mirror of
https://github.com/k4yt3x/video2x.git
synced 2024-12-29 16:09:10 +00:00
251 lines
11 KiB
Python
Executable File
251 lines
11 KiB
Python
Executable File
#!/usr/bin/env python3
|
|
# -*- coding: utf-8 -*-
|
|
"""
|
|
|
|
__ __ _ _ ___ __ __
|
|
\ \ / / (_) | | |__ \ \ \ / /
|
|
\ \ / / _ __| | ___ ___ ) | \ V /
|
|
\ \/ / | | / _` | / _ \ / _ \ / / > <
|
|
\ / | | | (_| | | __/ | (_) | / /_ / . \
|
|
\/ |_| \__,_| \___| \___/ |____| /_/ \_\
|
|
|
|
|
|
Name: Video2X Controller
|
|
Author: K4YT3X
|
|
Date Created: Feb 24, 2018
|
|
Last Modified: March 9, 2019
|
|
|
|
Licensed under the GNU General Public License Version 3 (GNU GPL v3),
|
|
available at: https://www.gnu.org/licenses/gpl-3.0.txt
|
|
|
|
(C) 2018-2019 K4YT3X
|
|
|
|
Description: Video2X is an automation software based on
|
|
waifu2x image enlarging engine. It extracts frames from a
|
|
video, enlarge it by a number of times without losing any
|
|
details or quality, keeping lines smooth and edges sharp.
|
|
"""
|
|
from avalon_framework import Avalon
|
|
from upscaler import Upscaler
|
|
from upscaler import MODELS_AVAILABLE
|
|
import GPUtil
|
|
import argparse
|
|
import json
|
|
import os
|
|
import psutil
|
|
import shutil
|
|
import tempfile
|
|
import time
|
|
import traceback
|
|
|
|
VERSION = '2.6.1'
|
|
|
|
# Each thread might take up to 2.5 GB during initialization.
|
|
# (system memory, not to be confused with GPU memory)
|
|
SYS_MEM_PER_THREAD = 2.5
|
|
GPU_MEM_PER_THREAD = 3.5
|
|
|
|
|
|
def process_arguments():
|
|
"""Processes CLI arguments
|
|
|
|
This function parses all arguments
|
|
This allows users to customize options
|
|
for the output video.
|
|
"""
|
|
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
|
|
|
|
# Video options
|
|
basic_options = parser.add_argument_group('Basic Options')
|
|
basic_options.add_argument('-i', '--input', help='Specify source video file/directory', action='store', default=False, required=True)
|
|
basic_options.add_argument('-o', '--output', help='Specify output video file/directory', action='store', default=False, required=True)
|
|
basic_options.add_argument('-m', '--method', help='Specify upscaling method', action='store', default='gpu', choices=['cpu', 'gpu', 'cudnn'], required=True)
|
|
basic_options.add_argument('-d', '--driver', help='Waifu2x driver', action='store', default='waifu2x_caffe', choices=['waifu2x_caffe', 'waifu2x_converter'])
|
|
basic_options.add_argument('-y', '--model_type', help='Specify model to use', action='store', default='models/cunet', choices=MODELS_AVAILABLE)
|
|
basic_options.add_argument('-t', '--threads', help='Specify number of threads to use for upscaling', action='store', type=int, default=5)
|
|
basic_options.add_argument('-c', '--config', help='Manually specify config file', action='store', default='{}\\video2x.json'.format(os.path.dirname(os.path.abspath(__file__))))
|
|
basic_options.add_argument('-b', '--batch', help='Enable batch mode (select all default values to questions)', action='store_true', default=False)
|
|
|
|
# Scaling options
|
|
# scaling_options = parser.add_argument_group('Scaling Options', required=True) # TODO: (width & height) || (factor)
|
|
scaling_options = parser.add_argument_group('Scaling Options') # TODO: (width & height) || (factor)
|
|
scaling_options.add_argument('--width', help='Output video width', action='store', type=int, default=False)
|
|
scaling_options.add_argument('--height', help='Output video height', action='store', type=int, default=False)
|
|
scaling_options.add_argument('-r', '--ratio', help='Scaling ratio', action='store', type=int, default=False)
|
|
|
|
# Parse arguments
|
|
return parser.parse_args()
|
|
|
|
|
|
def print_logo():
|
|
print('__ __ _ _ ___ __ __')
|
|
print('\\ \\ / / (_) | | |__ \\ \\ \\ / /')
|
|
print(' \\ \\ / / _ __| | ___ ___ ) | \\ V /')
|
|
print(' \\ \\/ / | | / _` | / _ \\ / _ \\ / / > <')
|
|
print(' \\ / | | | (_| | | __/ | (_) | / /_ / . \\')
|
|
print(' \\/ |_| \\__,_| \\___| \\___/ |____| /_/ \\_\\')
|
|
print('\n Video2X Video Enlarger')
|
|
spaces = ((44 - len("Version {}".format(VERSION))) // 2) * " "
|
|
print('{}\n{} Version {}\n{}'.format(Avalon.FM.BD, spaces, VERSION, Avalon.FM.RST))
|
|
|
|
|
|
def check_memory():
|
|
""" Check usable system memory
|
|
Warn the user if insufficient memory is available for
|
|
the number of threads that the user have chosen.
