
from util.util import mkdirs
from shutil import copyfile, rmtree
from PIL import Image, ImageOps
import numpy as np
import cv2
from datetime import datetime
import re
import gevent
from img_ops import process_image, mix_next_image
from listener import Listener, read_sequence
module_name = 'pix2pix'
def load_opt():
opt_parser = TestOptions()
opt = opt_parser.parse()
data_opt_parser = DatasetOptions()
data_opt = data_opt_parser.parse(opt.unknown)
opt.nThreads = 1 # test code only supports nThreads = 1
opt.batchSize = 1 # test code only supports batchSize = 1
opt.serial_batches = True # no shuffle
opt.no_flip = True # no flip
data_opt.tag = get_tag(opt, data_opt)
opt.render_dir = opt.results_dir + opt.name + "/" + data_opt.tag + "/"
return opt, data_opt, data_opt_parser
def get_tag(opt, data_opt):
if data_opt.tag == '':
d = datetime.now()
tag = data_opt.tag = "{}_{}_{}".format(
opt.name,
'live',
d.strftime('%Y%m%d%H%M')
)
else:
tag = data_opt.tag
return tag
def create_render_dir(opt):
print("create render_dir: {}".format(opt.render_dir))
if os.path.exists(opt.render_dir):
rmtree(opt.render_dir)
mkdirs(opt.render_dir)
def load_first_frame(opt, data_opt, i=0):
start_img_path = os.path.join(opt.render_dir, "frame_{:05}.png".format(i))
if data_opt.just_copy:
copyfile(opt.start_img, start_img_path)
A_img = None
A_im = None
A_offset = 0
else:
print("preload {}".format(opt.start_img))
A_img = Image.open(opt.start_img).convert('RGB')
A_im = np.asarray(A_img)
A = process_image(opt, data_opt, A_im)
cv2.imwrite(start_img_path, A)
numz = re.findall(r'\d+', os.path.basename(opt.start_img))
# print(numz)
if len(numz) > 0:
A_offset = int(numz[0])
# print(A_offset)
if A_offset:
print(">> starting offset: {}".format(A_offset))
A_dir = opt.start_img.replace(numz[0], "{:05d}")
print(A_dir)
else:
print("Sequence not found")
return A_offset, A_im, A_dir
def process_live_input(opt, data_opt, rpc_client):
print(">>> Process live input")
if data_opt.processing:
print("Already processing...")
data_opt.processing = True
data_loader = CreateRecursiveDataLoader(opt)
dataset = data_loader.load_data()
create_render_dir(opt)
sequence = read_sequence(data_opt.sequence_name, opt.module_name)
print("Got sequence {}, {} images".format(data_opt.sequence, len(sequence)))
if len(sequence) == 0:
print("Got empty sequence...")
data_opt.processing = False
rpc_client.send_status('processing', False)
return
print("First image: {}".format(sequence[0]))
rpc_client.send_status('processing', True)
start_img_path = os.path.join(opt.render_dir, "frame_{:05d}.png".format(0))
copyfile(sequence[0], start_img_path)
model = create_model(opt)
sequence_i = 1
print("generating...")
for i, data in enumerate(data_loader):
if i >= opt.how_many:
print("generated {} images, exiting".format(i))
break
if data_opt.load_checkpoint is True:
model.save_dir = os.path.join(opt.checkpoints_dir, opt.module_name, data_opt.checkpoint_name)
model.load_network(model.netG, 'G', data_opt.epoch)
data_opt.load_checkpoint = False
if data_opt.load_sequence is True:
data_opt.load_sequence = False
new_sequence = read_sequence(data_opt.sequence_name)
if len(new_sequence) != 0:
print("Got sequence {}, {} images, first: {}".format(data_opt.sequence_name, len(new_sequence), new_sequence[0]))
sequence = new_sequence
sequence_i = 1
else:
print("Sequence not found")
if data_opt.seek_to != 1:
if data_opt.seek_to > 0 and data_opt.seek_to < len(sequence):
sequence_i = data_opt.seek_to
data_opt.seek_to = 1
model.set_input(data)
model.test()
visuals = model.get_current_visuals()
img_path = model.get_image_paths()
sequence_i = mix_next_image(opt, data_opt, rpc_client, visuals['fake_B'], i, sequence, sequence_i)
if data_opt.pause:
data_opt.pause = False
break
gevent.sleep(data_opt.frame_delay)
data_opt.processing = False
rpc_client.send_status('processing', False)
if __name__ == '__main__':
opt, data_opt, data_opt_parser = load_opt()
listener = Listener(opt, data_opt, data_opt_parser, process_live_input)
listener.connect()
|
