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https://github.com/k4yt3x/video2x.git
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352 lines
12 KiB
Python
Executable File
352 lines
12 KiB
Python
Executable File
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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__ __ _ _ ___ __ __
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\ \ / / (_) | | |__ \ \ \ / /
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\ \ / / _ __| | ___ ___ ) | \ V /
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\ \/ / | | / _` | / _ \ / _ \ / / > <
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\ / | | | (_| | | __/ | (_) | / /_ / . \
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\/ |_| \__,_| \___| \___/ |____| /_/ \_\
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Name: Video2x Controller
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Author: K4YT3X
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Date Created: Feb 24, 2018
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Last Modified: November 2, 2018
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Licensed under the GNU General Public License Version 3 (GNU GPL v3),
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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
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waifu2x image enlarging engine. It extracts frames from a
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video, enlarge it by a number of times without losing any
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details or quality, keeping lines smooth and edges sharp.
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"""
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from avalon_framework import Avalon
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from ffmpeg import Ffmpeg
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from fractions import Fraction
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from waifu2x import Waifu2x
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import argparse
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import inspect
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import json
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import os
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import psutil
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import shutil
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import subprocess
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import threading
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import time
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import traceback
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VERSION = '2.1.5'
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EXEC_PATH = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
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FRAMES = '{}\\frames'.format(EXEC_PATH) # Folder containing extracted frames
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UPSCALED = '{}\\upscaled'.format(EXEC_PATH) # Folder containing enlarges frames
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def process_arguments():
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"""Processes CLI arguments
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This function parses all arguments
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This allows users to customize options
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for the output video.
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"""
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parser = argparse.ArgumentParser()
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# Video options
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options_group = parser.add_argument_group('Options')
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options_group.add_argument('--width', help='Output video width', action='store', type=int, default=False)
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options_group.add_argument('--height', help='Output video height', action='store', type=int, default=False)
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options_group.add_argument('-v', '--video', help='Specify source video file', action='store', default=False)
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options_group.add_argument('-o', '--output', help='Specify output file', action='store', default=False)
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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)
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options_group.add_argument('-c', '--config', help='Manually specify config file', action='store', default='video2x.json')
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# Render drivers, at least one option must be specified
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driver_group = parser.add_argument_group('Render Drivers')
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driver_group.add_argument('--cpu', help='Use CPU for enlarging', action='store_true', default=False)
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driver_group.add_argument('--gpu', help='Use GPU for enlarging', action='store_true', default=False)
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driver_group.add_argument('--cudnn', help='Use CUDNN for enlarging', action='store_true', default=False)
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return parser.parse_args()
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def print_logo():
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print('__ __ _ _ ___ __ __')
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print('\\ \\ / / (_) | | |__ \\ \\ \\ / /')
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print(' \\ \\ / / _ __| | ___ ___ ) | \\ V /')
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print(' \\ \\/ / | | / _` | / _ \\ / _ \\ / / > <')
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print(' \\ / | | | (_| | | __/ | (_) | / /_ / . \\')
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print(' \\/ |_| \\__,_| \\___| \\___/ |____| /_/ \\_\\')
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print('\n Video2X Video Enlarger')
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spaces = ((44 - len("Version " + VERSION)) // 2) * " "
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print('{}\n{} Version {}\n{}'.format(Avalon.FM.BD, spaces, VERSION, Avalon.FM.RST))
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def read_config():
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""" Reads configuration file
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Returns a dictionary read by json.
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"""
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with open(args.config, 'r') as raw_config:
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config = json.load(raw_config)
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return config
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def get_video_info():
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"""Gets original video information
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Retrieves original video information using
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ffprobe, then export it into json file.
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Finally it reads, parses the json file and
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returns a dictionary
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Returns:
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dictionary -- original video information
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"""
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json_str = subprocess.check_output(
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'\"{}ffprobe.exe\" -v quiet -print_format json -show_format -show_streams \"{}\"'.format(ffmpeg_path, args.video))
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return json.loads(json_str.decode('utf-8'))
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def check_model_type(args):
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"""
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Check if the model demanded from cli
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argument is legal.
