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250 lines
11 KiB
Python
Executable File
250 lines
11 KiB
Python
Executable File
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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__ __ _ _ ___ __ __
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\ \ / / (_) | | |__ \ \ \ / /
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\ \ / / _ __| | ___ ___ ) | \ V /
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\ \/ / | | / _` | / _ \ / _ \ / / > <
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\ / | | | (_| | | __/ | (_) | / /_ / . \
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\/ |_| \__,_| \___| \___/ |____| /_/ \_\
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Name: Video2X Controller
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Author: K4YT3X
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Date Created: Feb 24, 2018
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Last Modified: March 9, 2019
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Licensed under the GNU General Public License Version 3 (GNU GPL v3),
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available at: https://www.gnu.org/licenses/gpl-3.0.txt
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(C) 2018-2019 K4YT3X
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Description: Video2X is an automation software based on
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waifu2x image enlarging engine. It extracts frames from a
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video, enlarge it by a number of times without losing any
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details or quality, keeping lines smooth and edges sharp.
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"""
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from avalon_framework import Avalon
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from upscaler import Upscaler
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from upscaler import MODELS_AVAILABLE
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import GPUtil
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import argparse
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import json
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import os
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import psutil
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import shutil
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import tempfile
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import time
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import traceback
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VERSION = '2.6.0'
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# Each thread might take up to 2.5 GB during initialization.
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# (system memory, not to be confused with GPU memory)
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SYS_MEM_PER_THREAD = 2.5
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GPU_MEM_PER_THREAD = 3.5
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def process_arguments():
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"""Processes CLI arguments
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This function parses all arguments
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This allows users to customize options
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for the output video.
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"""
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parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
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# Video options
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basic_options = parser.add_argument_group('Basic Options')
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basic_options.add_argument('-i', '--input', help='Specify source video file/directory', action='store', default=False, required=True)
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basic_options.add_argument('-o', '--output', help='Specify output video file/directory', action='store', default=False, required=True)
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basic_options.add_argument('-m', '--method', help='Specify upscaling method', action='store', default='gpu', choices=['cpu', 'gpu', 'cudnn'], required=True)
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basic_options.add_argument('-d', '--driver', help='Waifu2x driver', action='store', default='waifu2x_caffe', choices=['waifu2x_caffe', 'waifu2x_converter'])
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basic_options.add_argument('-y', '--model_type', help='Specify model to use', action='store', default='models/cunet', choices=MODELS_AVAILABLE)
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basic_options.add_argument('-t', '--threads', help='Specify number of threads to use for upscaling', action='store', type=int, default=5)
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basic_options.add_argument('-c', '--config', help='Manually specify config file', action='store', default='{}\\video2x.json'.format(os.path.dirname(os.path.abspath(__file__))))
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# Scaling options
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# scaling_options = parser.add_argument_group('Scaling Options', required=True) # TODO: (width & height) || (factor)
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scaling_options = parser.add_argument_group('Scaling Options') # TODO: (width & height) || (factor)
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scaling_options.add_argument('--width', help='Output video width', action='store', type=int, default=False)
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scaling_options.add_argument('--height', help='Output video height', action='store', type=int, default=False)
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scaling_options.add_argument('-r', '--ratio', help='Scaling ratio', action='store', type=int, default=False)
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# Parse arguments
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return parser.parse_args()
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def print_logo():
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print('__ __ _ _ ___ __ __')
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print('\\ \\ / / (_) | | |__ \\ \\ \\ / /')
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print(' \\ \\ / / _ __| | ___ ___ ) | \\ V /')
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print(' \\ \\/ / | | / _` | / _ \\ / _ \\ / / > <')
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print(' \\ / | | | (_| | | __/ | (_) | / /_ / . \\')
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print(' \\/ |_| \\__,_| \\___| \\___/ |____| /_/ \\_\\')
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print('\n Video2X Video Enlarger')
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spaces = ((44 - len("Version {}".format(VERSION))) // 2) * " "
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print('{}\n{} Version {}\n{}'.format(Avalon.FM.BD, spaces, VERSION, Avalon.FM.RST))
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def check_memory():
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""" Check usable system memory
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Warn the user if insufficient memory is available for
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the number of threads that the user have chosen.
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"""
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memory_status = []
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# Get system available memory
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system_memory_available = psutil.virtual_memory().available / (1024 ** 3)
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memory_status.append(('system', system_memory_available))
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# Check if Nvidia-smi is available
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# GPUtil requires nvidia-smi.exe to interact with GPU
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if args.method == 'gpu' or args.method == 'cudnn':
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if not os.path.isfile('C:\\Program Files\\NVIDIA Corporation\\NVSMI\\nvidia-smi.exe'):
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# Nvidia System Management Interface not available
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Avalon.warning('Nvidia-smi not available, skipping available memory check')
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Avalon.warning('If you experience error \"cudaSuccess out of memory\", try reducing number of threads you\'re using')
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else:
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# "0" is GPU ID. Both waifu2x drivers use the first GPU available, therefore only 0 makes sense
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gpu_memory_available = (GPUtil.getGPUs()[0].memoryTotal - GPUtil.getGPUs()[0].memoryUsed) / 1024
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memory_status.append(('GPU', gpu_memory_available))
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# Go though each checkable memory type and check availability
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for memory_type, memory_available in memory_status:
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if memory_type == 'system':
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mem_per_thread = SYS_MEM_PER_THREAD
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else:
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mem_per_thread = GPU_MEM_PER_THREAD
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# If user doesn't even have enough memory to run even one thread
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if memory_available < mem_per_thread:
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Avalon.warning('You might have insufficient amount of {} memory available to run this program ({} GB)'.format(memory_type, memory_available))
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Avalon.warning('Proceed with caution')
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if args.threads > 1:
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if Avalon.ask('Reduce number of threads to avoid crashing?', True):
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args.threads = 1
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# If memory available is less than needed, warn the user
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elif memory_available < (mem_per_thread * args.threads):
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Avalon.warning('Each waifu2x-caffe thread will require up to 2.5 GB of system memory')
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Avalon.warning('You demanded {} threads to be created, but you only have {} GB {} memory available'.format(args.threads, round(memory_available, 4), memory_type))
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Avalon.warning('{} GB of {} memory is recommended for {} threads'.format(mem_per_thread * args.threads, memory_type, args.threads))
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Avalon.warning('With your current amount of {} memory available, {} threads is recommended'.format(memory_type, int(memory_available // mem_per_thread)))
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# Ask the user if he / she wants to change to the recommended
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# number of threads
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if Avalon.ask('Change to the recommended value?', True):
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args.threads = int(memory_available // mem_per_thread)
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else:
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Avalon.warning('Proceed with caution')
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def read_config(config_file):
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""" Reads configuration file
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Returns a dictionary read by JSON.
