mirror of
https://github.com/k4yt3x/video2x.git
synced 2025-11-03 22:21:37 +01:00
310 lines
12 KiB
Python
310 lines
12 KiB
Python
#!/usr/bin/env python3
|
|
# -*- coding: utf-8 -*-
|
|
"""
|
|
Name: Video2X Upscaler
|
|
Author: K4YT3X
|
|
Date Created: December 10, 2018
|
|
Last Modified: June 13, 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
|
|
"""
|
|
|
|
from avalon_framework import Avalon
|
|
from exceptions import *
|
|
from ffmpeg import Ffmpeg
|
|
from fractions import Fraction
|
|
from image_cleaner import ImageCleaner
|
|
from tqdm import tqdm
|
|
from waifu2x_caffe import Waifu2xCaffe
|
|
from waifu2x_converter import Waifu2xConverter
|
|
import copy
|
|
import os
|
|
import re
|
|
import shutil
|
|
import tempfile
|
|
import threading
|
|
import time
|
|
|
|
|
|
class Upscaler:
|
|
""" An instance of this class is a upscaler that will
|
|
upscale all images in the given directory.
|
|
|
|
Raises:
|
|
Exception -- all exceptions
|
|
ArgumentError -- if argument is not valid
|
|
"""
|
|
|
|
def __init__(self, input_video, output_video, method, waifu2x_settings, ffmpeg_settings):
|
|
# mandatory arguments
|
|
self.input_video = input_video
|
|
self.output_video = output_video
|
|
self.method = method
|
|
self.waifu2x_settings = waifu2x_settings
|
|
self.ffmpeg_settings = ffmpeg_settings
|
|
|
|
# optional arguments
|
|
self.waifu2x_driver = 'waifu2x_caffe'
|
|
self.scale_width = None
|
|
self.scale_height = None
|
|
self.scale_ratio = None
|
|
self.model_dir = None
|
|
self.threads = 5
|
|
self.video2x_cache_directory = f'{tempfile.gettempdir()}\\video2x'
|
|
self.image_format = 'png'
|
|
self.preserve_frames = False
|
|
|
|
def create_temp_directories(self):
|
|
"""create temporary directory
|
|
"""
|
|
self.extracted_frames = tempfile.mkdtemp(dir=self.video2x_cache_directory)
|
|
Avalon.debug_info(f'Extracted frames are being saved to: {self.extracted_frames}')
|
|
self.upscaled_frames = tempfile.mkdtemp(dir=self.video2x_cache_directory)
|
|
Avalon.debug_info(f'Upscaled frames are being saved to: {self.upscaled_frames}')
|
|
|
|
def cleanup_temp_directories(self):
|
|
"""delete temp directories when done
|
|
"""
|
|
if not self.preserve_frames:
|
|
for directory in [self.extracted_frames, self.upscaled_frames]:
|
|
try:
|
|
# avalon framework cannot be used if python is shutting down
|
|
# therefore, plain print is used
|
|
print(f'Cleaning up cache directory: {directory}')
|
|
shutil.rmtree(directory)
|
|
except (OSError, FileNotFoundError):
|
|
pass
|
|
|
|
def _check_arguments(self):
|
|
# check if arguments are valid / all necessary argument
|
|
# values are specified
|
|
if not self.input_video:
|
|
raise ArgumentError('You need to specify the video to process')
|
|
elif (not self.scale_width or not self.scale_height) and not self.scale_ratio:
|
|
raise ArgumentError('You must specify output video width and height or upscale factor')
|
|
elif not self.output_video:
|
|
raise ArgumentError('You need to specify the output video name')
|
|
elif not self.method:
|
|
raise ArgumentError('You need to specify the enlarging processing unit')
|
|
|
|
def _progress_bar(self, extracted_frames_directories):
|
|
""" This method prints a progress bar
|
|
|
|
This method prints a progress bar by keeping track
|
|
of the amount of frames in the input directory
|
|
and the output directory. This is originally
|
|
suggested by @ArmandBernard.
