video2x/video2x.py

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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
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__ __ _ _ ___ __ __
\ \ / / (_) | | |__ \ \ \ / /
\ \ / / _ __| | ___ ___ ) | \ V /
\ \/ / | | / _` | / _ \ / _ \ / / > <
\ / | | | (_| | | __/ | (_) | / /_ / . \
\/ |_| \__,_| \___| \___/ |____| /_/ \_\
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Name: Video2x Controller
Author: K4YT3X
Date Created: Feb 24, 2018
Last Modified: October 23, 2018
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Licensed under the GNU General Public License Version 3 (GNU GPL v3),
available at: https://www.gnu.org/licenses/gpl-3.0.txt
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(C) 2018 K4YT3X
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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.
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"""
from avalon_framework import Avalon
from ffmpeg import Ffmpeg
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from fractions import Fraction
from waifu2x import Waifu2x
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import argparse
import inspect
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import json
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import os
import psutil
import shutil
import subprocess
import threading
import time
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import traceback
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VERSION = '2.1.3'
EXEC_PATH = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
FRAMES = '{}\\frames'.format(EXEC_PATH) # Folder containing extracted frames
UPSCALED = '{}\\upscaled'.format(EXEC_PATH) # Folder containing enlarges frames
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def process_arguments():
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"""Processes CLI arguments
This function parses all arguments
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This allows users to customize options
for the output video.
"""
parser = argparse.ArgumentParser()
# Video options
options_group = parser.add_argument_group('Options')
options_group.add_argument('--width', help='Output video width', action='store', type=int, default=False)
options_group.add_argument('--height', help='Output video height', action='store', type=int, default=False)
options_group.add_argument('-v', '--video', help='Specify source video file', action='store', default=False)
options_group.add_argument('-o', '--output', help='Specify output file', action='store', default=False)
options_group.add_argument('-y', '--model_type', help='Specify model to use', action='store', default='anime_style_art_rgb')
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options_group.add_argument('-t', '--threads', help='Specify number of threads to use for upscaling', action='store', type=int, default=5)
options_group.add_argument('-c', '--config', help='Manually specify config file', action='store', default='video2x.json')
# Render drivers, at least one option must be specified
driver_group = parser.add_argument_group('Render Drivers')
driver_group.add_argument('--cpu', help='Use CPU for enlarging', action='store_true', default=False)
driver_group.add_argument('--gpu', help='Use GPU for enlarging', action='store_true', default=False)
driver_group.add_argument('--cudnn', help='Use CUDNN for enlarging', action='store_true', default=False)
return parser.parse_args()
def print_logo():
print('__ __ _ _ ___ __ __')
print('\\ \\ / / (_) | | |__ \\ \\ \\ / /')
print(' \\ \\ / / _ __| | ___ ___ ) | \\ V /')
print(' \\ \\/ / | | / _` | / _ \\ / _ \\ / / > <')
print(' \\ / | | | (_| | | __/ | (_) | / /_ / . \\')
print(' \\/ |_| \\__,_| \\___| \\___/ |____| /_/ \\_\\')
print('\n Video2X Video Enlarger')
spaces = ((44 - len("Version " + VERSION)) // 2) * " "
print('{}\n{} Version {}\n{}'.format(Avalon.FM.BD, spaces, VERSION, Avalon.FM.RST))
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def read_config():
""" Reads configuration file
Returns a dictionary read by json.
"""
with open(args.config, 'r') as raw_config:
config = json.load(raw_config)
return config
def get_video_info():
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"""Gets original video information
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Retrieves original video information using
ffprobe, then export it into json file.
Finally it reads, parses the json file and
returns a dictionary
Returns:
dictionary -- original video information
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"""
json_str = subprocess.check_output(
'\"{}ffprobe.exe\" -v quiet -print_format json -show_format -show_streams \"{}\"'.format(ffmpeg_path, args.video))
return json.loads(json_str.decode('utf-8'))
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def check_model_type(args):
"""
Check if the model demanded from cli
argument is legal.
"""
models_available = ['upconv_7_anime_style_art_rgb', 'upconv_7_photo',
'anime_style_art_rgb', 'photo', 'anime_style_art_y']
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if args.model_type not in models_available:
Avalon.error('Specified model type not found!')
Avalon.info('Available models:')
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for model in models_available:
print(model)
exit(1)
def upscale_frames(w2):
""" Upscale video frames with waifu2x-caffe
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This function upscales all the frames extracted
by ffmpeg using the waifu2x-caffe binary.
