Removed a feck ton
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@@ -1,17 +0,0 @@
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{
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"abbr":"ffc",
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"displayName":"FidelityFX_CLI",
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"lastUsedFilePath":"sc",
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"fileNameBeginning":"ig",
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"cliModeOptions": {
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"fsr":{ "displayName": "FidelityFX Super Resolution", "default": true },
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"c":{ "displayName": "Cubic", "default": false },
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"hqc":{ "displayName": "High Quality Cubic", "default": false }
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},
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"pluginCreator": "Janis Hutz",
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"pluginCreatorLink": "https://janishutz.com",
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"engineLink": "",
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"supports": [ "upscaling", "sharpening" ],
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"engineDownloadLink":"",
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"filesToInclude": [ "ffc.py" ]
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}
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@@ -1,319 +0,0 @@
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import os
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import multiprocessing
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import time
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import subprocess
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import sys
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class Scaler:
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def __init__( self ):
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self.os_type = sys.platform
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self.command = ''
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self.tmppath = ''
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self.videometa = {}
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def singleScaler ( self, input_path, output_path, scalefactor, sharpening, threads, mode, tmppath ):
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scaler = 'FSR'
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if ( mode.upper() == 'HQC' ):
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scaler = 'HighQualityCubic'
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elif ( mode.upper() == 'C' ):
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scaler = 'Cubic'
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if ( sharpening == 0 ):
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output = output_path
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elif ( scalefactor != 0 and sharpening != 0 ):
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output = tmppath + 'tmpImage.' + output_path.split( '.' )[ 1 ]
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else:
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output = input_path
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if ( scalefactor != 0 ):
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if self.os_type == 'linux':
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self.command = f'wine ./bin/lib/FidelityFX_CLI.exe -Mode { scaler } -Scale {scalefactor}x {scalefactor}x {input_path} {output}'
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elif self.os_type == 'win32':
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self.command = f'bin\\lib\\FidelityFX_CLI.exe -Mode { scaler } -Scale {scalefactor}x {scalefactor}x {input_path} {output}'
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else:
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print( 'OS CURRENTLY UNSUPPORTED!' )
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return False
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os.system( self.command )
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if ( sharpening != 0 ):
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if self.os_type == 'linux':
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self.command = f'wine ./bin/lib/FidelityFX_CLI.exe -Mode CAS -Sharpness {sharpening} {output} {output_path}'
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elif self.os_type == 'win32':
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self.command = f'bin\\lib\\FidelityFX_CLI.exe -Mode CAS -Sharpness {sharpening} {output} {output_path}'
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else:
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print( 'OS CURRENTLY UNSUPPORTED!' )
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return False
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os.system( self.command )
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print( '\n\n==> Photo upscaled' );
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def videoScaler ( self, tmppath, threads, scalefactor, sharpening, filetype, mode ):
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self.isScaling = True
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if ( scalefactor == 0 or scalefactor == None ):
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self.isScaling = False
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# Locate Images and assemble FSR-Command
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self.file_list = []
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self.filelist = os.listdir( tmppath )
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self.filelist.pop(0)
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self.filelist.sort()
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self.number = 0
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if sharpening != 0 and sharpening != None:
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for self.file in self.filelist:
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self.number += 1
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if ( self.os_type == 'win32' ):
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self.file_list.append( f"{tmppath}{self.file} {tmppath}up\\up{str(self.number).zfill(8)}.{ filetype } " );
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else:
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self.file_list.append( f"{tmppath}{self.file} {tmppath}up/up{str(self.number).zfill(8)}.{ filetype } " );
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try:
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os.mkdir( f'{tmppath}up' )
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except FileExistsError:
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pass
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else:
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for self.file in self.filelist:
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self.number += 1
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if ( self.os_type == 'win32' ):
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self.file_list.append( f"{tmppath}{self.file} {tmppath}sc\\ig{str(self.number).zfill(8)}.{ filetype } " );
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else:
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self.file_list.append( f"{tmppath}{self.file} {tmppath}sc/ig{str(self.number).zfill(8)}.{ filetype } " );
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try:
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os.mkdir( f'{tmppath}sc' )
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except FileExistsError:
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pass
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if ( self.os_type == 'win32' ):
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self.maxlength = 8000
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else:
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self.maxlength = 31900
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self.pos = 1
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############################################
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#
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# Thread optimisation: Divide workload up into different threads & upscale using helper function
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#
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############################################
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self.threads = threads
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if ( threads > multiprocessing.cpu_count() ):
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self.threads = multiprocessing.cpu_count();
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if ( self.isScaling ):
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engines = { 'c': 'Cubic', 'hqc': 'High Quality Cubic', 'fsr':'FidelityFX Super Resolution' }
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print( f'\n\n==> Upscaling using { self.threads } threads <==\n\n' );
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print( f'\n\n==> Upscaling Engine is FidelityFX_CLI with algorithm { engines[ mode.lower() ] } <==\n\n' );
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time.sleep( 2 );
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self.command_list = [];
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self.file_list_length = len( self.file_list );
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for i in range( self.threads ):
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self.files = '';
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for _ in range( int( self.file_list_length // self.threads ) ):
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self.files += self.file_list.pop( 0 );
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if ( i == self.threads - 1 ):
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for element in self.file_list:
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self.files += element;
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self.command_list.append( ( self.files, scalefactor, i, self.maxlength, self.os_type, mode ) )
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self.pool = multiprocessing.Pool( self.threads )
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self.pool.starmap( upscalerEngine, self.command_list );
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self.pool.close();
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self.pool.join();
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if sharpening != 0 and sharpening != None:
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print( f'\n\n\n==> Sharpening using { self.threads } threads <==\n\n' );
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time.sleep( 2 );
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self.pathSharpening = tmppath
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if ( self.isScaling ):
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if ( self.os_type == 'win32' ):
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self.pathSharpening += 'up\\'
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elif ( self.os_type == 'linux' ):
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self.pathSharpening += 'up/'
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time.sleep( 2 );
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try:
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os.mkdir( f'{tmppath}sc' )
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except FileExistsError:
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pass
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# Locate Images and assemble FSR-Command
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self.file_list = []
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self.filelist = os.listdir( self.pathSharpening )
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self.filelist.pop(0)
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self.filelist.sort()
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self.number = 0
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for self.file in self.filelist:
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self.number += 1
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if ( self.os_type == 'win32' ):
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self.file_list.append( f"{self.pathSharpening}{self.file} {tmppath}sc\\ig{str(self.number).zfill(8)}.{ filetype } " );
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else:
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self.file_list.append( f"{self.pathSharpening}{self.file} {tmppath}sc/ig{str(self.number).zfill(8)}.{ filetype } " );
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if ( self.os_type == 'win32' ):
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self.maxlength = 8000
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else:
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self.maxlength = 31900
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self.pos = 1
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# assemble command list
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self.command_list = [];
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self.file_list_length = len( self.file_list );
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for i in range( self.threads ):
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self.files = '';
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for _ in range( int( self.file_list_length // self.threads ) ):
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self.files += self.file_list.pop( 0 );
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if ( i == self.threads - 1 ):
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for element in self.file_list:
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self.files += element;
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self.command_list.append( ( self.files, i, self.maxlength, self.os_type, sharpening, not sharpening ) )
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self.pool = multiprocessing.Pool( self.threads )
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self.pool.starmap( sharpeningEngine, self.command_list );
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self.pool.close();
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self.pool.join();
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# Add return values
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def upscalerEngine ( files, scalefactor, number, maxlength, os_type, version ):
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scaler = 'FSR'
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if ( version.upper() == 'HQC' ):
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scaler = 'HighQualityCubic'
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elif ( version.upper() == 'C' ):
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scaler = 'Cubic'
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files = files;
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# Refactoring of commands that are longer than 32K characters
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fileout = [];
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pos = 0;
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if len( files ) > maxlength:
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while files[maxlength - pos:maxlength - pos + 1] != ' ':
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pos += 1
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file_processing = files[:maxlength - pos]
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if file_processing[len(file_processing) - 14:len(file_processing) - 12] == 'ig':
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pos += 5
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else:
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pass
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while files[maxlength - pos:maxlength - pos + 1] != ' ':
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pos += 1
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fileout.append(files[:maxlength - pos])
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filesopt = files[maxlength - pos:]
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posx = 0
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posy = maxlength
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# Command refactoring for commands that are longer than 64K characters
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if len(filesopt) > maxlength:
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while len(filesopt) > maxlength:
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posx += maxlength - pos
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posy += maxlength - pos
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pos = 1
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while files[posy - pos:posy - pos + 1] != ' ':
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pos += 1
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file_processing = files[posx:posy - pos]
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if file_processing[len(file_processing) - 14:len(file_processing) - 12] == 'ig':
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pos += 5
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while files[posy - pos:posy - pos + 1] != ' ':
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pos += 1
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file_processing = files[posx:posy - pos]
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fileout.append(file_processing)
