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(