|
|
"""
|
|
|
|
memory_status = []
|
|
# Get system available memory
|
|
system_memory_available = psutil.virtual_memory().available / (1024 ** 3)
|
|
memory_status.append(('system', system_memory_available))
|
|
|
|
# Check if Nvidia-smi is available
|
|
# GPUtil requires nvidia-smi.exe to interact with GPU
|
|
if args.method == 'gpu' or args.method == 'cudnn':
|
|
if not os.path.isfile('C:\\Program Files\\NVIDIA Corporation\\NVSMI\\nvidia-smi.exe'):
|
|
# Nvidia System Management Interface not available
|
|
Avalon.warning('Nvidia-smi not available, skipping available memory check')
|
|
Avalon.warning('If you experience error \"cudaSuccess out of memory\", try reducing number of threads you\'re using')
|
|
else:
|
|
# "0" is GPU ID. Both waifu2x drivers use the first GPU available, therefore only 0 makes sense
|
|
gpu_memory_available = (GPUtil.getGPUs()[0].memoryTotal - GPUtil.getGPUs()[0].memoryUsed) / 1024
|
|
memory_status.append(('GPU', gpu_memory_available))
|
|
|
|
# Go though each checkable memory type and check availability
|
|
for memory_type, memory_available in memory_status:
|
|
|
|
if memory_type == 'system':
|
|
mem_per_thread = SYS_MEM_PER_THREAD
|
|
else:
|
|
mem_per_thread = GPU_MEM_PER_THREAD
|
|
|
|
# If user doesn't even have enough memory to run even one thread
|
|
if memory_available < mem_per_thread:
|
|
Avalon.warning('You might have insufficient amount of {} memory available to run this program ({} GB)'.format(memory_type, memory_available))
|
|
Avalon.warning('Proceed with caution')
|
|
if args.threads > 1:
|
|
if Avalon.ask('Reduce number of threads to avoid crashing?', default=True, batch=args.batch):
|
|
args.threads = 1
|
|
# If memory available is less than needed, warn the user
|
|
elif memory_available < (mem_per_thread * args.threads):
|
|
Avalon.warning('Each waifu2x-caffe thread will require up to 2.5 GB of system memory')
|
|
Avalon.warning('You demanded {} threads to be created, but you only have {} GB {} memory available'.format(args.threads, round(memory_available, 4), memory_type))
|
|
Avalon.warning('{} GB of {} memory is recommended for {} threads'.format(mem_per_thread * args.threads, memory_type, args.threads))
|
|
Avalon.warning('With your current amount of {} memory available, {} threads is recommended'.format(memory_type, int(memory_available // mem_per_thread)))
|
|
|
|
# Ask the user if he / she wants to change to the recommended
|
|
# number of threads
|
|
if Avalon.ask('Change to the recommended value?', default=True, batch=args.batch):
|
|
args.threads = int(memory_available // mem_per_thread)
|
|
else:
|
|
Avalon.warning('Proceed with caution')
|
|
|
|
|
|
def read_config(config_file):
|
|
""" Reads configuration file
|
|
|
|
Returns a dictionary read by JSON.