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filesopt = files[posy - pos:]
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fileout.append(filesopt)
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else:
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fileout.append(files[maxlength - pos:])
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else:
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fileout.append(files)
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# Upscaling images
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print( '\n\n\nUpscaling images... \n\n\n\n\n\n PROCESS: ', number, '\n\n\n' )
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while len( fileout ) > 0:
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files_handle = fileout.pop(0)
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if os_type == 'linux':
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command_us = f'wine ./bin/lib/FidelityFX_CLI.exe -Mode { scaler } -Scale {scalefactor}x {scalefactor}x {files_handle}'
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elif os_type == 'win32':
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command_us = f'bin\\lib\\FidelityFX_CLI.exe -Mode { scaler } -Scale {scalefactor}x {scalefactor}x {files_handle}'
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else:
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print( 'OS CURRENTLY UNSUPPORTED!' )
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return False
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sub = subprocess.Popen( command_us, shell=True );
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sub.wait();
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time.sleep(3)
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print( '\n\nCompleted executing Job\n\n\n PROCESS: ', number, '\n\n\n' );
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########################
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#
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# Sharpening
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#
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#######################
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def sharpeningEngine ( files, number, maxlength, os_type, sharpening, didUpscale ):
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files = files;
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# Refactoring of commands that are longer than 32K characters
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fileout = [];
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pos = 0;
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if len( files ) > maxlength:
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while files[maxlength - pos:maxlength - pos + 1] != ' ':
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pos += 1
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file_processing = files[:maxlength - pos]
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if ( didUpscale ):
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if file_processing[len(file_processing) - 14:len(file_processing) - 12] == 'up':
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pos += 5
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else:
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if file_processing[len(file_processing) - 17:len(file_processing) - 15] == 'ru':
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pos += 8
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while files[maxlength - pos:maxlength - pos + 1] != ' ':
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pos += 1
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fileout.append(files[:maxlength - pos])
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filesopt = files[maxlength - pos:]
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posx = 0
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posy = maxlength
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# Command refactoring for commands that are longer than 64K characters
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if len(filesopt) > maxlength:
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while len(filesopt) > maxlength:
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posx += maxlength - pos
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posy += maxlength - pos
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pos = 1
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while files[posy - pos:posy - pos + 1] != ' ':
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pos += 1
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file_processing = files[posx:posy - pos]
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if ( didUpscale ):
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if file_processing[len(file_processing) - 14:len(file_processing) - 12] == 'up':
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pos += 5
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else:
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if file_processing[len(file_processing) - 17:len(file_processing) - 15] == 'ru':
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pos += 8
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while files[posy - pos:posy - pos + 1] != ' ':
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pos += 1
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file_processing = files[posx:posy - pos]
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fileout.append(file_processing)
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filesopt = files[posy - pos:]
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fileout.append(filesopt)
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else:
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fileout.append(files[maxlength - pos:])
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else:
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fileout.append(files)
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# Upscaling images
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print( '\n\n\nSharpening images... \n\n\n\n\n\n PROCESS: ', number, '\n\n\n' )
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while len( fileout ) > 0:
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files_handle = fileout.pop(0)
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print( '\n\n\n PROCESS: ', number, '\nRunning sharpening filter\n\n\n' );
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if os_type == 'linux':
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command_sharpening = f'wine ./bin/lib/FidelityFX_CLI.exe -Mode CAS -Sharpness {sharpening} {files_handle}'
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elif os_type == 'win32':
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command_sharpening = f'bin\\lib\\FidelityFX_CLI.exe -Mode CAS -Sharpness {sharpening} {files_handle}'
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else:
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print( 'OS CURRENTLY UNSUPPORTED!' )
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return False
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sub2 = subprocess.Popen( command_sharpening, shell=True );
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sub2.wait()
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time.sleep(3)
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print( '\n\nCompleted executing Job\n\n\n PROCESS: ', number, '\n\n\n' );
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@@ -1,16 +0,0 @@
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{
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"abbr":"SS",
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"displayName":"Real-ESGRAN",
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"lastUsedFilePath":"sc",
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"fileNameBeginning":"ig",
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"cliModeOptions": {
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"av3":{ "displayName": "realesr-animevideov3", "default": true },
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"x4plus":{ "displayName": "realesrgan-x4plus-anime", "default": false }
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},
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"pluginCreator": "Janis Hutz",
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"pluginCreatorLink": "https://janishutz.com",
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"engineLink": "",
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"supports": [ "upscaling" ],
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"engineDownloadLink":"",
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"filesToInclude": [ "fsr.py" ]
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}
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@@ -1,40 +0,0 @@
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import os
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import subprocess
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import multiprocessing
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import time
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import sys
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class Scaler:
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def __init__(self):
|
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self.os_type = sys.platform
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self.command = ""
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self.tmppath = ""
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self.videometa = {}
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def singleScaler ( self, input_path, output_path, scalefactor, sharpening, threads, mode, tmppath ):
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modes = { 'av3':'realesr-animevideov3', 'x4plus': 'realesrgan-x4plus-anime' }
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if self.os_type == 'linux':
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self.command = f'wine ./bin/lib/realesrgan-ncnn-vulkan.exe -i {input_path} -o {output_path} -s {scalefactor} -j {threads}:{threads}:{threads} -n { modes[ mode ] }'
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elif self.os_type == 'win32':
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self.command = f'bin\\lib\\realesrgan-ncnn-vulkan.exe -i {input_path} -o {output_path} -s {scalefactor} -j {threads}:{threads}:{threads} -n { modes[ mode ] }'
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else:
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print( 'OS CURRENTLY UNSUPPORTED!' )
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return False
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os.system( self.command )
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print( '\n\n==>Photo upscaled' );
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def videoScaler ( self, tmppath, threads, scalefactor, sharpening, filetype, mode ):
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modes = { 'av3':'realesr-animevideov3', 'x4plus': 'realesrgan-x4plus-anime' }
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print( '\n\n==> Preparing to upscale videos <==\n\n==> You will see a lot of numbers flying by showing the progress of the upscaling of each individual image.\n==> This process might take a long time, depending on the length of the video.\n\n')
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time.sleep( 2 );
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try:
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os.mkdir( f'{tmppath}sc' )
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except FileExistsError:
|
||||
pass
|
||||
if ( self.os_type == 'win32' ):
|
||||
self.command = f'bin\\lib\\realesrgan-ncnn-vulkan.exe -i {tmppath} -o {tmppath}sc -s {scalefactor} -j {threads}:{threads}:{threads} -n {modes[ mode ]}'
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elif ( self.os_type == 'linux' ):
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self.command = f'wine ./bin/lib/realesrgan-ncnn-vulkan.exe -i {tmppath} -o {tmppath}sc -s {scalefactor} -j {threads}:{threads}:{threads} -n {modes[ mode ]}'
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os.system( self.command );
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184
bin/handler.py
184
bin/handler.py
@@ -1,184 +0,0 @@
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'''
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* SimpleMediaUpscalerLite - handler.py
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*
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||||
* Created by Janis Hutz 03/14/2023, Licensed under the GPL V3 License
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||||
* https://janishutz.com, development@janishutz.com
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||||
*
|
||||
*
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||||
'''
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||||
|
||||
|
||||
import os
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||||
import sys
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||||
import bin.probe
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||||
ffmpeg = bin.probe
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import configparser
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||||
import json
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||||
import importlib
|
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import shutil
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import time
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||||
import tempfile
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||||
|
||||
importedModules = {}
|
||||
|
||||
engineList = os.listdir( 'bin/engines' );
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||||
counter = 0;
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||||
for element in engineList:
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||||
if ( element == '__pycache__' ):
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||||
engineList.pop( counter );
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||||
counter += 1;
|
||||
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||||
for element in engineList:
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||||
importedModules[ element ] = importlib.import_module( 'bin.engines.' + element + '.' + element ).Scaler()
|
||||
|
||||
# Loading the config file to get user preferred temp path
|
||||
config = configparser.ConfigParser()
|
||||
config.read('./config/settings.ini')
|
||||
|
||||
|
||||
class Handler:
|
||||
def __init__(self):
|
||||
self.os_type = sys.platform
|
||||
self.command = ''
|
||||
self.tmppath = ''
|
||||
self.videometa = {}
|
||||
|
||||
|
||||
# TODO: CHECK if this upscaler is any good: https://github.com/Maximellerbach/Image-Processing-using-AI (looks quite promising)
|
||||
|
||||
def handler( self, filepath, scalefactor, output_path, sharpening, filetype, engine, mode, threads=4 ):
|
||||
# Function to be called when using this class as this function automatically determines if file is video or image
|
||||
print( '\n\n SimpleMediaUpscalerLite - V1.1.0\n\n(c) 2023 SimpleMediaUpscalerLite contributors\n\n\n\n' );
|
||||
|
||||
if self.os_type == 'linux':
|
||||
self.tmppath = tempfile.gettempdir()
|
||||
elif self.os_type == 'win32':
|
||||
self.tmppath = tempfile.gettempdir()
|
||||
else:
|
||||
print('OS CURRENTLY UNSUPPORTED!')
|
||||
return False
|
||||
if ( self.os_type == 'win32' ):
|
||||
self.tmppath += '\\fsru\\'
|
||||
else:
|
||||
if ( self.tmppath[len(self.tmppath) - 1: ] == '/' ):
|
||||
self.tmppath += 'fsru/'
|
||||
else:
|
||||
self.tmppath += '/fsru/'
|
||||
|
||||
# checking for spaces in filepath (for use with terminal commands)
|
||||
self.filepath = ''
|
||||
for self.letter in filepath:
|
||||
if self.letter == ' ':
|
||||
self.filepath += '\ '
|
||||
else:
|
||||
self.filepath += self.letter
|
||||
|
||||
try:
|
||||
shutil.rmtree(self.tmppath)
|
||||
except FileNotFoundError:
|
||||
pass
|
||||
try:
|
||||
os.mkdir(self.tmppath)
|
||||
except FileExistsError:
|
||||
print( '==> ERROR: Temp path does not exist! <==' )
|
||||
return False
|
||||
|
||||
# Determining filetype
|
||||
if str(filepath)[len(filepath) - 4:] == '.mp4' or str(filepath)[len(filepath) - 4:] == '.mkv' or str(filepath)[len(filepath) - 4:] == '.MP4':
|
||||
print( '\n\n==> Upscaling video' )
|
||||
self.video_scaling( filepath, output_path, scalefactor, threads, sharpening, filetype, mode, engine )
|
||||
elif str(filepath)[len(filepath) - 4:] == '.JPG' or str(filepath)[len(filepath) - 4:] == '.png' or str(filepath)[len(filepath) - 4:] == '.jpg' or str(filepath)[len(filepath) - 5:] == '.jpeg':
|
||||
print( '\n==> Upscaling Image' )
|
||||
self.photo_scaling( filepath, output_path, scalefactor, sharpening, threads, engine, mode )
|
||||
else:
|
||||
print('not supported')
|
||||
return False
|
||||
|
||||
def photo_scaling(self, input_path, output_path, scalefactor, sharpening, threads, engine, mode ):
|
||||
# DO NOT CALL THIS! Use Handler().handler() instead!
|
||||
importedModules[ engine ].singleScaler( input_path, output_path, scalefactor, sharpening, threads, mode, self.tmppath );
|
||||
|
||||
def video_scaling( self, input_path, output_path, scalefactor, threads, sharpening, filetype, mode, engine ):
|
||||
self.engineSetting = json.load( open( 'bin/engines/' + engine + '/config.json' ) )
|
||||
# DO NOT CALL THIS! Use Handler().handler() instead!
|
||||
|
||||
# Splitting video into frames
|
||||
|
||||
print( '\n==> Created directory' )
|
||||
|
||||
if self.os_type == 'linux':
|
||||
self.command = f'ffmpeg -i {str(self.filepath)} {self.tmppath}ig%08d.{ filetype }'
|
||||
elif self.os_type == 'win32':
|
||||
self.command = f'ffmpeg -i {str(self.filepath)} \"{self.tmppath}ig%08d.{ filetype }\"'
|
||||
else:
|
||||
print('OS CURRENTLY UNSUPPORTED!')