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"""
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models_available = ['upconv_7_anime_style_art_rgb', 'upconv_7_photo',
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'anime_style_art_rgb', 'photo', 'anime_style_art_y']
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if args.model_type not in models_available:
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Avalon.error('Specified model type not found!')
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Avalon.info('Available models:')
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for model in models_available:
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print(model)
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exit(1)
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def upscale_frames(w2):
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""" Upscale video frames with waifu2x-caffe
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This function upscales all the frames extracted
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by ffmpeg using the waifu2x-caffe binary.
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Arguments:
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w2 {Waifu2x Object} -- initialized waifu2x object
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"""
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# Create a container for all upscaler threads
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upscaler_threads = []
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# List all images in the extracted frames
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frames = [os.path.join(FRAMES, f) for f in os.listdir(FRAMES) if os.path.isfile(os.path.join(FRAMES, f))]
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# If we have less images than threads,
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# create only the threads necessary
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if len(frames) < args.threads:
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args.threads = len(frames)
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# Create a folder for each thread and append folder
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# name into a list
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thread_folders = []
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for thread_id in range(args.threads):
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thread_folder = '{}\\{}'.format(FRAMES, str(thread_id))
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# Delete old folders and create new folders
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if os.path.isdir(thread_folder):
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shutil.rmtree(thread_folder)
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os.mkdir(thread_folder)
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# Append folder path into list
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thread_folders.append(thread_folder)
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# Evenly distribute images into each folder
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# until there is none left in the folder
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for image in frames:
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# Move image
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shutil.move(image, thread_folders[0])
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# Rotate list
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thread_folders = thread_folders[-1:] + thread_folders[:-1]
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# Create threads and start them
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for thread_folder in thread_folders:
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# Create thread
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thread = threading.Thread(target=w2.upscale, args=(thread_folder, UPSCALED, args.width, args.height))
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thread.name = str(thread_id)
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# Add threads into the pool
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upscaler_threads.append(thread)
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# Start all threads
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for thread in upscaler_threads:
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thread.start()
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# Wait for threads to finish
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for thread in upscaler_threads:
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thread.join()
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def video2x():
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"""Main controller for Video2X
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This function controls the flow of video conversion
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and handles all necessary functions.
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"""
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check_model_type(args)
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# Parse arguments for waifu2x
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if args.cpu:
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method = 'cpu'
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elif args.gpu:
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method = 'gpu'
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ffmpeg_arguments.append('-hwaccel {}'.format(ffmpeg_hwaccel))
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elif args.cudnn:
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method = 'cudnn'
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ffmpeg_arguments.append('-hwaccel {}'.format(ffmpeg_hwaccel))
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# Initialize objects for ffmpeg and waifu2x-caffe
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fm = Ffmpeg(ffmpeg_path, args.output, ffmpeg_arguments)
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w2 = Waifu2x(waifu2x_path, method, args.model_type)
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# Clear and create directories
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if os.path.isdir(FRAMES):
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shutil.rmtree(FRAMES)
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if os.path.isdir(UPSCALED):
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shutil.rmtree(UPSCALED)
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os.mkdir(FRAMES)
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os.mkdir(UPSCALED)
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# Extract frames from video
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fm.extract_frames(args.video, FRAMES)
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Avalon.info('Reading video information')
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info = get_video_info()
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# Analyze original video with ffprobe and retrieve framerate
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# width, height = info['streams'][0]['width'], info['streams'][0]['height']
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# Find index of video stream
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video_stream_index = None
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for stream in info['streams']:
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if stream['codec_type'] == 'video':
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video_stream_index = stream['index']
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break
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# Exit if no video stream found
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if video_stream_index is None:
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Avalon.error('Aborting: No video stream found')
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# Get average frame rate of video stream
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framerate = float(Fraction(info['streams'][video_stream_index]['avg_frame_rate']))
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Avalon.info('Framerate: {}'.format(framerate))
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# Upscale images one by one using waifu2x
