def process_amt_results(filename, output_dir, overwrite, gen_apprv_cmnt):
input_file = basename(filename)
input_file_base, input_file_ext = splitext(input_file)
output_name = '{0}.{1}'.format(input_file_base, 'json')
output_dir = dir_path(output_dir)
output_file = dir_join(output_dir, output_name)
results = read_results(filename)
scene_data = extract_scene_data(results)
save_json(scene_data, output_file, saveNonMin=False)
assignment_ids = set([scene['assignmentId'] for scene in scene_data])
create_approval_file(assignment_ids, filename, gen_apprv_cmnt)
create_reject_note_files(filename)
counter = 0
filename_base, filename_ext = splitext(output_name)
indv_output_dir = dir_path(dir_join(output_dir, filename_base + '_indv'))
for scene_data_single in scene_data:
#pdb.set_trace()
new_fn = '{0}_{1:02d}{2}'.format(scene_data_single['assignmentId'],
scene_data_single['hitIdx'],
filename_ext)
indv_output_file = dir_join(indv_output_dir, new_fn)
# Skip if already exists and no overwrite flag
if (not os.path.isfile(indv_output_file) or overwrite == True):
save_json(scene_data_single, indv_output_file, saveNonMin=False)
counter += 1
no_scene_data_name = '{0}_{1}{2}'.format(filename_base, 'noSceneData',
filename_ext)
no_scene_data_fn = dir_join(output_dir, no_scene_data_name)
for scene_datum in scene_data:
scene_datum['counts'] = extract_scene_stats(scene_datum['scene'])
scene_datum['sceneType'] = scene_datum['scene']['sceneType']
del scene_datum['scene']
save_json(scene_data, no_scene_data_fn, saveNonMin=True)
no_scene_data_name = '{0}_{1}{2}'.format(filename_base,
'noSceneNoCountsData',
filename_ext)
no_scene_data_fn = dir_join(output_dir, no_scene_data_name)
for scene_datum in scene_data:
del scene_datum['counts']
save_json(scene_data, no_scene_data_fn, saveNonMin=True)
def process_amt_results(filename, output_dir, overwrite, gen_apprv_cmnt):
input_file = basename(filename)
input_file_base, input_file_ext = splitext(input_file)
output_name = "{0}.{1}".format(input_file_base, "json")
output_dir = dir_path(output_dir)
output_file = dir_join(output_dir, output_name)
results = read_results(filename)
scene_data = extract_scene_data(results)
save_json(scene_data, output_file, saveNonMin=False)
assignment_ids = set([scene["assignmentId"] for scene in scene_data])
create_approval_file(assignment_ids, filename, gen_apprv_cmnt)
create_reject_note_files(filename)
counter = 0
filename_base, filename_ext = splitext(output_name)
indv_output_dir = dir_path(dir_join(output_dir, filename_base + "_indv"))
for scene_data_single in scene_data:
# pdb.set_trace()
new_fn = "{0}_{1:02d}{2}".format(scene_data_single["assignmentId"], scene_data_single["hitIdx"], filename_ext)
indv_output_file = dir_join(indv_output_dir, new_fn)
# Skip if already exists and no overwrite flag
if not os.path.isfile(indv_output_file) or overwrite == True:
save_json(scene_data_single, indv_output_file, saveNonMin=False)
counter += 1
no_scene_data_name = "{0}_{1}{2}".format(filename_base, "noSceneData", filename_ext)
no_scene_data_fn = dir_join(output_dir, no_scene_data_name)
for scene_datum in scene_data:
scene_datum["counts"] = extract_scene_stats(scene_datum["scene"])
scene_datum["sceneType"] = scene_datum["scene"]["sceneType"]
del scene_datum["scene"]
save_json(scene_data, no_scene_data_fn, saveNonMin=True)
no_scene_data_name = "{0}_{1}{2}".format(filename_base, "noSceneNoCountsData", filename_ext)
no_scene_data_fn = dir_join(output_dir, no_scene_data_name)
for scene_datum in scene_data:
del scene_datum["counts"]
save_json(scene_data, no_scene_data_fn, saveNonMin=True)
from os.path import abspath, dirname
from os.path import join as dir_join
import tensorflow as tf
from configparser import SafeConfigParser
# File hierarchy
_python_dir = dirname(abspath(__file__))
_proyect_dir = dirname(_python_dir)
_config_dir = dir_join(_proyect_dir, 'config')
_log_dir_root = dir_join(_proyect_dir, 'log')
_data_dir = dir_join(_proyect_dir, 'data')
# Configuration parser
cfg_parser = SafeConfigParser()
cfg_parser.read(dir_join(_config_dir, 'cfg_model.ini'))
# Private variables
_initializer = cfg_parser.get(section='train', option='initializer')
_normalization = cfg_parser.get(section='train', option='normalization')
_batch_size = cfg_parser.getint(section='train', option='batch_size')
def safe_div(numerator, denominator, name='safe_div'):
"""Divides two values, returning 0 if the denominator is <= 0.
Args:
numerator: A real `Tensor`.
denominator: A real `Tensor`, with dtype matching `numerator`.
name: Name for the returned op.
Returns:
0 if `denominator` <= 0, else `numerator` / `denominator`
# Django settings for {{ project_name }} project.
from os.path import join as dir_join
import sys
PROJECT_ROOT = '{{ project_directory }}'
sys.path.append(dir_join(PROJECT_ROOT, 'apps'))
DEBUG = True
TEMPLATE_DEBUG = DEBUG
ADMINS = (
# ('Your Name', '*****@*****.**'),
)
MANAGERS = ADMINS
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3', # Add 'postgresql_psycopg2', 'mysql', 'sqlite3' or 'oracle'.
'NAME': 'dev.{{ project_name }}.db', # Or path to database file if using sqlite3.
'USER': '', # Not used with sqlite3.
'PASSWORD': '', # Not used with sqlite3.
'HOST': '', # Set to empty string for localhost. Not used with sqlite3.
'PORT': '', # Set to empty string for default. Not used with sqlite3.
}
}
# Local time zone for this installation. Choices can be found here:
# http://en.wikipedia.org/wiki/List_of_tz_zones_by_name