|
||||
return False
|
||||
|
||||
os.system( self.command )
|
||||
print( '\n==> Video split ' )
|
||||
|
||||
# Retrieving Video metadata
|
||||
self.filelist = os.listdir(self.tmppath)
|
||||
try:
|
||||
self.videometa = ffmpeg.probe(str(input_path))['streams'].pop(0)
|
||||
except Exception:
|
||||
print( '\n\n==> Failed to execute ffprobe. Please ensure that you have a valid ffmpeg & ffprobe installation.\n --> Refer to our wiki for a guide on a proper installation\n\n')
|
||||
return False;
|
||||
|
||||
self.duration = self.videometa.get( 'duration' )
|
||||
self.frames = len( self.filelist )
|
||||
try:
|
||||
self.framerate = round(float(self.frames) / float(self.duration), 1)
|
||||
except TypeError:
|
||||
print( '\n\n=> using fallback method to get framerate' )
|
||||
self.infos = str( self.videometa.get( 'r_frame_rate' ) )
|
||||
self.framerate = float( self.infos[:len(self.infos) - 2] )
|
||||
|
||||
print( '\n\n==> Video duration is: ', self.duration, 's' )
|
||||
print( '==> Framecount is: ', self.frames, ' frames' )
|
||||
print( '==> Frame rate is: ', self.framerate, ' FPS' )
|
||||
print( '==> Running with: ', threads, ' threads\n\n' )
|
||||
|
||||
time.sleep( 2 );
|
||||
|
||||
importedModules[ engine ].videoScaler ( self.tmppath, int( threads ), int( scalefactor ), float( sharpening ), filetype, mode )
|
||||
|
||||
# get Video's audio
|
||||
print( '\n\n==>Finished Upscaling individual images. \n==>Retrieving Video audio to append\n\n' )
|
||||
|
||||
try:
|
||||
self.framerate = round(float(self.frames) / float(self.duration), 1)
|
||||
except TypeError:
|
||||
print( '\n\n=> using fallback method to get framerate' )
|
||||
self.infos = str( self.videometa.get( 'r_frame_rate' ) )
|
||||
self.framerate = float( self.infos[:len(self.infos) - 2] )
|
||||
|
||||
time.sleep( 2 );
|
||||
try:
|
||||
os.remove(f'{self.tmppath}audio.aac')
|
||||
os.remove(f'{output_path}')
|
||||
except FileNotFoundError:
|
||||
pass
|
||||
if self.os_type == 'linux':
|
||||
self.command = f'ffmpeg -i {self.filepath} -vn -acodec copy {self.tmppath}audio.aac'
|
||||
elif self.os_type == 'win32':
|
||||
self.command = f'ffmpeg -i {self.filepath} -vn -acodec copy {self.tmppath}audio.aac'
|
||||
else:
|
||||
print( 'OS CURRENTLY UNSUPPORTED!' )
|
||||
return False
|
||||
os.system( self.command )
|
||||
|
||||
|
||||
|
||||
# reassemble Video
|
||||
print( '\n\n==> Reassembling Video... with framerate @', self.framerate, '\n\n' )
|
||||
if self.os_type == 'linux':
|
||||
self.command = f'ffmpeg -framerate {self.framerate} -i {self.tmppath}{self.engineSetting[ "lastUsedFilePath" ]}/{self.engineSetting[ "fileNameBeginning" ]}%08d.{filetype} {output_path} -i {self.tmppath}audio.aac'
|
||||
elif self.os_type == 'win32':
|
||||
self.command = f'ffmpeg -framerate {self.framerate} -i \'{self.tmppath}{self.engineSetting[ "lastUsedFilePath" ]}\\{self.engineSetting[ "fileNameBeginning" ]}%08d.{filetype}\' {output_path} -i {self.tmppath}audio.aac'
|
||||
else:
|
||||
print( 'OS CURRENTLY UNSUPPORTED!' );
|
||||
return False
|
||||
os.system( self.command )
|
||||
|
||||
return True;
|
||||
Binary file not shown.
Binary file not shown.
154
bin/lib/edi.py
154
bin/lib/edi.py
@@ -1,154 +0,0 @@
|
||||
import cv2
|
||||
import numpy as np
|
||||
from matplotlib import pyplot as plt
|
||||
import math
|
||||
import sys
|
||||
|
||||
"""
|
||||
Author:
|
||||
|
||||
hu.leying@columbia.edu
|
||||
|
||||
Usage:
|
||||
|
||||
EDI_predict(img, m, s)
|
||||
|
||||
# img is the input image
|
||||
# m is the sampling window size, not scaling factor! The larger the m, more blurry the image. Ideal m >= 4.
|
||||
# s is the scaling factor, support any s > 0 (e.g. use s=2 to upscale by 2, use s=0.5 to downscale by 2)
|
||||
|
||||
If you want to directly call EDI_upscale to upscale image by the scale of 2:
|
||||
|
||||
EDI_upscale(img, m)
|
||||
|
||||
# m should be the power of 2. Will increment by 1 if input m is odd
|
||||
|
||||
If you want to directly call EDI_downscale to downscale image by the scale of 2:
|
||||
|
||||
EDI_downscale(img)
|
||||
|
||||
"""
|
||||
|
||||
def EDI_downscale(img):
|
||||
|
||||
# initializing downgraded image
|
||||
w, h = img.shape
|
||||
imgo2 = np.zeros((w//2, h//2))
|
||||
|
||||
# downgrading image
|
||||
for i in range(w//2):
|
||||
for j in range(h//2):
|
||||
imgo2[i][j] = int(img[2*i][2*j])
|
||||
|
||||
return imgo2.astype(img.dtype)
|
||||
|
||||
def EDI_upscale(img, m):
|
||||
|
||||
# m should be equal to a power of 2
|
||||
if m%2 != 0:
|
||||
m += 1
|
||||
|
||||
# initializing image to be predicted
|
||||
w, h = img.shape
|
||||
imgo = np.zeros((w*2,h*2))
|
||||
|
||||
# Place low-resolution pixels
|
||||
for i in range(w):
|
||||
for j in range(h):
|
||||
imgo[2*i][2*j] = img[i][j]
|
||||
|
||||
y = np.zeros((m**2,1)) # pixels in the window
|
||||
C = np.zeros((m**2,4)) # interpolation neighbours of each pixel in the window
|
||||
|
||||
# Reconstruct the points with the form of (2*i+1,2*j+1)
|
||||
for i in range(math.floor(m/2), w-math.floor(m/2)):
|
||||
for j in range(math.floor(m/2), h-math.floor(m/2)):
|
||||
tmp = 0
|
||||
for ii in range(i-math.floor(m/2), i+math.floor(m/2)):
|
||||
for jj in range(j-math.floor(m/2), j+math.floor(m/2)):
|
||||
y[tmp][0] = imgo[2*ii][2*jj]
|
||||
C[tmp][0] = imgo[2*ii-2][2*jj-2]
|
||||
C[tmp][1] = imgo[2*ii+2][2*jj-2]
|
||||
C[tmp][2] = imgo[2*ii+2][2*jj+2]
|
||||
C[tmp][3] = imgo[2*ii-2][2*jj+2]
|
||||
tmp += 1
|
||||
|
||||
# calculating weights
|
||||
# a = (C^T * C)^(-1) * (C^T * y) = (C^T * C) \ (C^T * y)
|
||||
a = np.matmul(np.matmul(np.linalg.pinv(np.matmul(np.transpose(C),C)), np.transpose(C)), y)
|
||||
imgo[2*i+1][2*j+1] = np.matmul([imgo[2*i][2*j], imgo[2*i+2][2*j], imgo[2*i+2][2*j+2], imgo[2*i][2*j+2]], a)
|
||||
|
||||
# Reconstructed the points with the forms of (2*i+1,2*j) and (2*i,2*j+1)
|
||||
for i in range(math.floor(m/2), w-math.floor(m/2)):
|
||||
for j in range(math.floor(m/2), h-math.floor(m/2)):
|
||||
tmp = 0
|
||||
for ii in range(i-math.floor(m/2), i+math.floor(m/2)):
|
||||
for jj in range(j-math.floor(m/2), j+math.floor(m/2)):
|
||||
y[tmp][0] = imgo[2*ii+1][2*jj-1]
|
||||
C[tmp][0] = imgo[2*ii-1][2*jj-1]
|
||||
C[tmp][1] = imgo[2*ii+1][2*jj-3]
|
||||
C[tmp][2] = imgo[2*ii+3][2*jj-1]
|
||||
C[tmp][3] = imgo[2*ii+1][2*jj+1]
|
||||
tmp += 1
|
||||
|
||||
# calculating weights
|
||||
# a = (C^T * C)^(-1) * (C^T * y) = (C^T * C) \ (C^T * y)
|
||||
a = np.matmul(np.matmul(np.linalg.pinv(np.matmul(np.transpose(C),C)), np.transpose(C)), y)
|
||||
imgo[2*i+1][2*j] = np.matmul([imgo[2*i][2*j], imgo[2*i+1][2*j-1], imgo[2*i+2][2*j], imgo[2*i+1][2*j+1]], a)
|
||||
imgo[2*i][2*j+1] = np.matmul([imgo[2*i-1][2*j+1], imgo[2*i][2*j], imgo[2*i+1][2*j+1], imgo[2*i][2*j+2]], a)
|
||||
|
||||
# Fill the rest with bilinear interpolation
|
||||
np.clip(imgo, 0, 255.0, out=imgo)
|
||||
imgo_bilinear = cv2.resize(img, dsize=(h*2,w*2), interpolation=cv2.INTER_LINEAR)
|
||||
imgo[imgo==0] = imgo_bilinear[imgo==0]
|
||||
|
||||
return imgo.astype(img.dtype)
|
||||
|
||||
def EDI_predict(img, m, s):
|
||||
|
||||
try:
|
||||
w, h = img.shape
|
||||
except:
|
||||
sys.exit("Error input: Please input a valid grayscale image!")
