mirror of
https://github.com/k4yt3x/video2x.git
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358 lines
15 KiB
Python
358 lines
15 KiB
Python
#!/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: April 11, 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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Video2X is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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Video2X is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <https://www.gnu.org/licenses/>.
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Description: Video2X is an automation software based on waifu2x image
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enlarging engine. It extracts frames from a video, enlarge it by a
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number of times without losing any details or quality, keeping lines
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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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import argparse
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import GPUtil
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import json
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import os
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import psutil
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import re
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import shutil
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import sys
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import tempfile
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import time
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import traceback
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VERSION = '2.7.0'
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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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file_options = parser.add_argument_group('File Options')
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file_options.add_argument('-i', '--input', help='Source video file/directory', action='store', required=True)
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file_options.add_argument('-o', '--output', help='Output video file/directory', action='store', required=True)
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# upscaler options
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upscaler_options = parser.add_argument_group('Upscaler Options')
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upscaler_options.add_argument('-m', '--method', help='Upscaling method', action='store', default='gpu', choices=['cpu', 'gpu', 'cudnn'], required=True)
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upscaler_options.add_argument('-d', '--driver', help='Waifu2x driver', action='store', default='waifu2x_caffe', choices=['waifu2x_caffe', 'waifu2x_converter'])
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upscaler_options.add_argument('-y', '--model_dir', help='Folder containing model JSON files', action='store')
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upscaler_options.add_argument('-t', '--threads', help='Number of threads to use for upscaling', action='store', type=int, default=5)
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upscaler_options.add_argument('-c', '--config', help='Video2X config file location', action='store', default='{}\\video2x.json'.format(os.path.dirname(os.path.abspath(sys.argv[0]))))
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upscaler_options.add_argument('-b', '--batch', help='Enable batch mode (select all default values to questions)', action='store_true')
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# scaling options
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scaling_options = parser.add_argument_group('Scaling Options')
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scaling_options.add_argument('--width', help='Output video width', action='store', type=int)
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scaling_options.add_argument('--height', help='Output video height', action='store', type=int)
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scaling_options.add_argument('-r', '--ratio', help='Scaling ratio', action='store', type=float)
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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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try:
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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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except ValueError:
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pass
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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?', default=True, batch=args.batch):
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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?', default=True, batch=args.batch):
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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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def absolutify_paths(config):
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""" Check to see if paths to binaries are absolute
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This function checks if paths to binary files are absolute.
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If not, then absolutify the path.
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Arguments:
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config {dict} -- configuration file dictionary
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Returns:
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dict -- configuration file dictionary
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"""
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current_folder = os.path.dirname(os.path.abspath(sys.argv[0]))
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# check waifu2x-caffe path
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if not re.match('^[a-z]:', config['waifu2x_caffe']['waifu2x_caffe_path'], re.IGNORECASE):
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config['waifu2x_caffe']['waifu2x_caffe_path'] = '{}\\{}'.format(current_folder, config['waifu2x_caffe']['waifu2x_caffe_path'])
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# check waifu2x-converter-cpp path
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if not re.match('^[a-z]:', config['waifu2x_converter']['waifu2x_converter_path'], re.IGNORECASE):
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config['waifu2x_converter']['waifu2x_converter_path'] = '{}\\{}'.format(current_folder, config['waifu2x_converter']['waifu2x_converter_path'])
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# check ffmpeg path
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if not re.match('^[a-z]:', config['ffmpeg']['ffmpeg_path'], re.IGNORECASE):
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config['ffmpeg']['ffmpeg_path'] = '{}\\{}'.format(current_folder, config['ffmpeg']['ffmpeg_path'])
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# check video2x cache path
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if config['video2x']['video2x_cache_folder']:
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if not re.match('^[a-z]:', config['video2x']['video2x_cache_folder'], re.IGNORECASE):
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config['video2x']['video2x_cache_folder'] = '{}\\{}'.format(current_folder, config['video2x']['video2x_cache_folder'])
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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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config = absolutify_paths(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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if not os.path.isfile(waifu2x_settings['waifu2x_caffe_path']):
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Avalon.error('Specified waifu2x-caffe directory doesn\'t exist')
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Avalon.error('Please check the configuration file settings')
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raise FileNotFoundError(waifu2x_settings['waifu2x_caffe_path'])
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elif args.driver == 'waifu2x_converter':
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waifu2x_settings = config['waifu2x_converter']
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if not os.path.isdir(waifu2x_settings['waifu2x_converter_path']):
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Avalon.error('Specified waifu2x-conver-cpp directory doesn\'t exist')
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Avalon.error('Please check the configuration file settings')
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raise FileNotFoundError(waifu2x_settings['waifu2x_converter_path'])
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# check if waifu2x path is valid
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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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image_format = config['video2x']['image_format'].lower()
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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?', default=True, batch=args.batch):
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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 input specified is a single file
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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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# check for input output format mismatch
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if os.path.isdir(args.output):
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Avalon.error('Input and output path type mismatch')
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Avalon.error('Input is single file but output is folder')
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raise Exception('input output path type mismatch')
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elif not re.search('.*\..*$', args.input):
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Avalon.error('No suffix found in output file path')
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Avalon.error('Suffix must be specified for FFmpeg')
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raise Exception('No suffix specified')
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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)
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# set optional options
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upscaler.waifu2x_driver = args.driver
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upscaler.scale_width = args.width
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upscaler.scale_height = args.height
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upscaler.scale_ratio = args.ratio
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upscaler.model_dir = args.model_dir
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upscaler.threads = args.threads
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upscaler.video2x_cache_folder = video2x_cache_folder
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upscaler.image_format = image_format
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upscaler.preserve_frames = preserve_frames
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# run upscaler-
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upscaler.run()
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upscaler.cleanup()
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# if input specified is a folder
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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)
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# set optional options
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upscaler.waifu2x_driver = args.driver
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upscaler.scale_width = args.width
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upscaler.scale_height = args.height
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upscaler.scale_ratio = args.ratio
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upscaler.model_dir = args.model_dir
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upscaler.threads = args.threads
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upscaler.video2x_cache_folder = video2x_cache_folder
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upscaler.image_format = image_format
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upscaler.preserve_frames = preserve_frames
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# run upscaler
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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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Avalon.warning('If you experience error \"cudaSuccess out of memory\", try reducing number of threads you\'re using')
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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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