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"""
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with open(config_file, 'r') as raw_config:
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config = json.load(raw_config)
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return config
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# /////////////////// Execution /////////////////// #
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# This is not a library
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if __name__ != '__main__':
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Avalon.error('This file cannot be imported')
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raise ImportError('{} cannot be imported'.format(__file__))
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print_logo()
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# Process CLI arguments
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args = process_arguments()
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# Arguments sanity check
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if args.driver == 'waifu2x_converter' and args.width and args.height:
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Avalon.error('Waifu2x Converter CPP accepts only scaling ratio')
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exit(1)
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if (args.width or args.height) and args.ratio:
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Avalon.error('You can only specify either scaling ratio or output width and height')
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exit(1)
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if (args.width and not args.height) or (not args.width and args.height):
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Avalon.error('You must specify both width and height')
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exit(1)
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# Check available memory
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check_memory()
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# Read configurations from JSON
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config = read_config(args.config)
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# load waifu2x configuration
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if args.driver == 'waifu2x_caffe':
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waifu2x_settings = config['waifu2x_caffe']
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elif args.driver == 'waifu2x_converter':
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waifu2x_settings = config['waifu2x_converter']
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# read FFMPEG configuration
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ffmpeg_settings = config['ffmpeg']
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# load video2x settings
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video2x_cache_folder = config['video2x']['video2x_cache_folder']
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preserve_frames = config['video2x']['preserve_frames']
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# Create temp directories if they don't exist
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if not video2x_cache_folder:
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video2x_cache_folder = '{}\\video2x'.format(tempfile.gettempdir())
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if video2x_cache_folder and not os.path.isdir(video2x_cache_folder):
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if not os.path.isfile(video2x_cache_folder) and not os.path.islink(video2x_cache_folder):
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Avalon.warning('Specified cache folder/directory {} does not exist'.format(video2x_cache_folder))
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if Avalon.ask('Create folder/directory?', True):
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if os.mkdir(video2x_cache_folder) is None:
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Avalon.info('{} created'.format(video2x_cache_folder))
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else:
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Avalon.error('Unable to create {}'.format(video2x_cache_folder))
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Avalon.error('Aborting...')
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exit(1)
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else:
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Avalon.error('Specified cache folder/directory is a file/link')
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Avalon.error('Unable to continue, exiting...')
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exit(1)
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# Start execution
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try:
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# Start timer
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begin_time = time.time()
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if os.path.isfile(args.input):
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""" Upscale single video file """
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Avalon.info('Upscaling single video file: {}'.format(args.input))
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upscaler = Upscaler(input_video=args.input, output_video=args.output, method=args.method, waifu2x_settings=waifu2x_settings, ffmpeg_settings=ffmpeg_settings, waifu2x_driver=args.driver, scale_width=args.width, scale_height=args.height, scale_ratio=args.ratio, model_type=args.model_type, threads=args.threads, video2x_cache_folder=video2x_cache_folder)
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upscaler.run()
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upscaler.cleanup()
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elif os.path.isdir(args.input):
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""" Upscale videos in a folder/directory """
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Avalon.info('Upscaling videos in folder/directory: {}'.format(args.input))
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for input_video in [f for f in os.listdir(args.input) if os.path.isfile(os.path.join(args.input, f))]:
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output_video = '{}\\{}'.format(args.output, input_video)
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upscaler = Upscaler(input_video=os.path.join(args.input, input_video), output_video=output_video, method=args.method, waifu2x_settings=waifu2x_settings, ffmpeg_settings=ffmpeg_settings, waifu2x_driver=args.driver, scale_width=args.width, scale_height=args.height, scale_ratio=args.ratio, model_type=args.model_type, threads=args.threads, video2x_cache_folder=video2x_cache_folder)
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upscaler.run()
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upscaler.cleanup()
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else:
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Avalon.error('Input path is neither a file nor a folder/directory')
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raise FileNotFoundError('{} is neither file nor folder/directory'.format(args.input))
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Avalon.info('Program completed, taking {} seconds'.format(round((time.time() - begin_time), 5)))
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except Exception:
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Avalon.error('An exception has occurred')
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traceback.print_exc()
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finally:
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# Remove Video2X Cache folder
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try:
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if not preserve_frames:
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shutil.rmtree(video2x_cache_folder)
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except FileNotFoundError:
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pass
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