|
||||
|
||||
output_type = img.dtype
|
||||
|
||||
if s <= 0:
|
||||
sys.exit("Error input: Please input s > 0!")
|
||||
|
||||
elif s == 1:
|
||||
print("No need to rescale since s = 1")
|
||||
return img
|
||||
|
||||
elif s < 1:
|
||||
# Calculate how many times to do the EDI downscaling
|
||||
n = math.floor(math.log(1/s, 2))
|
||||
|
||||
# Downscale to the expected size with linear interpolation
|
||||
linear_factor = 1/s / math.pow(2, n)
|
||||
if linear_factor != 1:
|
||||
img = cv2.resize(img, dsize=(int(h/linear_factor),int(w/linear_factor)), interpolation=cv2.INTER_LINEAR).astype(output_type)
|
||||
|
||||
for i in range(n):
|
||||
img = EDI_downscale(img)
|
||||
return img
|
||||
|
||||
elif s < 2:
|
||||
# Linear Interpolation is enough for upscaling not over 2
|
||||
return cv2.resize(img, dsize=(int(h*s),int(w*s)), interpolation=cv2.INTER_LINEAR).astype(output_type)
|
||||
|
||||
else:
|
||||
# Calculate how many times to do the EDI upscaling
|
||||
n = math.floor(math.log(s, 2))
|
||||
for i in range(n):
|
||||
img = EDI_upscale(img, m)
|
||||
|
||||
# Upscale to the expected size with linear interpolation
|
||||
linear_factor = s / math.pow(2, n)
|
||||
if linear_factor == 1:
|
||||
return img.astype(output_type)
|
||||
|
||||
# Update new shape
|
||||
w, h = img.shape
|
||||
return cv2.resize(img, dsize=(int(h*linear_factor),int(w*linear_factor)), interpolation=cv2.INTER_LINEAR).astype(output_type)
|
||||
|
||||
Binary file not shown.
@@ -1,43 +0,0 @@
|
||||
7767517
|
||||
41 42
|
||||
Input input.1 0 1 data
|
||||
Split splitncnn_input0 1 2 data input.1_splitncnn_0 input.1_splitncnn_1
|
||||
Convolution Conv_0 1 1 input.1_splitncnn_1 54 0=64 1=3 4=1 5=1 6=1728
|
||||
PReLU PRelu_1 1 1 54 56 0=64
|
||||
Convolution Conv_2 1 1 56 57 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_3 1 1 57 59 0=64
|
||||
Convolution Conv_4 1 1 59 60 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_5 1 1 60 62 0=64
|
||||
Convolution Conv_6 1 1 62 63 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_7 1 1 63 65 0=64
|
||||
Convolution Conv_8 1 1 65 66 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_9 1 1 66 68 0=64
|
||||
Convolution Conv_10 1 1 68 69 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_11 1 1 69 71 0=64
|
||||
Convolution Conv_12 1 1 71 72 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_13 1 1 72 74 0=64
|
||||
Convolution Conv_14 1 1 74 75 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_15 1 1 75 77 0=64
|
||||
Convolution Conv_16 1 1 77 78 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_17 1 1 78 80 0=64
|
||||
Convolution Conv_18 1 1 80 81 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_19 1 1 81 83 0=64
|
||||
Convolution Conv_20 1 1 83 84 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_21 1 1 84 86 0=64
|
||||
Convolution Conv_22 1 1 86 87 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_23 1 1 87 89 0=64
|
||||
Convolution Conv_24 1 1 89 90 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_25 1 1 90 92 0=64
|
||||
Convolution Conv_26 1 1 92 93 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_27 1 1 93 95 0=64
|
||||
Convolution Conv_28 1 1 95 96 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_29 1 1 96 98 0=64
|
||||
Convolution Conv_30 1 1 98 99 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_31 1 1 99 101 0=64
|
||||
Convolution Conv_32 1 1 101 102 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_33 1 1 102 104 0=64
|
||||
Convolution Conv_34 1 1 104 105 0=48 1=3 4=1 5=1 6=27648
|
||||
PixelShuffle DepthToSpace_35 1 1 105 106 0=4
|
||||
Interp Resize_37 1 1 input.1_splitncnn_0 111 0=1 1=4.000000e+00 2=4.000000e+00
|
||||
BinaryOp Add_38 2 1 106 111 112
|
||||
Interp Resize_40 1 1 112 output 0=3 1=5.000000e-01 2=5.000000e-01
|
||||
Binary file not shown.
@@ -1,43 +0,0 @@
|
||||
7767517
|
||||
41 42
|
||||
Input input.1 0 1 data
|
||||
Split splitncnn_input0 1 2 data input.1_splitncnn_0 input.1_splitncnn_1
|
||||
Convolution Conv_0 1 1 input.1_splitncnn_1 54 0=64 1=3 4=1 5=1 6=1728
|
||||
PReLU PRelu_1 1 1 54 56 0=64
|
||||
Convolution Conv_2 1 1 56 57 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_3 1 1 57 59 0=64
|
||||
Convolution Conv_4 1 1 59 60 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_5 1 1 60 62 0=64
|
||||
Convolution Conv_6 1 1 62 63 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_7 1 1 63 65 0=64
|
||||
Convolution Conv_8 1 1 65 66 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_9 1 1 66 68 0=64
|
||||
Convolution Conv_10 1 1 68 69 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_11 1 1 69 71 0=64
|
||||
Convolution Conv_12 1 1 71 72 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_13 1 1 72 74 0=64
|
||||
Convolution Conv_14 1 1 74 75 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_15 1 1 75 77 0=64
|
||||
Convolution Conv_16 1 1 77 78 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_17 1 1 78 80 0=64
|
||||
Convolution Conv_18 1 1 80 81 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_19 1 1 81 83 0=64
|
||||
Convolution Conv_20 1 1 83 84 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_21 1 1 84 86 0=64
|
||||
Convolution Conv_22 1 1 86 87 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_23 1 1 87 89 0=64
|
||||
Convolution Conv_24 1 1 89 90 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_25 1 1 90 92 0=64
|
||||
Convolution Conv_26 1 1 92 93 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_27 1 1 93 95 0=64
|
||||
Convolution Conv_28 1 1 95 96 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_29 1 1 96 98 0=64
|
||||
Convolution Conv_30 1 1 98 99 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_31 1 1 99 101 0=64
|
||||
Convolution Conv_32 1 1 101 102 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_33 1 1 102 104 0=64
|
||||
Convolution Conv_34 1 1 104 105 0=48 1=3 4=1 5=1 6=27648
|
||||
PixelShuffle DepthToSpace_35 1 1 105 106 0=4
|
||||
Interp Resize_37 1 1 input.1_splitncnn_0 111 0=1 1=4.000000e+00 2=4.000000e+00
|
||||
BinaryOp Add_38 2 1 106 111 112
|
||||
Interp Resize_40 1 1 112 output 0=3 1=7.500000e-01 2=7.500000e-01
|
||||
Binary file not shown.
@@ -1,42 +0,0 @@
|
||||
7767517
|
||||
40 41
|
||||
Input input.1 0 1 data
|
||||
Split splitncnn_input0 1 2 data input.1_splitncnn_0 input.1_splitncnn_1
|
||||
Convolution Conv_0 1 1 input.1_splitncnn_1 54 0=64 1=3 4=1 5=1 6=1728
|
||||
PReLU PRelu_1 1 1 54 56 0=64
|
||||
Convolution Conv_2 1 1 56 57 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_3 1 1 57 59 0=64
|
||||
Convolution Conv_4 1 1 59 60 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_5 1 1 60 62 0=64
|
||||
Convolution Conv_6 1 1 62 63 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_7 1 1 63 65 0=64
|
||||
Convolution Conv_8 1 1 65 66 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_9 1 1 66 68 0=64
|
||||
Convolution Conv_10 1 1 68 69 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_11 1 1 69 71 0=64
|
||||
Convolution Conv_12 1 1 71 72 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_13 1 1 72 74 0=64
|
||||
Convolution Conv_14 1 1 74 75 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_15 1 1 75 77 0=64
|
||||
Convolution Conv_16 1 1 77 78 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_17 1 1 78 80 0=64
|
||||
Convolution Conv_18 1 1 80 81 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_19 1 1 81 83 0=64
|
||||
Convolution Conv_20 1 1 83 84 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_21 1 1 84 86 0=64
|
||||
Convolution Conv_22 1 1 86 87 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_23 1 1 87 89 0=64
|
||||
Convolution Conv_24 1 1 89 90 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_25 1 1 90 92 0=64
|
||||
Convolution Conv_26 1 1 92 93 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_27 1 1 93 95 0=64
|
||||
Convolution Conv_28 1 1 95 96 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_29 1 1 96 98 0=64
|
||||
Convolution Conv_30 1 1 98 99 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_31 1 1 99 101 0=64
|
||||
Convolution Conv_32 1 1 101 102 0=64 1=3 4=1 5=1 6=36864
|
||||
PReLU PRelu_33 1 1 102 104 0=64
|
||||
Convolution Conv_34 1 1 104 105 0=48 1=3 4=1 5=1 6=27648
|
||||
PixelShuffle DepthToSpace_35 1 1 105 106 0=4
|
||||
Interp Resize_37 1 1 input.1_splitncnn_0 111 0=1 1=4.000000e+00 2=4.000000e+00
|
||||
BinaryOp Add_38 2 1 106 111 output
|
||||
Binary file not shown.