|
|
"""
|
|
# get number of extracted frames
|
|
total_frames = 0
|
|
for directory in extracted_frames_directories:
|
|
total_frames += len([f for f in os.listdir(directory) if f[-4:] == f'.{self.image_format}'])
|
|
|
|
with tqdm(total=total_frames, ascii=True, desc='Upscaling Progress') as progress_bar:
|
|
|
|
# tqdm update method adds the value to the progress
|
|
# bar instead of setting the value. Therefore, a delta
|
|
# needs to be calculated.
|
|
previous_cycle_frames = 0
|
|
while not self.progress_bar_exit_signal:
|
|
|
|
try:
|
|
total_frames_upscaled = len([f for f in os.listdir(self.upscaled_frames) if f[-4:] == f'.{self.image_format}'])
|
|
delta = total_frames_upscaled - previous_cycle_frames
|
|
previous_cycle_frames = total_frames_upscaled
|
|
|
|
# if upscaling is finished
|
|
if total_frames_upscaled >= total_frames:
|
|
return
|
|
|
|
# adds the detla into the progress bar
|
|
progress_bar.update(delta)
|
|
except FileNotFoundError:
|
|
pass
|
|
|
|
time.sleep(1)
|
|
|
|
def _upscale_frames(self):
|
|
""" Upscale video frames with waifu2x-caffe
|
|
|
|
This function upscales all the frames extracted
|
|
by ffmpeg using the waifu2x-caffe binary.
|
|
|
|
Arguments:
|
|
w2 {Waifu2x Object} -- initialized waifu2x object
|
|
"""
|
|
|
|
# progress bar thread exit signal
|
|
self.progress_bar_exit_signal = False
|
|
|
|
# create a container for exceptions in threads
|
|
# if this thread is not empty, then an exception has occured
|
|
self.upscaler_exceptions = []
|
|
|
|
# initialize waifu2x driver
|
|
if self.waifu2x_driver != 'waifu2x_caffe' and self.waifu2x_driver != 'waifu2x_converter':
|
|
raise Exception(f'Unrecognized waifu2x driver: {self.waifu2x_driver}')
|
|
|
|
# it's easier to do multi-threading with waifu2x_converter
|
|
# the number of threads can be passed directly to waifu2x_converter
|
|
if self.waifu2x_driver == 'waifu2x_converter':
|
|
w2 = Waifu2xConverter(self.waifu2x_settings, self.model_dir)
|
|
|
|
progress_bar = threading.Thread(target=self._progress_bar, args=([self.extracted_frames],))
|
|
progress_bar.start()
|
|
|
|
w2.upscale(self.extracted_frames, self.upscaled_frames, self.scale_ratio, self.threads, self.image_format, self.upscaler_exceptions)
|
|
for image in [f for f in os.listdir(self.upscaled_frames) if os.path.isfile(os.path.join(self.upscaled_frames, f))]:
|
|
renamed = re.sub(f'_\[.*-.*\]\[x(\d+(\.\d+)?)\]\.{self.image_format}', f'.{self.image_format}', image)
|
|
shutil.move(f'{self.upscaled_frames}\\{image}', f'{self.upscaled_frames}\\{renamed}')
|
|
|
|
self.progress_bar_exit_signal = True
|
|
progress_bar.join()
|
|
return
|
|
|
|
# create a container for all upscaler threads
|
|
upscaler_threads = []
|
|
|
|
# list all images in the extracted frames
|
|
frames = [os.path.join(self.extracted_frames, f) for f in os.listdir(self.extracted_frames) if os.path.isfile(os.path.join(self.extracted_frames, f))]
|
|
|
|
# if we have less images than threads,
|
|
# create only the threads necessary
|
|
if len(frames) < self.threads:
|
|
self.threads = len(frames)
|
|
|
|
# create a directory for each thread and append directory
|
|
# name into a list
|
|
|
|
thread_pool = []
|
|
thread_directories = []
|
|
for thread_id in range(self.threads):
|
|
thread_directory = f'{self.extracted_frames}\\{str(thread_id)}'
|
|
thread_directories.append(thread_directory)
|
|
|
|
# delete old directories and create new directories
|
|
if os.path.isdir(thread_directory):
|
|
shutil.rmtree(thread_directory)
|
|
os.mkdir(thread_directory)
|
|
|
|
# append directory path into list
|
|
thread_pool.append((thread_directory, thread_id))
|
|
|
|
# evenly distribute images into each directory
|
|
# until there is none left in the directory
|
|
for image in frames:
