def __init__(self, window):
self.window = window
self.terminals = Dict()
self.expanded_term = None
self.current_context = None
self.contexts = Dict()
self.pop_out_contexts = Dict()
self.queue = Queue()
def images_and_states_to_records(images, states, features, ground_truth=None):
assert len(images) == len(states)
assert len(images) == len(features)
records = []
if ground_truth is None:
for img, state, feature in zip(images, states, features):
records.append(Dict(image=img, state=state, feature=feature))
else:
for img, gt, state, feature in zip(images, ground_truth, states,
features):
img = np.stack([img, gt])
records.append(Dict(image=img, state=state, feature=feature))
return records
def get_high_resolution_net(self, res):
if res not in self.high_res_nets:
print('Creating high_res_network for ', res)
net = Dict()
net.high_res_input = tf.placeholder(
tf.float32,
shape=(None, res[0], res[1], self.cfg.real_img_channels),
name='highres_in')
net.fake_input = self.fake_input
net.fake_input_feature = self.fake_input_feature
net.real_data = self.real_data
net.z = self.z
net.is_train = self.is_train
net.states = self.states
with tf.variable_scope('generator', reuse=True):
fake_output, net.generator_debug_output, net.generator_debugger = self.cfg.generator(
[net.fake_input, net.z, net.states],
is_train=net.is_train,
cfg=self.cfg,
high_res=net.high_res_input,
progress=0)
net.fake_output, net.new_states, net.high_res_output = fake_output
net.fake_logit, net.fake_embeddings, _ = self.cfg.critic(
images=net.fake_output, cfg=self.cfg, reuse=True, is_train=False)
self.high_res_nets[res] = net
return self.high_res_nets[res]
def __init__(self,
manager,
contexts,
name,
index,
pos,
start_callback=None,
restart_callback=None,
stop_callback=None):
self.manager = manager
self.contexts = contexts
self.name = name
self.index = index
self.pos = pos
self.status = 0
self.start_callback = start_callback
self.restart_callback = restart_callback
self.stop_callback = stop_callback
self.terminal_contexts = Dict()
for context_name in self.contexts:
self.add_context(context_name, self.contexts[context_name])
self.output = []
def get_next_RAW(self, batch_size, test=False):
if test:
batch = self.fake_dataset_test.get_next_batch(batch_size)[0]
else:
batch = self.fake_dataset.get_next_batch(batch_size)[0]
pool = []
for img in batch:
pool.append(Dict(image=img, state=self.get_initial_states(1)[0]))
return self.records_to_images_and_states(pool)
def fill_pool(self):
while len(self.image_pool) < self.target_pool_size:
batch, features = self.fake_dataset.get_next_batch(self.cfg.batch_size)
for i in range(len(batch)):
self.image_pool.append(
Dict(
image=batch[i],
state=self.get_initial_states(1)[0],
feature=features[i]))
self.image_pool = self.image_pool[:self.target_pool_size]
assert len(self.image_pool) == self.target_pool_size, '%d, %d' % (
len(self.image_pool), self.target_pool_size)
def update(self):
for tm_name in self.terminals.keys():
self.terminals[tm_name].update()
while not self.queue.empty():
func, data = self.queue.get()
if func == "add_terminal":
name = data
index = len(self.terminals)
self.contexts[index] = PageContext(
self.window.get_root_context())
cntxs = Dict(main=self.contexts["main"])
cntxs[index] = self.contexts[index]
self.terminals[index] = Terminal(
self, cntxs, name, index,
TerminalManager.get_rc_index(index))
self.contexts["main"].configure_page()
elif func == "set_terminal_attribute":
name, attrib, value = data
term = self.get_terminal(name)
if attrib == "start_callback":
term.set_start_callback(value)
elif attrib == "restart_callback":
term.set_restart_callback(value)
elif attrib == "stop_callback":
term.set_stop_callback(value)
elif attrib == "status":
term.update_status(value)
else:
log.error("Invalid Attribute Passed: " + attrib)
elif func == "append_to_terminal":
name, data, end = data
term = self.get_terminal(name)
term.append(data, end)
from artist import ArtistDataProvider
from fivek import FiveKDataProvider
from critics import critic
from agent import agent_generator
from util import Dict
from filters import *
cfg = Dict()
###########################################################################
###########################################################################
# Here is a list of parameters. Instead of hard coding them in the script, I summarize them here.
# You do not need to modify most of them except the dataset part (see bottom), unless for good reasons.
###########################################################################
###########################################################################
#--------------------------------------------------------------------------
###########################################################################
# Filter Parameters
###########################################################################
cfg.filters = [
ExposureFilter, GammaFilter, ImprovedWhiteBalanceFilter,
SaturationPlusFilter, ToneFilter, ContrastFilter, WNBFilter, ColorFilter
]
# Gamma = 1/x ~ x
cfg.curve_steps = 8
cfg.gamma_range = 3
cfg.exposure_range = 3.5
cfg.wb_range = 1.1
cfg.color_curve_range = (0.90, 1.10)
from json import dumps, loads
import log
from util import Dict
CONFIG = Dict(
log_level=0
)
def load_config():
try:
with open("config.json") as i:
data = loads(i.read())
for key in data.keys():
CONFIG[key] = data.get(key)
except FileNotFoundError as e:
log.info("Configuration file not found, generating one now.")
data = dumps(CONFIG, indent=4)
with open("config.json", 'w') as i:
i.write(data)
log.info("Please configure configuration file before executing again.")
exit(1)
def get_next_RAW_train_all(self):
batch = self.fake_dataset_train.get_all()[0]
pool = []
for img in batch:
pool.append(Dict(image=img, state=self.get_initial_states(1)[0]))
return self.records_to_images_and_states(pool)
import logging
import os
from atexit import register
from datetime import datetime
from inspect import stack
from io import StringIO
from threading import current_thread
from config import CONFIG
from util import Dict
LEVELS = Dict(NOTSET=0, DEBUG=1, INFO=2, WARNING=3, ERROR=4, CRITICAL=5)
PREFS = Dict(LEVEL=LEVELS.NOTSET,
SHOW_TAGS=True,
ENABLE_THREAD_TAG=True,
ENABLE_MODULE_TAG=True,
ENABLE_FUNC_TAG=True)
has_init = False
def init():
level = CONFIG.log_level
PREFS.LEVEL = level
_log_start(level)
def _log_start(level=LEVELS.NOTSET):
tm = datetime.now()
# file_name = str(manager).replace('-', '').replace(' ', '').replace(':', '.')
file_name = str(tm.year).zfill(4) + '.' + str(