@@ -1,270 +0,0 @@
|
||||
7767517
|
||||
268 473
|
||||
Input input.1 0 1 data
|
||||
Convolution Conv_0 1 1 data 193 0=64 1=3 4=1 5=1 6=1728
|
||||
Split splitncnn_0 1 8 193 193_splitncnn_0 193_splitncnn_1 193_splitncnn_2 193_splitncnn_3 193_splitncnn_4 193_splitncnn_5 193_splitncnn_6 193_splitncnn_7
|
||||
Convolution Conv_1 1 1 193_splitncnn_7 195 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_1 1 4 195 195_splitncnn_0 195_splitncnn_1 195_splitncnn_2 195_splitncnn_3
|
||||
Concat Concat_3 2 1 193_splitncnn_6 195_splitncnn_3 196
|
||||
Convolution Conv_4 1 1 196 198 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_2 1 3 198 198_splitncnn_0 198_splitncnn_1 198_splitncnn_2
|
||||
Concat Concat_6 3 1 193_splitncnn_5 195_splitncnn_2 198_splitncnn_2 199
|
||||
Convolution Conv_7 1 1 199 201 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_3 1 2 201 201_splitncnn_0 201_splitncnn_1
|
||||
Concat Concat_9 4 1 193_splitncnn_4 195_splitncnn_1 198_splitncnn_1 201_splitncnn_1 202
|
||||
Convolution Conv_10 1 1 202 204 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_12 5 1 193_splitncnn_3 195_splitncnn_0 198_splitncnn_0 201_splitncnn_0 204 205
|
||||
Convolution Conv_13 1 1 205 206 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_16 2 1 206 193_splitncnn_2 209 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_4 1 6 209 209_splitncnn_0 209_splitncnn_1 209_splitncnn_2 209_splitncnn_3 209_splitncnn_4 209_splitncnn_5
|
||||
Convolution Conv_17 1 1 209_splitncnn_5 211 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_5 1 4 211 211_splitncnn_0 211_splitncnn_1 211_splitncnn_2 211_splitncnn_3
|
||||
Concat Concat_19 2 1 209_splitncnn_4 211_splitncnn_3 212
|
||||
Convolution Conv_20 1 1 212 214 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_6 1 3 214 214_splitncnn_0 214_splitncnn_1 214_splitncnn_2
|
||||
Concat Concat_22 3 1 209_splitncnn_3 211_splitncnn_2 214_splitncnn_2 215
|
||||
Convolution Conv_23 1 1 215 217 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_7 1 2 217 217_splitncnn_0 217_splitncnn_1
|
||||
Concat Concat_25 4 1 209_splitncnn_2 211_splitncnn_1 214_splitncnn_1 217_splitncnn_1 218
|
||||
Convolution Conv_26 1 1 218 220 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_28 5 1 209_splitncnn_1 211_splitncnn_0 214_splitncnn_0 217_splitncnn_0 220 221
|
||||
Convolution Conv_29 1 1 221 222 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_32 2 1 222 209_splitncnn_0 225 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_8 1 6 225 225_splitncnn_0 225_splitncnn_1 225_splitncnn_2 225_splitncnn_3 225_splitncnn_4 225_splitncnn_5
|
||||
Convolution Conv_33 1 1 225_splitncnn_5 227 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_9 1 4 227 227_splitncnn_0 227_splitncnn_1 227_splitncnn_2 227_splitncnn_3
|
||||
Concat Concat_35 2 1 225_splitncnn_4 227_splitncnn_3 228
|
||||
Convolution Conv_36 1 1 228 230 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_10 1 3 230 230_splitncnn_0 230_splitncnn_1 230_splitncnn_2
|
||||
Concat Concat_38 3 1 225_splitncnn_3 227_splitncnn_2 230_splitncnn_2 231
|
||||
Convolution Conv_39 1 1 231 233 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_11 1 2 233 233_splitncnn_0 233_splitncnn_1
|
||||
Concat Concat_41 4 1 225_splitncnn_2 227_splitncnn_1 230_splitncnn_1 233_splitncnn_1 234
|
||||
Convolution Conv_42 1 1 234 236 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_44 5 1 225_splitncnn_1 227_splitncnn_0 230_splitncnn_0 233_splitncnn_0 236 237
|
||||
Convolution Conv_45 1 1 237 238 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_48 2 1 238 225_splitncnn_0 241 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Eltwise Add_51 2 1 241 193_splitncnn_1 244 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_12 1 7 244 244_splitncnn_0 244_splitncnn_1 244_splitncnn_2 244_splitncnn_3 244_splitncnn_4 244_splitncnn_5 244_splitncnn_6
|
||||
Convolution Conv_52 1 1 244_splitncnn_6 246 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_13 1 4 246 246_splitncnn_0 246_splitncnn_1 246_splitncnn_2 246_splitncnn_3
|
||||
Concat Concat_54 2 1 244_splitncnn_5 246_splitncnn_3 247
|
||||
Convolution Conv_55 1 1 247 249 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_14 1 3 249 249_splitncnn_0 249_splitncnn_1 249_splitncnn_2
|
||||
Concat Concat_57 3 1 244_splitncnn_4 246_splitncnn_2 249_splitncnn_2 250
|
||||
Convolution Conv_58 1 1 250 252 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_15 1 2 252 252_splitncnn_0 252_splitncnn_1
|
||||
Concat Concat_60 4 1 244_splitncnn_3 246_splitncnn_1 249_splitncnn_1 252_splitncnn_1 253
|
||||
Convolution Conv_61 1 1 253 255 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_63 5 1 244_splitncnn_2 246_splitncnn_0 249_splitncnn_0 252_splitncnn_0 255 256
|
||||
Convolution Conv_64 1 1 256 257 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_67 2 1 257 244_splitncnn_1 260 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_16 1 6 260 260_splitncnn_0 260_splitncnn_1 260_splitncnn_2 260_splitncnn_3 260_splitncnn_4 260_splitncnn_5
|
||||
Convolution Conv_68 1 1 260_splitncnn_5 262 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_17 1 4 262 262_splitncnn_0 262_splitncnn_1 262_splitncnn_2 262_splitncnn_3
|
||||
Concat Concat_70 2 1 260_splitncnn_4 262_splitncnn_3 263
|
||||
Convolution Conv_71 1 1 263 265 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_18 1 3 265 265_splitncnn_0 265_splitncnn_1 265_splitncnn_2
|
||||
Concat Concat_73 3 1 260_splitncnn_3 262_splitncnn_2 265_splitncnn_2 266
|
||||
Convolution Conv_74 1 1 266 268 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_19 1 2 268 268_splitncnn_0 268_splitncnn_1
|
||||
Concat Concat_76 4 1 260_splitncnn_2 262_splitncnn_1 265_splitncnn_1 268_splitncnn_1 269
|
||||
Convolution Conv_77 1 1 269 271 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_79 5 1 260_splitncnn_1 262_splitncnn_0 265_splitncnn_0 268_splitncnn_0 271 272
|
||||
Convolution Conv_80 1 1 272 273 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_83 2 1 273 260_splitncnn_0 276 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_20 1 6 276 276_splitncnn_0 276_splitncnn_1 276_splitncnn_2 276_splitncnn_3 276_splitncnn_4 276_splitncnn_5
|
||||
Convolution Conv_84 1 1 276_splitncnn_5 278 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_21 1 4 278 278_splitncnn_0 278_splitncnn_1 278_splitncnn_2 278_splitncnn_3
|
||||
Concat Concat_86 2 1 276_splitncnn_4 278_splitncnn_3 279
|
||||
Convolution Conv_87 1 1 279 281 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_22 1 3 281 281_splitncnn_0 281_splitncnn_1 281_splitncnn_2
|
||||
Concat Concat_89 3 1 276_splitncnn_3 278_splitncnn_2 281_splitncnn_2 282
|
||||
Convolution Conv_90 1 1 282 284 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_23 1 2 284 284_splitncnn_0 284_splitncnn_1
|
||||
Concat Concat_92 4 1 276_splitncnn_2 278_splitncnn_1 281_splitncnn_1 284_splitncnn_1 285
|
||||
Convolution Conv_93 1 1 285 287 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_95 5 1 276_splitncnn_1 278_splitncnn_0 281_splitncnn_0 284_splitncnn_0 287 288
|
||||
Convolution Conv_96 1 1 288 289 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_99 2 1 289 276_splitncnn_0 292 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Eltwise Add_102 2 1 292 244_splitncnn_0 295 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_24 1 7 295 295_splitncnn_0 295_splitncnn_1 295_splitncnn_2 295_splitncnn_3 295_splitncnn_4 295_splitncnn_5 295_splitncnn_6
|
||||
Convolution Conv_103 1 1 295_splitncnn_6 297 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_25 1 4 297 297_splitncnn_0 297_splitncnn_1 297_splitncnn_2 297_splitncnn_3
|
||||
Concat Concat_105 2 1 295_splitncnn_5 297_splitncnn_3 298
|
||||
Convolution Conv_106 1 1 298 300 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_26 1 3 300 300_splitncnn_0 300_splitncnn_1 300_splitncnn_2
|
||||
Concat Concat_108 3 1 295_splitncnn_4 297_splitncnn_2 300_splitncnn_2 301
|
||||
Convolution Conv_109 1 1 301 303 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_27 1 2 303 303_splitncnn_0 303_splitncnn_1
|
||||
Concat Concat_111 4 1 295_splitncnn_3 297_splitncnn_1 300_splitncnn_1 303_splitncnn_1 304
|
||||
Convolution Conv_112 1 1 304 306 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_114 5 1 295_splitncnn_2 297_splitncnn_0 300_splitncnn_0 303_splitncnn_0 306 307
|
||||