|
|
"""
|
|
with open(config_file, 'r') as raw_config:
|
|
config = json.load(raw_config)
|
|
return config
|
|
|
|
|
|
# /////////////////// Execution /////////////////// #
|
|
|
|
# This is not a library
|
|
if __name__ != '__main__':
|
|
Avalon.error('This file cannot be imported')
|
|
raise ImportError('{} cannot be imported'.format(__file__))
|
|
|
|
print_logo()
|
|
|
|
# Process CLI arguments
|
|
args = process_arguments()
|
|
|
|
# Arguments sanity check
|
|
if args.driver == 'waifu2x_converter' and args.width and args.height:
|
|
Avalon.error('Waifu2x Converter CPP accepts only scaling ratio')
|
|
exit(1)
|
|
if (args.width or args.height) and args.ratio:
|
|
Avalon.error('You can only specify either scaling ratio or output width and height')
|
|
exit(1)
|
|
if (args.width and not args.height) or (not args.width and args.height):
|
|
Avalon.error('You must specify both width and height')
|
|
exit(1)
|
|
|
|
# Check available memory
|
|
check_memory()
|
|
|
|
# Read configurations from JSON
|
|
config = read_config(args.config)
|
|
|
|
# load waifu2x configuration
|
|
if args.driver == 'waifu2x_caffe':
|
|
waifu2x_settings = config['waifu2x_caffe']
|
|
elif args.driver == 'waifu2x_converter':
|
|
waifu2x_settings = config['waifu2x_converter']
|
|
|
|
# read FFMPEG configuration
|
|
ffmpeg_settings = config['ffmpeg']
|
|
|
|
# load video2x settings
|
|
video2x_cache_folder = config['video2x']['video2x_cache_folder']
|
|
preserve_frames = config['video2x']['preserve_frames']
|
|
|
|
# Create temp directories if they don't exist
|
|
if not video2x_cache_folder:
|
|
video2x_cache_folder = '{}\\video2x'.format(tempfile.gettempdir())
|
|
|
|
if video2x_cache_folder and not os.path.isdir(video2x_cache_folder):
|
|
if not os.path.isfile(video2x_cache_folder) and not os.path.islink(video2x_cache_folder):
|
|
Avalon.warning('Specified cache folder/directory {} does not exist'.format(video2x_cache_folder))
|
|
if Avalon.ask('Create folder/directory?', default=True, batch=args.batch):
|
|
if os.mkdir(video2x_cache_folder) is None:
|
|
Avalon.info('{} created'.format(video2x_cache_folder))
|
|
else:
|
|
Avalon.error('Unable to create {}'.format(video2x_cache_folder))
|
|
Avalon.error('Aborting...')
|
|
exit(1)
|
|
else:
|
|
Avalon.error('Specified cache folder/directory is a file/link')
|
|
Avalon.error('Unable to continue, exiting...')
|
|
exit(1)
|
|
|
|
|
|
# Start execution
|
|
try:
|
|
# Start timer
|
|
begin_time = time.time()
|
|
|
|
if os.path.isfile(args.input):
|
|
""" Upscale single video file """
|
|
Avalon.info('Upscaling single video file: {}'.format(args.input))
|
|
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)
|
|
upscaler.run()
|
|
upscaler.cleanup()
|
|
elif os.path.isdir(args.input):
|
|
""" Upscale videos in a folder/directory """
|
|
Avalon.info('Upscaling videos in folder/directory: {}'.format(args.input))
|
|
for input_video in [f for f in os.listdir(args.input) if os.path.isfile(os.path.join(args.input, f))]:
|
|
output_video = '{}\\{}'.format(args.output, input_video)
|
|
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)
|
|
upscaler.run()
|
|
upscaler.cleanup()
|
|
else:
|
|
Avalon.error('Input path is neither a file nor a folder/directory')
|
|
raise FileNotFoundError('{} is neither file nor folder/directory'.format(args.input))
|
|
|
|
Avalon.info('Program completed, taking {} seconds'.format(round((time.time() - begin_time), 5)))
|
|
except Exception:
|
|
Avalon.error('An exception has occurred')
|
|
traceback.print_exc()
|
|
finally:
|
|
# Remove Video2X Cache folder
|
|
try:
|
|
if not preserve_frames:
|
|
shutil.rmtree(video2x_cache_folder)
|
|
except FileNotFoundError:
|
|
pass
|