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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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bin/video2x.py
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@ -13,7 +13,7 @@ __ __ _ _ ___ __ __
Name: Video2X Controller Name: Video2X Controller
Author: K4YT3X Author: K4YT3X
Date Created: Feb 24, 2018 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), Licensed under the GNU General Public License Version 3 (GNU GPL v3),
available at: https://www.gnu.org/licenses/gpl-3.0.txt 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 Upscaler
from upscaler import MODELS_AVAILABLE from upscaler import MODELS_AVAILABLE
import argparse import argparse
import GPUtil
import json import json
import os import os
import psutil import psutil
import time import time
import traceback import traceback
VERSION = '2.4.1' VERSION = '2.4.2'
# 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) # (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(): 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('-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('-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('-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
# scaling_options = parser.add_argument_group('Scaling Options', required=True) # TODO: (width & height) || (factor) # 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)) print('{}\n{} Version {}\n{}'.format(Avalon.FM.BD, spaces, VERSION, Avalon.FM.RST))
def check_system_memory(): def check_memory():
""" Check usable system memory """ Check usable system memory
Warn the user if insufficient memory is available for Warn the user if insufficient memory is available for
the number of threads that the user have chosen. 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 memory_status = []
if memory_available < MEM_PER_THREAD: # Get system available memory
Avalon.warning('You might have an insufficient amount of memory available to run this program ({} GB)'.format(memory_available)) system_memory_available = psutil.virtual_memory().available / (1024 ** 3)
Avalon.warning('Proceed with caution') memory_status.append(('system', system_memory_available))
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)))
# Ask the user if he / she wants to change to the recommended # Check if Nvidia-smi is available
# number of threads # GPUtil requires nvidia-smi.exe to interact with GPU
if Avalon.ask('Change to the recommended value?', True): if args.method == 'gpu' or args.method == 'cudnn':
args.threads = int(memory_available // MEM_PER_THREAD) 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: 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') 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): 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') Avalon.error('You must specify both width and height')
exit(1) exit(1)
# Check system available memory # Check available memory
check_system_memory() check_memory()
# Read configurations from JSON # Read configurations from JSON
config = read_config(args.config) config = read_config(args.config)
@ -159,6 +185,23 @@ extracted_frames = config['extracted_frames']
upscaled_frames = config['upscaled_frames'] upscaled_frames = config['upscaled_frames']
preserve_frames = config['preserve_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 # Start execution
try: try:
@ -172,7 +215,7 @@ try:
upscaler.run() upscaler.run()
elif os.path.isdir(args.input): elif os.path.isdir(args.input):
""" Upscale videos in a folder/directory """ """ 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))]: 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) 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) 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)