|
|
# move image
|
|
shutil.move(image, thread_pool[0][0])
|
|
# rotate list
|
|
thread_pool = thread_pool[-1:] + thread_pool[:-1]
|
|
|
|
# create threads and start them
|
|
for thread_info in thread_pool:
|
|
|
|
# create a separate w2 instance for each thread
|
|
w2 = Waifu2xCaffe(copy.deepcopy(self.waifu2x_settings), self.method, self.model_dir)
|
|
|
|
# create thread
|
|
if self.scale_ratio:
|
|
thread = threading.Thread(target=w2.upscale, args=(thread_info[0], self.upscaled_frames, self.scale_ratio, False, False, self.image_format, self.upscaler_exceptions))
|
|
else:
|
|
thread = threading.Thread(target=w2.upscale, args=(thread_info[0], self.upscaled_frames, False, self.scale_width, self.scale_height, self.image_format, self.upscaler_exceptions))
|
|
thread.name = thread_info[1]
|
|
|
|
# add threads into the pool
|
|
upscaler_threads.append(thread)
|
|
|
|
# start progress bar in a different thread
|
|
progress_bar = threading.Thread(target=self._progress_bar, args=(thread_directories,))
|
|
progress_bar.start()
|
|
|
|
# create the clearer and start it
|
|
Avalon.debug_info('Starting upscaled image cleaner')
|
|
image_cleaner = ImageCleaner(self.extracted_frames, self.upscaled_frames, len(upscaler_threads))
|
|
image_cleaner.start()
|
|
|
|
# start all threads
|
|
for thread in upscaler_threads:
|
|
thread.start()
|
|
|
|
# wait for threads to finish
|
|
for thread in upscaler_threads:
|
|
thread.join()
|
|
|
|
# upscaling done, kill the clearer
|
|
Avalon.debug_info('Killing upscaled image cleaner')
|
|
image_cleaner.stop()
|
|
|
|
self.progress_bar_exit_signal = True
|
|
|
|
if len(self.upscaler_exceptions) != 0:
|
|
raise(self.upscaler_exceptions[0])
|
|
|
|
def run(self):
|
|
"""Main controller for Video2X
|
|
|
|
This function controls the flow of video conversion
|
|
and handles all necessary functions.
|
|
"""
|
|
|
|
# parse arguments for waifu2x
|
|
# check argument sanity
|
|
self._check_arguments()
|
|
|
|
# convert paths to absolute paths
|
|
self.input_video = os.path.abspath(self.input_video)
|
|
self.output_video = os.path.abspath(self.output_video)
|
|
|
|
# initialize objects for ffmpeg and waifu2x-caffe
|
|
fm = Ffmpeg(self.ffmpeg_settings, self.image_format)
|
|
|
|
# extract frames from video
|
|
fm.extract_frames(self.input_video, self.extracted_frames)
|
|
|
|
Avalon.info('Reading video information')
|
|
video_info = fm.get_video_info(self.input_video)
|
|
# 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 video_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')
|
|
exit(1)
|
|
|
|
# get average frame rate of video stream
|
|
framerate = float(Fraction(video_info['streams'][video_stream_index]['avg_frame_rate']))
|
|
Avalon.info(f'Framerate: {framerate}')
|
|
|
|
# width/height will be coded width/height x upscale factor
|
|
if self.scale_ratio:
|
|
original_width = video_info['streams'][video_stream_index]['width']
|
|
original_height = video_info['streams'][video_stream_index]['height']
|
|
self.scale_width = int(self.scale_ratio * original_width)
|
|
self.scale_height = int(self.scale_ratio * original_height)
|
|
|
|
# upscale images one by one using waifu2x
|
|
Avalon.info('Starting to upscale extracted images')
|
|
self._upscale_frames()
|
|
Avalon.info('Upscaling completed')
|
|
|
|
# frames to Video
|
|
Avalon.info('Converting extracted frames into video')
|
|
|
|
# use user defined output size
|
|
fm.convert_video(framerate, f'{self.scale_width}x{self.scale_height}', self.upscaled_frames)
|
|
Avalon.info('Conversion completed')
|
|
|
|
# migrate audio tracks and subtitles
|
|
Avalon.info('Migrating audio tracks and subtitles to upscaled video')
|
|
fm.migrate_audio_tracks_subtitles(self.input_video, self.output_video, self.upscaled_frames)
|