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Avalon.info('Starting to upscale extracted images')
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upscale_frames(w2)
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Avalon.info('Upscaling completed')
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# Frames to Video
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Avalon.info('Converting extracted frames into video')
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fm.convert_video(framerate, '{}x{}'.format(args.width, args.height), UPSCALED)
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Avalon.info('Conversion completed')
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# Extract and press audio in
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Avalon.info('Stripping audio track from original video')
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fm.extract_audio(args.video, UPSCALED)
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Avalon.info('Inserting audio track into new video')
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fm.insert_audio_track(UPSCALED)
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# /////////////////// Execution /////////////////// #
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# This is not a library
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if __name__ != '__main__':
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Avalon.error('This file cannot be imported')
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exit(1)
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# Process cli arguments
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args = process_arguments()
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# Print video2x banner
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print_logo()
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# Check if arguments are valid / all necessary argument
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# values are specified
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if not args.video:
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Avalon.error('You need to specify the video to process')
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exit(1)
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elif not args.width or not args.height:
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Avalon.error('You must specify output video width and height')
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exit(1)
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elif not args.output:
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Avalon.error('You need to specify the output video name')
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exit(1)
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elif not args.cpu and not args.gpu and not args.cudnn:
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Avalon.error('You need to specify the enlarging processing unit')
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exit(1)
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# Convert paths to absolute paths
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args.video = os.path.abspath(args.video)
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args.output = os.path.abspath(args.output)
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# Read configurations from config file
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config = read_config()
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waifu2x_path = config['waifu2x_path']
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ffmpeg_path = config['ffmpeg_path']
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ffmpeg_arguments = config['ffmpeg_arguments']
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ffmpeg_hwaccel = config['ffmpeg_hwaccel']
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# Add a forward slash to directory if not present
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# otherwise there will be a format error
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if ffmpeg_path[-1] != '/' and ffmpeg_path[-1] != '\\':
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ffmpeg_path = '{}/'.format(ffmpeg_path)
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# Check if FFMPEG and waifu2x are present
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if not os.path.isdir(ffmpeg_path):
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Avalon.error('FFMPEG binaries not found')
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Avalon.error('Please specify FFMPEG binaries location in config file')
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Avalon.error('Current value: {}'.format(ffmpeg_path))
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raise FileNotFoundError(ffmpeg_path)
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if not os.path.isfile(waifu2x_path):
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Avalon.error('Waifu2x CUI executable not found')
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Avalon.error('Please specify Waifu2x CUI location in config file')
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Avalon.error('Current value: {}'.format(waifu2x_path))
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raise FileNotFoundError(waifu2x_path)
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# Check usable memory
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# Warn the user if insufficient memory is available for
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# the number of threads that the user have chosen. Each
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# thread might take up to 2.5 GB during initialization.
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MEM_PER_THREAD = 2.5
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memory_available = psutil.virtual_memory().available / (1024 ** 3)
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# If user doesn't even have enough memory to run even one thread
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if memory_available < MEM_PER_THREAD:
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Avalon.warning('You might have an insufficient amount of memory available to run this program ({} GB)'.format(memory_available))
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Avalon.warning('Proceed with caution')
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# If memory available is less than needed, warn the user
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elif memory_available < (MEM_PER_THREAD * args.threads):
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Avalon.warning('Each waifu2x-caffe thread will require up to 2.5 GB during initialization')
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Avalon.warning('You demanded {} threads to be created, but you only have {} GB memory available'.format(args.threads, round(memory_available, 4)))
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Avalon.warning('{} GB of memory is recommended for {} threads'.format(MEM_PER_THREAD * args.threads, args.threads))
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Avalon.warning('With your current amount of memory available, {} threads is recommended'.format(int(memory_available // MEM_PER_THREAD)))
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# Ask the user if he / she wants to change to the recommended
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# number of threads
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if Avalon.ask('Change to the recommended value?', True):
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args.threads = int(memory_available // MEM_PER_THREAD)
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else:
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Avalon.warning('Proceed with caution')
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# Start execution
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try:
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begin_time = time.time()
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video2x()
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Avalon.info('Program completed, taking {} seconds'.format(round((time.time() - begin_time), 5)))
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except Exception:
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Avalon.error('An exception occurred')
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traceback.print_exc()
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