Convolution Conv_115 1 1 307 308 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_118 2 1 308 295_splitncnn_1 311 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_28 1 6 311 311_splitncnn_0 311_splitncnn_1 311_splitncnn_2 311_splitncnn_3 311_splitncnn_4 311_splitncnn_5
|
||||
Convolution Conv_119 1 1 311_splitncnn_5 313 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_29 1 4 313 313_splitncnn_0 313_splitncnn_1 313_splitncnn_2 313_splitncnn_3
|
||||
Concat Concat_121 2 1 311_splitncnn_4 313_splitncnn_3 314
|
||||
Convolution Conv_122 1 1 314 316 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_30 1 3 316 316_splitncnn_0 316_splitncnn_1 316_splitncnn_2
|
||||
Concat Concat_124 3 1 311_splitncnn_3 313_splitncnn_2 316_splitncnn_2 317
|
||||
Convolution Conv_125 1 1 317 319 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_31 1 2 319 319_splitncnn_0 319_splitncnn_1
|
||||
Concat Concat_127 4 1 311_splitncnn_2 313_splitncnn_1 316_splitncnn_1 319_splitncnn_1 320
|
||||
Convolution Conv_128 1 1 320 322 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_130 5 1 311_splitncnn_1 313_splitncnn_0 316_splitncnn_0 319_splitncnn_0 322 323
|
||||
Convolution Conv_131 1 1 323 324 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_134 2 1 324 311_splitncnn_0 327 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_32 1 6 327 327_splitncnn_0 327_splitncnn_1 327_splitncnn_2 327_splitncnn_3 327_splitncnn_4 327_splitncnn_5
|
||||
Convolution Conv_135 1 1 327_splitncnn_5 329 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_33 1 4 329 329_splitncnn_0 329_splitncnn_1 329_splitncnn_2 329_splitncnn_3
|
||||
Concat Concat_137 2 1 327_splitncnn_4 329_splitncnn_3 330
|
||||
Convolution Conv_138 1 1 330 332 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_34 1 3 332 332_splitncnn_0 332_splitncnn_1 332_splitncnn_2
|
||||
Concat Concat_140 3 1 327_splitncnn_3 329_splitncnn_2 332_splitncnn_2 333
|
||||
Convolution Conv_141 1 1 333 335 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_35 1 2 335 335_splitncnn_0 335_splitncnn_1
|
||||
Concat Concat_143 4 1 327_splitncnn_2 329_splitncnn_1 332_splitncnn_1 335_splitncnn_1 336
|
||||
Convolution Conv_144 1 1 336 338 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_146 5 1 327_splitncnn_1 329_splitncnn_0 332_splitncnn_0 335_splitncnn_0 338 339
|
||||
Convolution Conv_147 1 1 339 340 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_150 2 1 340 327_splitncnn_0 343 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Eltwise Add_153 2 1 343 295_splitncnn_0 346 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_36 1 7 346 346_splitncnn_0 346_splitncnn_1 346_splitncnn_2 346_splitncnn_3 346_splitncnn_4 346_splitncnn_5 346_splitncnn_6
|
||||
Convolution Conv_154 1 1 346_splitncnn_6 348 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_37 1 4 348 348_splitncnn_0 348_splitncnn_1 348_splitncnn_2 348_splitncnn_3
|
||||
Concat Concat_156 2 1 346_splitncnn_5 348_splitncnn_3 349
|
||||
Convolution Conv_157 1 1 349 351 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_38 1 3 351 351_splitncnn_0 351_splitncnn_1 351_splitncnn_2
|
||||
Concat Concat_159 3 1 346_splitncnn_4 348_splitncnn_2 351_splitncnn_2 352
|
||||
Convolution Conv_160 1 1 352 354 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_39 1 2 354 354_splitncnn_0 354_splitncnn_1
|
||||
Concat Concat_162 4 1 346_splitncnn_3 348_splitncnn_1 351_splitncnn_1 354_splitncnn_1 355
|
||||
Convolution Conv_163 1 1 355 357 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_165 5 1 346_splitncnn_2 348_splitncnn_0 351_splitncnn_0 354_splitncnn_0 357 358
|
||||
Convolution Conv_166 1 1 358 359 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_169 2 1 359 346_splitncnn_1 362 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_40 1 6 362 362_splitncnn_0 362_splitncnn_1 362_splitncnn_2 362_splitncnn_3 362_splitncnn_4 362_splitncnn_5
|
||||
Convolution Conv_170 1 1 362_splitncnn_5 364 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_41 1 4 364 364_splitncnn_0 364_splitncnn_1 364_splitncnn_2 364_splitncnn_3
|
||||
Concat Concat_172 2 1 362_splitncnn_4 364_splitncnn_3 365
|
||||
Convolution Conv_173 1 1 365 367 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_42 1 3 367 367_splitncnn_0 367_splitncnn_1 367_splitncnn_2
|
||||
Concat Concat_175 3 1 362_splitncnn_3 364_splitncnn_2 367_splitncnn_2 368
|
||||
Convolution Conv_176 1 1 368 370 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_43 1 2 370 370_splitncnn_0 370_splitncnn_1
|
||||
Concat Concat_178 4 1 362_splitncnn_2 364_splitncnn_1 367_splitncnn_1 370_splitncnn_1 371
|
||||
Convolution Conv_179 1 1 371 373 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_181 5 1 362_splitncnn_1 364_splitncnn_0 367_splitncnn_0 370_splitncnn_0 373 374
|
||||
Convolution Conv_182 1 1 374 375 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_185 2 1 375 362_splitncnn_0 378 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_44 1 6 378 378_splitncnn_0 378_splitncnn_1 378_splitncnn_2 378_splitncnn_3 378_splitncnn_4 378_splitncnn_5
|
||||
Convolution Conv_186 1 1 378_splitncnn_5 380 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_45 1 4 380 380_splitncnn_0 380_splitncnn_1 380_splitncnn_2 380_splitncnn_3
|
||||
Concat Concat_188 2 1 378_splitncnn_4 380_splitncnn_3 381
|
||||
Convolution Conv_189 1 1 381 383 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_46 1 3 383 383_splitncnn_0 383_splitncnn_1 383_splitncnn_2
|
||||
Concat Concat_191 3 1 378_splitncnn_3 380_splitncnn_2 383_splitncnn_2 384
|
||||
Convolution Conv_192 1 1 384 386 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_47 1 2 386 386_splitncnn_0 386_splitncnn_1
|
||||
Concat Concat_194 4 1 378_splitncnn_2 380_splitncnn_1 383_splitncnn_1 386_splitncnn_1 387
|
||||
Convolution Conv_195 1 1 387 389 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_197 5 1 378_splitncnn_1 380_splitncnn_0 383_splitncnn_0 386_splitncnn_0 389 390
|
||||
Convolution Conv_198 1 1 390 391 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_201 2 1 391 378_splitncnn_0 394 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Eltwise Add_204 2 1 394 346_splitncnn_0 397 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_48 1 7 397 397_splitncnn_0 397_splitncnn_1 397_splitncnn_2 397_splitncnn_3 397_splitncnn_4 397_splitncnn_5 397_splitncnn_6
|
||||
Convolution Conv_205 1 1 397_splitncnn_6 399 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_49 1 4 399 399_splitncnn_0 399_splitncnn_1 399_splitncnn_2 399_splitncnn_3
|
||||
Concat Concat_207 2 1 397_splitncnn_5 399_splitncnn_3 400
|
||||
Convolution Conv_208 1 1 400 402 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_50 1 3 402 402_splitncnn_0 402_splitncnn_1 402_splitncnn_2
|
||||
Concat Concat_210 3 1 397_splitncnn_4 399_splitncnn_2 402_splitncnn_2 403
|
||||
Convolution Conv_211 1 1 403 405 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_51 1 2 405 405_splitncnn_0 405_splitncnn_1
|
||||
Concat Concat_213 4 1 397_splitncnn_3 399_splitncnn_1 402_splitncnn_1 405_splitncnn_1 406
|
||||
Convolution Conv_214 1 1 406 408 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_216 5 1 397_splitncnn_2 399_splitncnn_0 402_splitncnn_0 405_splitncnn_0 408 409
|
||||
Convolution Conv_217 1 1 409 410 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_220 2 1 410 397_splitncnn_1 413 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_52 1 6 413 413_splitncnn_0 413_splitncnn_1 413_splitncnn_2 413_splitncnn_3 413_splitncnn_4 413_splitncnn_5
|
||||
Convolution Conv_221 1 1 413_splitncnn_5 415 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_53 1 4 415 415_splitncnn_0 415_splitncnn_1 415_splitncnn_2 415_splitncnn_3
|
||||
Concat Concat_223 2 1 413_splitncnn_4 415_splitncnn_3 416
|
||||
Convolution Conv_224 1 1 416 418 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_54 1 3 418 418_splitncnn_0 418_splitncnn_1 418_splitncnn_2
|
||||
Concat Concat_226 3 1 413_splitncnn_3 415_splitncnn_2 418_splitncnn_2 419
|
||||
Convolution Conv_227 1 1 419 421 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_55 1 2 421 421_splitncnn_0 421_splitncnn_1
|
||||
Concat Concat_229 4 1 413_splitncnn_2 415_splitncnn_1 418_splitncnn_1 421_splitncnn_1 422
|
||||
Convolution Conv_230 1 1 422 424 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_232 5 1 413_splitncnn_1 415_splitncnn_0 418_splitncnn_0 421_splitncnn_0 424 425
|
||||
