2.6.2 removed model verification, enhanced command execution method

This commit is contained in:
k4yt3x 2019-03-19 13:12:12 -04:00
parent 31aa3a630d
commit e6df7a962a

78
bin/video2x.py Executable file → Normal file
View File

@ -13,20 +13,32 @@ __ __ _ _ ___ __ __
Name: Video2X Controller
Author: K4YT3X
Date Created: Feb 24, 2018
Last Modified: March 9, 2019
Last Modified: March 19, 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.
Video2X is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Video2X is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>.
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 MODELS_AVAILABLE
from upscaler import Upscaler
import argparse
import GPUtil
@ -38,9 +50,9 @@ import tempfile
import time
import traceback
VERSION = '2.6.1'
VERSION = '2.6.2'
# Each thread might take up to 2.5 GB during initialization.
# 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
@ -55,25 +67,25 @@ def process_arguments():
"""
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
# Video options
# 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('-i', '--input', help='Specify source video file/directory', action='store', required=True)
basic_options.add_argument('-o', '--output', help='Specify output video file/directory', action='store', 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('-y', '--model_dir', help='Specify model to use', action='store', default=None)
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
# scaling_options = parser.add_argument_group('Scaling Options', required=True)
scaling_options = parser.add_argument_group('Scaling Options')
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
# parse arguments
return parser.parse_args()
@ -96,11 +108,11 @@ def check_memory():
"""
memory_status = []
# Get system available memory
# 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
# 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'):
@ -115,7 +127,7 @@ def check_memory():
except ValueError:
pass
# Go though each checkable memory type and check availability
# go though each checkable memory type and check availability
for memory_type, memory_available in memory_status:
if memory_type == 'system':
@ -123,21 +135,21 @@ def check_memory():
else:
mem_per_thread = GPU_MEM_PER_THREAD
# If user doesn't even have enough memory to run even one 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
# 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
# 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)
@ -157,17 +169,17 @@ def read_config(config_file):
# /////////////////// Execution /////////////////// #
# This is not a library
# 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
# process CLI arguments
args = process_arguments()
# Arguments sanity check
# 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)
@ -178,10 +190,10 @@ 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 available memory
check_memory()
# Read configurations from JSON
# read configurations from JSON
config = read_config(args.config)
# load waifu2x configuration
@ -197,7 +209,7 @@ ffmpeg_settings = config['ffmpeg']
video2x_cache_folder = config['video2x']['video2x_cache_folder']
preserve_frames = config['video2x']['preserve_frames']
# Create temp directories if they don't exist
# create temp directories if they don't exist
if not video2x_cache_folder:
video2x_cache_folder = '{}\\video2x'.format(tempfile.gettempdir())
@ -217,15 +229,15 @@ if video2x_cache_folder and not os.path.isdir(video2x_cache_folder):
exit(1)
# Start execution
# start execution
try:
# Start timer
# 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 = 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_dir=args.model_dir, threads=args.threads, video2x_cache_folder=video2x_cache_folder)
upscaler.run()
upscaler.cleanup()
elif os.path.isdir(args.input):
@ -233,7 +245,7 @@ try:
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 = 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_dir=args.model_dir, threads=args.threads, video2x_cache_folder=video2x_cache_folder)
upscaler.run()
upscaler.cleanup()
else:
@ -245,7 +257,7 @@ except Exception:
Avalon.error('An exception has occurred')
traceback.print_exc()
finally:
# Remove Video2X Cache folder
# remove Video2X Cache folder
try:
if not preserve_frames:
shutil.rmtree(video2x_cache_folder)