/
start_tool.py
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/
start_tool.py
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import logging
import ntpath
import os
import threading
import time
import zipfile
from argparse import ArgumentParser
from typing import Optional
import wget
from OpenGL.GL import GL_MAJOR_VERSION, GL_MINOR_VERSION, glGetIntegerv
from data.data_handler import ProcessedNNHandler
from definitions import DATA_PATH, CameraPose
from gui.constants import StatisticLink
from gui.ui_window import OptionGui
from opengl_helper.screenshot import create_screenshot
from processing.network_processing import NetworkProcessor
from utility.file import FileHandler
from utility.log_handling import setup_logger
from utility.performance import track_time
from utility.window import Window, WindowHandler
def download_and_unzip_sample() -> str:
output_directory = DATA_PATH
filename = wget.download(
'https://drive.google.com/uc?export=download&id=1EpsubJhHH4shqzDhsBB0SHsBjWgWa03S', out=output_directory)
zip_filepath = os.path.join(output_directory, filename)
with zipfile.ZipFile(zip_filepath, 'r') as zip_ref:
zip_ref.extractall(DATA_PATH)
return os.path.join(DATA_PATH, 'sample_model.pro.npz')
def open_processed_network(option_gui: OptionGui, filename: str) -> None:
data_loader: ProcessedNNHandler = ProcessedNNHandler(filename)
option_gui.processing_config['prune_percentage'] = 0.9
option_gui.processing_setting.set()
option_gui.settings['network_name'] = ntpath.basename(
filename) + '_processed'
option_gui.update_layer(data_loader.layer_data, processed_nn=data_loader)
def compute_render(some_name: str) -> None:
global options_gui
global use_sample
if use_sample:
global sample_filepath
logging.info('Loading sample model...')
open_processed_network(options_gui, sample_filepath)
width, height = 1920, 1200
FileHandler().read_statistics()
window_handler: WindowHandler = WindowHandler()
window: Window = window_handler.create_window()
window.set_callbacks()
window.activate()
logging.info(
f'OpenGL Version: {glGetIntegerv(GL_MAJOR_VERSION)}.{glGetIntegerv(GL_MINOR_VERSION)}')
network_processor: Optional[NetworkProcessor] = None
@track_time(track_recursive=False)
def frame() -> None:
window_handler.update()
if network_processor is not None:
if 'trigger_network_sample' in options_gui.settings and options_gui.settings['trigger_network_sample'] > 0:
network_processor.reset_edges()
options_gui.settings['trigger_network_sample'] = 0
network_processor.process(options_gui.settings['action_state'])
network_processor.render(
window.cam, options_gui.render_config, options_gui.settings['show_class'])
if StatisticLink.SAMPLE_COUNT in options_gui.settings:
options_gui.settings[StatisticLink.SAMPLE_COUNT].set(
network_processor.edge_processor.point_count)
if StatisticLink.EDGE_COUNT in options_gui.settings:
options_gui.settings[StatisticLink.EDGE_COUNT].set(
network_processor.edge_processor.get_edge_count())
if StatisticLink.CELL_COUNT in options_gui.settings:
options_gui.settings[StatisticLink.CELL_COUNT].set(
network_processor.grid_processor.grid.grid_cell_count_overall)
if StatisticLink.PRUNED_EDGES in options_gui.settings:
options_gui.settings[StatisticLink.PRUNED_EDGES].set(
network_processor.network.pruned_edges)
window.swap()
while options_gui is None or (
len(options_gui.settings['current_layer_data']) == 0 and not options_gui.settings['Closed']):
window_handler.update()
time.sleep(5)
if not options_gui.settings['Closed']:
print('Start building network: ' +
str(options_gui.settings['current_layer_data']))
options_gui.settings['update_model'] = False
network_processor = NetworkProcessor(options_gui.settings['current_layer_data'],
options_gui.processing_config,
importance_data=options_gui.settings['importance_data'],
processed_nn=options_gui.settings['processed_nn'])
window.cam.base = network_processor.get_node_mid()
window.cam.set_position(CameraPose.LEFT)
fps: float = 120
frame_count: int = 0
to_pause_time: float = 0
last_frame_count: int = 0
checked_frame_count: int = -1
check_time: float = time.perf_counter()
last_time: float = time.perf_counter()
while window.is_active() and not options_gui.settings['Closed']:
if options_gui.settings['update_model']:
options_gui.settings['update_model'] = False
network_processor.delete()
print('Rebuilding network: ' +
str(options_gui.settings['current_layer_data']))
network_processor = NetworkProcessor(options_gui.settings['current_layer_data'],
options_gui.processing_config,
importance_data=options_gui.settings['importance_data'],
processed_nn=options_gui.settings['processed_nn'])
window.cam.base = network_processor.get_node_mid()
window.cam.set_position(CameraPose.LEFT)
frame()
if window.screenshot:
if 'network_name' in options_gui.settings.keys():
create_screenshot(
width, height, options_gui.settings['network_name'])
else:
create_screenshot(width, height)
window.screenshot = False
elif window.record:
window.frame_id += 1
if 'network_name' in options_gui.settings.keys():
create_screenshot(
width, height, options_gui.settings['network_name'], frame_id=window.frame_id)
else:
create_screenshot(width, height, frame_id=window.frame_id)
frame_count += 1
if time.perf_counter() - check_time > 1.0:
options_gui.settings[StatisticLink.FPS].set(float(
f'{float(frame_count - checked_frame_count) / (time.perf_counter() - check_time):.2f}'))
checked_frame_count = frame_count
check_time = time.perf_counter()
if 'save_file' in options_gui.settings.keys() and options_gui.settings['save_file']:
network_processor.save_model(
options_gui.settings['save_processed_nn_path'])
options_gui.settings['save_file'] = False
current_time: float = time.perf_counter()
elapsed_time: float = current_time - last_time
if elapsed_time < 1.0 / fps:
if elapsed_time > 0.001:
to_pause_time += (float(frame_count -
last_frame_count) / fps) - elapsed_time
last_frame_count = frame_count
last_time = current_time
if to_pause_time > 0.005:
time.sleep(to_pause_time)
paused_for: float = time.perf_counter() - current_time
to_pause_time -= paused_for
last_time += paused_for
else:
last_frame_count = frame_count
last_time = current_time
to_pause_time = 0 if to_pause_time < 0 else to_pause_time - \
(elapsed_time - 1.0 / fps)
network_processor.delete()
FileHandler().write_statistics()
window_handler.destroy()
options_gui.destroy()
def parse_args() -> bool:
parser = ArgumentParser(prog='Start nn_vis tool')
parser.add_argument('--demo', action='store_true',
help='Download sample of a processed model and render it with 90% pruned edges instead of generating a random model.')
args = parser.parse_args()
return args.demo
if __name__ == '__main__':
global options_gui
options_gui = OptionGui()
global sample_filepath
sample_filepath = 'sample_model.pro.npz'
global use_sample
use_sample = parse_args()
setup_logger('tool')
if use_sample:
expected_sample_path = os.path.join(DATA_PATH, sample_filepath)
if not os.path.exists(expected_sample_path):
logging.info(
f'Downloading sample model to "{expected_sample_path}". This might take a minute ...')
sample_filepath = download_and_unzip_sample()
else:
logging.info(
f'Using sample model at "{expected_sample_path}"')
sample_filepath = expected_sample_path
compute_render_thread: threading.Thread = threading.Thread(
target=compute_render, args=(1,))
compute_render_thread.setDaemon(True)
compute_render_thread.start()
options_gui.start()