def set_configuration(self):
# Check training variables
with tf.name_scope("train_var"):
all_vars = tf.trainable_variables()
enc_var = [v for v in all_vars if 'Encoder' in v.op.name or 'encoder' in v.op.name]
print(cyan('================== ENCODER ==================='))
slim.model_analyzer.analyze_vars(enc_var, print_info=True)
d_var = [v for v in all_vars if 'Depth' in v.op.name or 'depth' in v.op.name]
print(cyan('================ DEPTH branch ================'))
slim.model_analyzer.analyze_vars(d_var, print_info=True)
p_var = [v for v in all_vars if 'Pixel' in v.op.name or 'pixel' in v.op.name]
print(cyan('================ PIXEL branch ================'))
slim.model_analyzer.analyze_vars(p_var, print_info=True)
m_var = [v for v in all_vars if 'Mask' in v.op.name or 'mask' in v.op.name]
print(cyan('================ MASK branch ================='))
slim.model_analyzer.analyze_vars(m_var, print_info=True)
self.train_summary_op = tf.summary.merge_all(key='train')
# Set up the saver
self.saver = tf.train.Saver(max_to_keep=100)
self.pretrain_saver = tf.train.Saver(var_list=all_vars, max_to_keep=1)
self.pretrain_saver_enc = tf.train.Saver(var_list=enc_var, max_to_keep=1)
self.pretrain_saver_d = tf.train.Saver(var_list=d_var, max_to_keep=1)
self.pretrain_saver_p = tf.train.Saver(var_list=p_var, max_to_keep=1)
self.pretrain_saver_m = tf.train.Saver(var_list=m_var, max_to_keep=1)
# Set up training session
with tf.name_scope('train_session_config'):
self.summary_writer = tf.summary.FileWriter(self.checkpoint_dir)
self.supervisor = tf.train.Supervisor(logdir=self.checkpoint_dir, is_chief=True, saver=None, summary_op=None,
summary_writer=self.summary_writer, save_summaries_secs=300,
save_model_secs=600, global_step=self.global_step)
session_config = tf.ConfigProto(allow_soft_placement=True, gpu_options=tf.GPUOptions(allow_growth=True),
device_count={'GPU':1})
self.session = self.supervisor.prepare_or_wait_for_session(config=session_config)
# Reload the checkpoint if exist
with tf.name_scope('train_checkpoint'):
if self.continue_train:
if self.checkpoint_dir is not None:
# checkpoint = tf.train.latest_checkpoint(checkpoint_dir)
print(yellow('Restoring latest checkpoint path: {}'.format(self.checkpoint_dir)))
self.pretrain_saver.restore(self.session, self.checkpoint_dir)
def put_images_pairs_in_folder(pair_list, dest_folder, set_count):
list_num_total = len(pair_list)
for i, pair in enumerate(pair_list):
temp_folder = os.path.join(dest_folder,
'set_ori{}'.format(i + set_count))
if not os.path.exists(temp_folder):
os.makedirs(temp_folder)
print('Moving {}th pair out of {} pairs'.format(i, list_num_total))
try:
move(pair[0][0], temp_folder) # D5 jpg
move(pair[0][1], temp_folder) # D5 cv2
move(pair[1][0], temp_folder) # p20 jpg
move(pair[1][1], temp_folder) # p20 dng
move_folders(pair[2], temp_folder) # zed folders
except:
print(yellow('File does not exists '))
pass
print(magenta('Finishing moving images in pairs'))
print(
red('[Error] Select at least one device to run: --p20 / --zed / --d5'
))
exit(-1)
print(cyan('============== Selected Devices ================'))
print(cyan('{}'.format(processes)))
print(cyan('==================== Guide ====================='))
print(cyan('Mouse LEFT click to record videos.'))
print(cyan('Mouse RIGHT click to exit the program.'))
make_dir_if_not_exists(__ZED_IMG_PATH__)
make_dir_if_not_exists(__P20_IMG_PATH__)
make_dir_if_not_exists(__D5_IMG_PATH__)
# Create logger
img_logger = logutils.create_logger(__VID_LOGGING_FILE__)
# Kill the process which blocks the camera connection
canon.killGphoto2Process()
print(
yellow('Make sure that all the devices are on and at the right mode!'))
# Collect events until released
with Listener(on_click=on_click_run) as listener:
listener.join()
# Alarm that this program is closed.
beep(3)
print('Done!')
import os
import cv2
from utils.print_utils import yellow, red
__BASE_DIR__ = '/media/dc2019/My Book/VID/VQM_data'
__TEST_DIR__ = os.path.join(__BASE_DIR__, 'zed/test')
__VALID_DIR__ = os.path.join(__BASE_DIR__, 'zed/validation')
sets = os.listdir(__TEST_DIR__)
for set in sets:
set_dir = os.path.join(__TEST_DIR__, set)
print(yellow(set_dir))
frames = os.listdir(set_dir)
for frame in frames:
print(os.path.join(set_dir, frame))
try:
img = cv2.imread(os.path.join(set_dir, frame))
except:
print(red(os.path.join(set_dir, frame)))
print('Done!')
def print_helpping_messages(self):
print(yellow('n: go to next folder \ p: go to previous folder'))
print(yellow('s: move items into a saving folder'))
print(yellow('h: move items into a hold folder'))
print(yellow('d: move items into a deleting folder'))