Convolution Conv_233 1 1 425 426 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_236 2 1 426 413_splitncnn_0 429 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_56 1 6 429 429_splitncnn_0 429_splitncnn_1 429_splitncnn_2 429_splitncnn_3 429_splitncnn_4 429_splitncnn_5
|
||||
Convolution Conv_237 1 1 429_splitncnn_5 431 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_57 1 4 431 431_splitncnn_0 431_splitncnn_1 431_splitncnn_2 431_splitncnn_3
|
||||
Concat Concat_239 2 1 429_splitncnn_4 431_splitncnn_3 432
|
||||
Convolution Conv_240 1 1 432 434 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_58 1 3 434 434_splitncnn_0 434_splitncnn_1 434_splitncnn_2
|
||||
Concat Concat_242 3 1 429_splitncnn_3 431_splitncnn_2 434_splitncnn_2 435
|
||||
Convolution Conv_243 1 1 435 437 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_59 1 2 437 437_splitncnn_0 437_splitncnn_1
|
||||
Concat Concat_245 4 1 429_splitncnn_2 431_splitncnn_1 434_splitncnn_1 437_splitncnn_1 438
|
||||
Convolution Conv_246 1 1 438 440 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_248 5 1 429_splitncnn_1 431_splitncnn_0 434_splitncnn_0 437_splitncnn_0 440 441
|
||||
Convolution Conv_249 1 1 441 442 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_252 2 1 442 429_splitncnn_0 445 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Eltwise Add_255 2 1 445 397_splitncnn_0 448 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_60 1 7 448 448_splitncnn_0 448_splitncnn_1 448_splitncnn_2 448_splitncnn_3 448_splitncnn_4 448_splitncnn_5 448_splitncnn_6
|
||||
Convolution Conv_256 1 1 448_splitncnn_6 450 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_61 1 4 450 450_splitncnn_0 450_splitncnn_1 450_splitncnn_2 450_splitncnn_3
|
||||
Concat Concat_258 2 1 448_splitncnn_5 450_splitncnn_3 451
|
||||
Convolution Conv_259 1 1 451 453 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_62 1 3 453 453_splitncnn_0 453_splitncnn_1 453_splitncnn_2
|
||||
Concat Concat_261 3 1 448_splitncnn_4 450_splitncnn_2 453_splitncnn_2 454
|
||||
Convolution Conv_262 1 1 454 456 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_63 1 2 456 456_splitncnn_0 456_splitncnn_1
|
||||
Concat Concat_264 4 1 448_splitncnn_3 450_splitncnn_1 453_splitncnn_1 456_splitncnn_1 457
|
||||
Convolution Conv_265 1 1 457 459 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_267 5 1 448_splitncnn_2 450_splitncnn_0 453_splitncnn_0 456_splitncnn_0 459 460
|
||||
Convolution Conv_268 1 1 460 461 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_271 2 1 461 448_splitncnn_1 464 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_64 1 6 464 464_splitncnn_0 464_splitncnn_1 464_splitncnn_2 464_splitncnn_3 464_splitncnn_4 464_splitncnn_5
|
||||
Convolution Conv_272 1 1 464_splitncnn_5 466 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_65 1 4 466 466_splitncnn_0 466_splitncnn_1 466_splitncnn_2 466_splitncnn_3
|
||||
Concat Concat_274 2 1 464_splitncnn_4 466_splitncnn_3 467
|
||||
Convolution Conv_275 1 1 467 469 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_66 1 3 469 469_splitncnn_0 469_splitncnn_1 469_splitncnn_2
|
||||
Concat Concat_277 3 1 464_splitncnn_3 466_splitncnn_2 469_splitncnn_2 470
|
||||
Convolution Conv_278 1 1 470 472 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_67 1 2 472 472_splitncnn_0 472_splitncnn_1
|
||||
Concat Concat_280 4 1 464_splitncnn_2 466_splitncnn_1 469_splitncnn_1 472_splitncnn_1 473
|
||||
Convolution Conv_281 1 1 473 475 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_283 5 1 464_splitncnn_1 466_splitncnn_0 469_splitncnn_0 472_splitncnn_0 475 476
|
||||
Convolution Conv_284 1 1 476 477 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_287 2 1 477 464_splitncnn_0 480 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Split splitncnn_68 1 6 480 480_splitncnn_0 480_splitncnn_1 480_splitncnn_2 480_splitncnn_3 480_splitncnn_4 480_splitncnn_5
|
||||
Convolution Conv_288 1 1 480_splitncnn_5 482 0=32 1=3 4=1 5=1 6=18432 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_69 1 4 482 482_splitncnn_0 482_splitncnn_1 482_splitncnn_2 482_splitncnn_3
|
||||
Concat Concat_290 2 1 480_splitncnn_4 482_splitncnn_3 483
|
||||
Convolution Conv_291 1 1 483 485 0=32 1=3 4=1 5=1 6=27648 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_70 1 3 485 485_splitncnn_0 485_splitncnn_1 485_splitncnn_2
|
||||
Concat Concat_293 3 1 480_splitncnn_3 482_splitncnn_2 485_splitncnn_2 486
|
||||
Convolution Conv_294 1 1 486 488 0=32 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Split splitncnn_71 1 2 488 488_splitncnn_0 488_splitncnn_1
|
||||
Concat Concat_296 4 1 480_splitncnn_2 482_splitncnn_1 485_splitncnn_1 488_splitncnn_1 489
|
||||
Convolution Conv_297 1 1 489 491 0=32 1=3 4=1 5=1 6=46080 9=2 -23310=1,2.000000e-01
|
||||
Concat Concat_299 5 1 480_splitncnn_1 482_splitncnn_0 485_splitncnn_0 488_splitncnn_0 491 492
|
||||
Convolution Conv_300 1 1 492 493 0=64 1=3 4=1 5=1 6=110592
|
||||
Eltwise Add_303 2 1 493 480_splitncnn_0 496 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Eltwise Add_306 2 1 496 448_splitncnn_0 499 0=1 -23301=2,2.000000e-01,1.000000e+00
|
||||
Convolution Conv_307 1 1 499 500 0=64 1=3 4=1 5=1 6=36864
|
||||
BinaryOp Add_308 2 1 193_splitncnn_0 500 501
|
||||
Interp Resize_310 1 1 501 506 0=1 1=2.000000e+00 2=2.000000e+00
|
||||
Convolution Conv_311 1 1 506 508 0=64 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Interp Resize_314 1 1 508 513 0=1 1=2.000000e+00 2=2.000000e+00
|
||||
Convolution Conv_315 1 1 513 515 0=64 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Convolution Conv_317 1 1 515 517 0=64 1=3 4=1 5=1 6=36864 9=2 -23310=1,2.000000e-01
|
||||
Convolution Conv_319 1 1 517 output 0=3 1=3 4=1 5=1 6=1728
|
||||
Binary file not shown.
File diff suppressed because it is too large
Load Diff
Binary file not shown.
@@ -1,15 +0,0 @@
|
||||
import edi
|
||||
import numpy as np
|
||||
import argparse
|
||||
|
||||
ap = argparse.ArgumentParser( description='Testing for edi. NOTE: No error catching!' )
|
||||
ap.add_argument( 'inputfile', help='Input file for upscaling' )
|
||||
ap.add_argument( 'outputfile', help='Output file' )
|
||||
ap.add_argument( '-S', '--scalefactor', help='Scale factor' )
|
||||
ap.add_argument( '-a', '--sampling', help='Sampling window size. The bigger, the blurrier. Best >= 4')
|
||||
ap.set_defaults( sampling=4 )
|
||||
ap.set_defaults( scalefactor=2 )
|
||||
|
||||
args = ap.parse_args()
|
||||
|
||||
print( edi.EDI_predict( np.load( args.inputfile, allow_pickle=True ), args.sampling, args.scalefactor ) )
|
||||
@@ -1,9 +0,0 @@
|
||||
"""
|
||||
* SimpleMediaUpscalerLite - pluginDownloader.py
|
||||
*
|
||||
* Created by Janis Hutz 05/31/2023, Licensed under the GPL V3 License
|
||||
* https://janishutz.com, development@janishutz.com
|
||||
*
|
||||
*
|
||||
"""
|
||||
|
||||
64
bin/probe.py
64
bin/probe.py
@@ -1,64 +0,0 @@
|
||||
"""
|
||||
This file here was created from multiple parts of ffmpeg-python
|
||||
"""
|
||||
|
||||
import json
|
||||
import subprocess
|
||||
import sys
|
||||
|
||||
try:
|
||||
from collections.abc import Iterable
|
||||
except ImportError:
|
||||
from collections import Iterable
|
||||
|
||||
def convert_kwargs_to_cmd_line_args(kwargs):
|
||||
"""Helper function to build command line arguments out of dict."""
|
||||
args = []
|
||||
for k in sorted(kwargs.keys()):
|
||||
v = kwargs[k]
|
||||
if isinstance(v, Iterable) and not isinstance(v, str):
|
||||
for value in v:
|
||||
args.append('-{}'.format(k))
|
||||
if value is not None:
|
||||
args.append('{}'.format(value))
|
||||
continue
|
||||
args.append('-{}'.format(k))
|
||||
if v is not None:
|
||||
args.append('{}'.format(v))
|
||||
return args
|
||||
|
||||
class Error(Exception):
|
||||
def __init__(self, cmd, stdout, stderr):
|
||||
super(Error, self).__init__(
|
||||
'{} error (see stderr output for detail)'.format(cmd)
|
||||
)
|
||||
self.stdout = stdout
|
||||
self.stderr = stderr
|
||||
|
||||
def probe(filename, cmd='ffprobe', timeout=None, **kwargs):
|
||||
"""Run ffprobe on the specified file and return a JSON representation of the output.
|
||||
|
||||
Raises:
|
||||
:class:`ffmpeg.Error`: if ffprobe returns a non-zero exit code,
|
||||
an :class:`Error` is returned with a generic error message.
|
||||
The stderr output can be retrieved by accessing the
|
||||
``stderr`` property of the exception.
