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2.4.2 added gpu memory check, auto create temp folders

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K4YT3X 2019-02-26 18:04:51 -05:00
parent f00617a409
commit 60d97907df
1 changed files with 69 additions and 26 deletions
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95
bin/video2x.py
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@ -13,7 +13,7 @@ __ __ _ _ ___ __ __
Name: Video2X Controller
Author: K4YT3X
Date Created: Feb 24, 2018
Last Modified: February 8, 2019
Last Modified: February 26, 2019
Licensed under the GNU General Public License Version 3 (GNU GPL v3),
available at: https://www.gnu.org/licenses/gpl-3.0.txt
@ -29,17 +29,19 @@ from avalon_framework import Avalon
from upscaler import Upscaler
from upscaler import MODELS_AVAILABLE
import argparse
import GPUtil
import json
import os
import psutil
import time
import traceback
VERSION = '2.4.1'
VERSION = '2.4.2'
# Each thread might take up to 2.5 GB during initialization.
# (system memory, not to be confused with GPU memory)
MEM_PER_THREAD = 2.5
SYS_MEM_PER_THREAD = 2.5
GPU_MEM_PER_THREAD = 3.5
def process_arguments():
@ -59,7 +61,7 @@ def process_arguments():
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='anime_style_art_rgb', 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')
basic_options.add_argument('-c', '--config', help='Manually specify config file', action='store', default='{}\\video2x.json'.format(os.path.dirname(os.path.abspath(__file__))))
# Scaling options
# scaling_options = parser.add_argument_group('Scaling Options', required=True) # TODO: (width & height) || (factor)
@ -84,33 +86,57 @@ def print_logo():
print('{}\n{} Version {}\n{}'.format(Avalon.FM.BD, spaces, VERSION, Avalon.FM.RST))
def check_system_memory():
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_available = psutil.virtual_memory().available / (1024 ** 3)
# If user doesn't even have enough memory to run even one thread
if memory_available < MEM_PER_THREAD:
Avalon.warning('You might have an insufficient amount of memory available to run this program ({} GB)'.format(memory_available))
Avalon.warning('Proceed with caution')
if args.threads > 1:
if Avalon.ask('Reduce number of threads to avoid crashing?', True):
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 during initialization')
Avalon.warning('You demanded {} threads to be created, but you only have {} GB memory available'.format(args.threads, round(memory_available, 4)))
Avalon.warning('{} GB of memory is recommended for {} threads'.format(MEM_PER_THREAD * args.threads, args.threads))
Avalon.warning('With your current amount of memory available, {} threads is recommended'.format(int(memory_available // MEM_PER_THREAD)))
memory_status = []
# Get system available memory
system_memory_available = psutil.virtual_memory().available / (1024 ** 3)
memory_status.append(('system', system_memory_available))
# Ask the user if he / she wants to change to the recommended
# number of threads
if Avalon.ask('Change to the recommended value?', True):
args.threads = int(memory_available // MEM_PER_THREAD)
# 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?', True):
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?', True):
args.threads = int(memory_available // mem_per_thread)
else:
Avalon.warning('Proceed with caution')
def read_config(config_file):
@ -146,8 +172,8 @@ 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 system available memory
check_system_memory()
# Check available memory
check_memory()
# Read configurations from JSON
config = read_config(args.config)
@ -159,6 +185,23 @@ extracted_frames = config['extracted_frames']
upscaled_frames = config['upscaled_frames']
preserve_frames = config['preserve_frames']
# Create temp directories if they don't exist
for directory in [extracted_frames, upscaled_frames]:
if directory and not os.path.isdir(directory):
if not os.path.isfile(directory) and not os.path.islink(directory):
Avalon.warning('Specified temporary folder/directory {} does not exist'.format(directory))
if Avalon.ask('Create folder/directory?'):
if os.mkdir(directory) == 0:
Avalon.info('{} created'.format(directory))
else:
Avalon.error('Unable to create {}'.format(directory))
Avalon.error('Aborting...')
exit(1)
else:
Avalon.error('Specified temporary folder/directory is a file/link')
Avalon.error('Unable to continue, exiting...')
exit(1)
# Start execution
try:
@ -172,7 +215,7 @@ try:
upscaler.run()
elif os.path.isdir(args.input):
""" Upscale videos in a folder/directory """
Avalon.info('Upscaling videos in folder: {}'.format(args.input))
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_path=waifu2x_path, ffmpeg_path=ffmpeg_path, waifu2x_driver=args.driver, ffmpeg_arguments=ffmpeg_arguments, ffmpeg_hwaccel=ffmpeg_hwaccel, output_width=args.width, output_height=args.height, ratio=args.ratio, model_type=args.model_type, threads=args.threads, extracted_frames=extracted_frames, upscaled_frames=upscaled_frames)