Arguments:
w2 {Waifu2x Object} -- initialized waifu2x object
"""
# Create a container for all upscaler threads
upscaler_threads = []
# List all images in the extracted frames
frames = [os.path.join(FRAMES, f) for f in os.listdir(FRAMES) if os.path.isfile(os.path.join(FRAMES, f))]
# If we have less images than threads,
# create only the threads necessary
if len(frames) < args.threads:
args.threads = len(frames)
# Move an equal amount of images into separate
# folders for each thread
images_per_thread = len(frames) // args.threads
for thread_id in range(args.threads):
thread_folder = '{}\\{}'.format(FRAMES, str(thread_id))
# Delete old folders and create new folders
if os.path.isdir(thread_folder):
shutil.rmtree(thread_folder)
os.mkdir(thread_folder)
# Begin moving images into corresponding folders
for _ in range(images_per_thread):
try:
shutil.move(frames.pop(0), thread_folder)
except IndexError:
pass
# Create thread
thread = threading.Thread(target=w2.upscale, args=(thread_folder, UPSCALED, args.width, args.height))
thread.name = str(thread_id)
# Add threads into the pool
upscaler_threads.append(thread)
# Start all threads
for thread in upscaler_threads:
thread.start()
# Wait for threads to finish
for thread in upscaler_threads:
thread.join()
def video2x():
"""Main controller for Video2X
This function controls the flow of video conversion
and handles all necessary functions.
"""
check_model_type(args)
# Parse arguments for waifu2x
if args.cpu:
method = 'cpu'
elif args.gpu:
method = 'gpu'
elif args.cudnn:
method = 'cudnn'
# Initialize objects for ffmpeg and waifu2x-caffe
fm = Ffmpeg(ffmpeg_path, args.output, ffmpeg_arguments)
w2 = Waifu2x(waifu2x_path, method, args.model_type)
# Clear and create directories
if os.path.isdir(FRAMES):
shutil.rmtree(FRAMES)
if os.path.isdir(UPSCALED):
shutil.rmtree(UPSCALED)
os.mkdir(FRAMES)
os.mkdir(UPSCALED)
# Extract frames from video
fm.extract_frames(args.video, FRAMES)
Avalon.info('Reading video information')
info = get_video_info()
# Analyze original video with ffprobe and retrieve framerate
# width, height = info['streams'][0]['width'], info['streams'][0]['height']
# Find index of video stream
video_stream_index = None
for stream in info['streams']:
if stream['codec_type'] == 'video':
video_stream_index = stream['index']
break
# Exit if no video stream found
if video_stream_index is None:
Avalon.error('Aborting: No video stream found')
# Get average frame rate of video stream
framerate = float(Fraction(info['streams'][video_stream_index]['avg_frame_rate']))
Avalon.info('Framerate: {}'.format(framerate))
# Upscale images one by one using waifu2x
Avalon.info('Starting to upscale extracted images')
upscale_frames(w2)
Avalon.info('Upscaling completed')
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# Frames to Video
Avalon.info('Converting extracted frames into video')
fm.convert_video(framerate, '{}x{}'.format(args.width, args.height), UPSCALED)
Avalon.info('Conversion completed')
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# Extract and press audio in
Avalon.info('Stripping audio track from original video')
fm.extract_audio(args.video, UPSCALED)
Avalon.info('Inserting audio track into new video')
fm.insert_audio_track(UPSCALED)
# /////////////////// Execution /////////////////// #
# This is not a library
if __name__ != '__main__':
Avalon.error('This file cannot be imported')
exit(1)
# Process cli arguments
args = process_arguments()
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# Print video2x banner
print_logo()
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# Check if arguments are valid / all necessary argument
# values are specified
if not args.video:
Avalon.error('You need to specify the video to process')
exit(1)
elif not args.width or not args.height:
Avalon.error('You must specify output video width and height')
exit(1)
elif not args.output:
Avalon.error('You need to specify the output video name')
exit(1)
elif not args.cpu and not args.gpu and not args.cudnn:
Avalon.error('You need to specify the enlarging processing unit')
exit(1)
# Convert paths to absolute paths
args.video = os.path.abspath(args.video)
args.output = os.path.abspath(args.output)
# Read configurations from config file
config = read_config()
waifu2x_path = config['waifu2x_path']
ffmpeg_path = config['ffmpeg_path']
ffmpeg_arguments = config['ffmpeg_arguments']
# Add a forward slash to directory if not present
# otherwise there will be a format error
if ffmpeg_path[-1] != '/' and ffmpeg_path[-1] != '\\':
ffmpeg_path = '{}/'.format(ffmpeg_path)
# Check if FFMPEG and waifu2x are present
if not os.path.isdir(ffmpeg_path):
Avalon.error('FFMPEG binaries not found')
Avalon.error('Please specify FFMPEG binaries location in config file')
Avalon.error('Current value: {}'.format(ffmpeg_path))
raise FileNotFoundError(ffmpeg_path)
if not os.path.isfile(waifu2x_path):
Avalon.error('Waifu2x CUI executable not found')
Avalon.error('Please specify Waifu2x CUI location in config file')
Avalon.error('Current value: {}'.format(waifu2x_path))
raise FileNotFoundError(waifu2x_path)
# Check usable memory
# Warn the user if insufficient memory is available for
# the number of threads that the user have chosen. Each
# thread might take up to 2.5 GB during initialization.
MEM_PER_THREAD = 2.5
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 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
# 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')
# Start execution
try:
begin_time = time.time()
video2x()
Avalon.info('Program completed, taking {} seconds'.format(round((time.time() - begin_time), 5)))
except Exception:
Avalon.error('An exception occurred')
traceback.print_exc()