|
||||
"""
|
||||
args = [cmd, '-show_format', '-show_streams', '-of', 'json']
|
||||
args += convert_kwargs_to_cmd_line_args(kwargs)
|
||||
args += [filename]
|
||||
|
||||
if ( sys.platform == 'win32' ):
|
||||
p = subprocess.Popen(args, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True)
|
||||
else:
|
||||
p = subprocess.Popen(args, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
|
||||
communicate_kwargs = {}
|
||||
if timeout is not None:
|
||||
communicate_kwargs['timeout'] = timeout
|
||||
out, err = p.communicate(**communicate_kwargs)
|
||||
if p.returncode != 0:
|
||||
raise Error('ffprobe', out, err)
|
||||
return json.loads(out.decode('utf-8'))
|
||||
|
||||
|
||||
__all__ = ['probe']
|
||||
@@ -1,5 +0,0 @@
|
||||
[PathSettings]
|
||||
defaultOutputPath = $HOME/FSRSimpleMediaUpscalerLite/
|
||||
|
||||
[DevSettings]
|
||||
loggerReqLevel = DEBUG
|
||||
@@ -1,3 +0,0 @@
|
||||
{
|
||||
"fsr": { "displayName":"AMD FidelityFX Super Resolution" }
|
||||
}
|
||||
154
smuL-cli.py
154
smuL-cli.py
@@ -1,154 +0,0 @@
|
||||
"""
|
||||
* SimpleMediaUpscalerLite - fsrSimpleMediaUpscalerLite-cli.py
|
||||
*
|
||||
* Created by Janis Hutz 03/15/2023, Licensed under the GPL V3 License
|
||||
* https://janishutz.com, development@janishutz.com
|
||||
*
|
||||
*
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import bin.handler
|
||||
import os
|
||||
import multiprocessing
|
||||
import json
|
||||
|
||||
engineList = os.listdir( 'bin/engines' );
|
||||
counter = 0;
|
||||
for element in engineList:
|
||||
if ( element == '__pycache__' ):
|
||||
engineList.pop( counter );
|
||||
counter += 1;
|
||||
|
||||
engineInfo = {}
|
||||
|
||||
for engine in engineList:
|
||||
engineInfo[ engine ] = json.load( open( 'bin/engines/' + engine + '/config.json' ) )
|
||||
|
||||
allowedFiletypes = [ 'png', 'jpg' ];
|
||||
|
||||
def performChecks ( args, ap ):
|
||||
if ( args.details == None or args.details == '' ):
|
||||
if ( not args.printengines ):
|
||||
if ( not args.version ):
|
||||
# Check if input and output file arguments are available
|
||||
if ( args.inputfile == None or args.inputfile == '' ):
|
||||
print( '\n\n ==> ERROR: Input file required! <==\n\n' )
|
||||
ap.print_usage();
|
||||
return False
|
||||
|
||||
output = args.outputfile;
|
||||
if ( args.outputfile == None or args.outputfile == '' ):
|
||||
output = args.inputfile[ :len( args.inputfile ) - 4 ] + '_upscaled' + args.inputfile[ len( args.inputfile ) - 4: ]
|
||||
|
||||
# check if output file exists and if, prompt user if it should be overwritten and remove if, if yes
|
||||
if ( os.path.exists( output ) ):
|
||||
doReplace = input( '--> File already exists. Do you want to replace it? (Y/n) ' ).lower()
|
||||
if ( doReplace == 'y' or doReplace == '' ):
|
||||
os.remove( output );
|
||||
else:
|
||||
print( '\n==> Refusing to Upscale video. Please delete the file or specify another filepath! <==' )
|
||||
return False
|
||||
|
||||
# check if engine argument is valid
|
||||
try:
|
||||
engineInfo[ args.engine.lower() ]
|
||||
except KeyError:
|
||||
print( '\n==> ERROR: Engine not available. Ensure you have specified a valid engine. Possible engines: ' )
|
||||
for entry in engineList:
|
||||
print( ' --> ' + entry )
|
||||
return False
|
||||
|
||||
# Check scalefactor argument and also verify that engine supports upscaling
|
||||
if ( args.scalefactor != None and args.scalefactor != 0 ):
|
||||
if ( int( args.scalefactor ) > 4 and int( args.scalefactor ) < -4 ):
|
||||
print( '\n==> ERROR: Invalid scale factor. Value has to be an integer between -4 and 4 (option -s)' )
|
||||
return False
|
||||
else:
|
||||
if ( not 'upscaling' in engineInfo[ args.engine ][ 'supports' ] ):
|
||||
print( '\n==> ERROR: This engine does NOT support upscaling' )
|
||||
return False
|
||||
|
||||
# Check sharpening argument and also verify that engine supports it
|
||||
if ( args.sharpening != None and args.sharpening != 0 ):
|
||||
if ( float( args.sharpening ) >= 1.0 or float( args.sharpening ) <= 0.0 ):
|
||||
print( '\n==> ERROR: Invalid value for sharpening. Value has to be between 0 and 1' )
|
||||
return False
|
||||
else:
|
||||
if ( not 'sharpening' in engineInfo[ args.engine ][ 'supports' ] ):
|
||||
print( '\n==> ERROR: This engine does NOT support sharpening' )
|
||||
return False
|
||||
|
||||
# check if scalefactor and / or sharpening is available
|
||||
if ( ( args.scalefactor == 0 or args.scalefactor == None ) and ( args.sharpening == 0 or args.sharpening == None ) ):
|
||||
print( '\n==> ERROR: Either scalefactor or sharpening argument required!' )
|
||||
return False
|
||||
|
||||
# Check if filetype argument is valid
|
||||
if ( not args.filetype in allowedFiletypes ):
|
||||
print( '\n==> ERROR: Unknown filetype for temp files. Can be png or jpg' )
|
||||
return False
|
||||
|
||||
# Check if mode of engine is valid
|
||||
if ( args.mode != None ):
|
||||
try:
|
||||
engineInfo[ args.engine.lower() ][ 'cliModeOptions' ][ args.mode.lower() ]
|
||||
except KeyError:
|
||||
print( '\n==> ERROR: The specified mode is not supported by this engine. Options:' )
|
||||
for option in engineInfo[ args.engine ][ 'cliModeOptions' ]:
|
||||
print( ' --> ' + engineInfo[ args.engine ][ 'cliModeOptions' ][ option ][ 'displayName' ] + ' (' + option + ')' )
|
||||
return False
|
||||
|
||||
return True
|
||||
else:
|
||||
print( '\n\n==> You are running Version 1.1.0 of ImageVideoScaler-CLI <==\n' )
|
||||
else:
|
||||
print( '\n\n==> Available engines <==\n' )
|
||||
for entry in engineList:
|
||||
print( ' --> ' + entry )
|
||||
print( '\n\n' )
|
||||
else:
|
||||
print( '\n\n ==> INFOS about ' + engineInfo[ args.details.lower() ][ 'displayName' ] + '\n' )
|
||||
print( ' --> Engine cli option is: ' + engineInfo[ args.details ][ 'abbr' ].lower() )
|
||||
print( ' --> CLI mode options are: ' )
|
||||
for mode in engineInfo[ args.details ][ 'cliModeOptions' ]:
|
||||
print( ' -> ' + engineInfo[ args.details ][ 'cliModeOptions' ][ mode ][ 'displayName' ] + ':' )
|
||||
print( ' > CLI name: ' + mode )
|
||||
print( ' > Is the default: ' + str( engineInfo[ args.details ][ 'cliModeOptions' ][ mode ][ 'default' ] ) )
|
||||
print( '\n\n' )
|
||||
|
||||
if __name__ == '__main__':
|
||||
ap = argparse.ArgumentParser( description='SimpleMediaUpscalerLite - CLI, a CLI application to upscale videos and images using different upscaling engines.' )
|
||||
ap.add_argument( '-i', '--inputfile', help='File path for the video / image to be upscaled' )
|
||||
ap.add_argument( '-o', '--outputfile', help='Output file path for the video / image that was upscaled' )
|
||||
ap.add_argument( '-s', '--scalefactor', help='Scale factor for the video / image. Can be a integer from -4 to 4' )
|
||||
ap.add_argument( '-S', '--sharpening', help='Sharpening factor (between 0 and 1 whereas 0 means no sharpening, 1 the most sharpening. Recommendation: Do not exceed 0.25, as it often looks bad)' )
|
||||
ap.add_argument( '-T', '--threads', help='Thread count to use. Cannot exceed CPU thread count. Scaling non-linear (using 2 threads is not exactly 2x the speed of 1 thread). Scales well with FSR, barely with Real-ESRGAN, as it uses mostly the GPU to upscale' )
|
||||
ap.add_argument( '-E', '--engine', help='Upscaling engine. By default can be fsr or ss. Use the -p option to see all installed engines' )
|
||||
ap.add_argument( '-M', '--mode', help='Specify a special mode for a specific engine. Might not be available in every engine. Use the -d option to find out more' )
|
||||
ap.add_argument( '-F', '--filetype', help='Change the file type of the temporary image files. Supports png, jpg. Video quality: png > jpg. PNG is default, if not specified.' )
|
||||
ap.add_argument( '-d', '--details', help='Get details on usage of a particular engine and exit. Reads the config.json file of that engine and displays it in a HR manner' )
|
||||
ap.add_argument( '-p', '--printengines', help='Print all engines and exit', action='store_true' )
|
||||
ap.add_argument( '-v', '--version', help='Print version and exit', action='store_true' )
|
||||
ap.set_defaults( scalefactor = 0, sharpening = 0, threads = 4, engine = 'ffc', filetype = 'png' )
|
||||
args = ap.parse_args()
|
||||
|
||||
handler = bin.handler.Handler()
|
||||
|
||||
multiprocessing.freeze_support();
|
||||
|
||||
if ( performChecks( args, ap ) ):
|
||||
output = args.outputfile;
|
||||
if ( args.outputfile == None or args.outputfile == '' ):
|
||||
output = args.inputfile[ :len( args.inputfile ) - 4 ] + '_upscaled' + args.inputfile[ len( args.inputfile ) - 4: ]
|
||||
|
||||
mode = 'fsr'
|
||||
if ( args.mode != None ):
|
||||
mode = args.mode
|
||||
else:
|
||||
for option in engineInfo[ args.engine ][ 'cliModeOptions' ]:
|
||||
if ( engineInfo[ args.engine ][ 'cliModeOptions' ][ option ][ 'default' ] ):
|
||||
mode = option
|
||||
break
|
||||
if ( handler.handler( args.inputfile, args.scalefactor, output, args.sharpening, args.filetype, args.engine, mode, args.threads ) ):
|
||||
print( '\n\n---------------------------------------------------------------------------------\n\nDONE \n\n\n\nSimpleMediaUpscalerLite V1.1.0\n\nCopyright 2023 SimpleMediaUpscalerLite contributors\nThis application comes with absolutely no warranty to the extent permitted by applicable law\n\n\n\nOutput was written to ' + output + '\n\n\n' )
|
||||
@@ -1,50 +0,0 @@
|
||||
# -*- mode: python ; coding: utf-8 -*-
|
||||
|
||||
|
||||
block_cipher = None
|
||||
|
||||
|
||||
a = Analysis(
|
||||
['smuL-cli.py'],
|
||||
pathex=[],
|
||||
binaries=[],
|
||||
datas=[],
|
||||
hiddenimports=[],
|
||||
hookspath=[],
|
||||
hooksconfig={},
|
||||
runtime_hooks=[],
|
||||
excludes=[],
|
||||
win_no_prefer_redirects=False,
|
||||
win_private_assemblies=False,
|
||||
cipher=block_cipher,
|
||||
noarchive=False,
|
||||
)
|
||||
pyz = PYZ(a.pure, a.zipped_data, cipher=block_cipher)
|
||||
|
||||
exe = EXE(
|
||||
pyz,
|
||||
a.scripts,
|
||||
[],
|
||||
exclude_binaries=True,
|
||||
name='smuL-cli',
|
||||
debug=False,
|
||||
bootloader_ignore_signals=False,
|
||||
strip=False,
|
||||
upx=True,
|
||||
console=True,
|
||||
disable_windowed_traceback=False,
|
||||
argv_emulation=False,
|
||||
target_arch=None,
|
||||
codesign_identity=None,
|
||||
entitlements_file=None,
|
||||
)
|
||||
coll = COLLECT(
|
||||
exe,
|
||||
a.binaries,
|
||||
a.zipfiles,
|
||||
a.datas,
|
||||
strip=False,
|
||||
upx=True,
|
||||
upx_exclude=[],
|
||||
name='smuL-cli',
|
||||
)
|
||||
Reference in New Issue
Block a user