added sumbmodules

This commit is contained in:
leno3003 2022-03-30 15:05:22 +02:00
parent 774932a5b0
commit 5267017f7d
2 changed files with 81 additions and 49 deletions

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4
Output image format
4
Which GPU indexes to choose?
Face type
Max number of faces from image
Image size
Jpeg quality
Write debug images to aligned_debug?
Which GPU indexes to choose?
Face type
Image size
Jpeg quality
Which GPU indexes to choose?
Autobackup every N hour
Write preview history
Flip SRC faces randomly
Flip DST faces randomly
Batch_size
Eyes and mouth priority
Uniform yaw distribution of samples
Blur out mask
Place models and optimizer on GPU
Use AdaBelief optimizer?
Use learning rate dropout
Enable random warp of samples
Random hue/saturation/light intensity
GAN power
Face style power
Background style power
Color transfer for src faceset
Enable gradient clipping
Enable pretraining mode
Which GPU indexes to choose?
Use interactive merger?
Number of workers?
Use saved session?
Bitrate of output file in MB/s

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import pickle import pickle
dictionary = { dictionary = {
'4' : '\n',
'Output image format':'png', 'Output image format':'png',
'Override' : '0', 'Which GPU indexes to choose?': '0',
'Face type': 'wf',
'Max number of faces from image' : '1',
'Image size' : '512',
'Jpeg quality' : '90',
'Write debug images to aligned_debug?': 'False',
'Autobackup every N hour':'2',
'Write preview history' : 'False',
'Flip SRC faces randomly':'False',
'Flip DST faces randomly':'False',
'Batch_size': '4',
'Eyes and mouth priority':'False',
'Uniform yaw distribution of samples':'True',
'Blur out mask':'False',
'Place models and optimizer on GPU' : 'True',
'Use AdaBelief optimizer?' : 'True',
'Use learning rate dropout' : 'False',
'Enable random warp of samples' : 'True',
'Random hue/saturation/light intensity' : '0.0',
'GAN power' : '0.0',
'Face style power' : '0.0',
'Background style power': '0.0',
'Color transfer for src faceset' : 'lct',
'Enable gradient clipping': 'False', 'Enable gradient clipping': 'False',
' Use saved session? ' : 'False',
'Enable pretraining mode' : 'False', 'Enable pretraining mode' : 'False',
' Press enter in 2 seconds to override model settings. ' : '\n', 'Use interactive merger?':'False',
'[0] Which GPU indexes to choose? : ' : '0', 'Number of workers?':'8',
'[wf] Face type ( f/wf/head ?:help ) : ' : 'wf', 'Use saved session?':'False',
'[0] Max number of faces from image ( ?:help ) : ' : '0', 'Bitrate of output file in MB/s' : '16',
'[512] Image size ( 256-2048 ?:help ) : ' : '512', 'Choose erode mask modifier',
'[90] Jpeg quality ( 1-100 ?:help ) : ' : '90', 'Choose blur mask modifier',
'[n] Write debug images to aligned_debug? ( y/n ) : ' : 'False', 'Choose motion blur power' : '0',
'[y] Continue extraction? ( y/n ?:help ) : ' : 'True', 'Choose output face scale modifier' : '0',
'[2] Autobackup every N hour ( 0..24 ?:help ) : ' : '2', 'Choose super resolution power' : '0',
'[n] Write preview history ( y/n ?:help ) : ' : 'False', 'Choose image degrade by denoise power' : '0',
'[83000] Target iteration : ' : '\n', 'Choose image degrade by bicubic rescale power' : '0',
'[n] Flip SRC faces randomly ( y/n ?:help ) : ' : 'False', 'Degrade color power of final image' : '0',
'[n] Flip DST faces randomly ( y/n ?:help ) : ' : 'False', 'Color transfer to predicted face' : 'rct',
'[4] Batch_size ( ?:help ) : ' : '4',
'[n] Eyes and mouth priority ( y/n ?:help ) : ' : 'False',
'[y] Uniform yaw distribution of samples ( y/n ?:help ) : ' : 'True',
'[n] Blur out mask ( y/n ?:help ) : ' : 'False',
'[y] Place models and optimizer on GPU ( y/n ?:help ) : ' : 'True',
'[y] Use AdaBelief optimizer? ( y/n ?:help ) : ' : 'True',
'[n] Use learning rate dropout ( n/y/cpu ?:help ) : ' : 'n',
'[y] Enable random warp of samples ( y/n ?:help ) : ' : 'True',
'[0.0] Random hue/saturation/light intensity ( 0.0 .. 0.3 ?:help ) : ' : '0.0',
'[0.0] GAN power ( 0.0 .. 5.0 ?:help ) : ' : '0.0',
'[0.0] Face style power ( 0.0..100.0 ?:help ) : ' : '0.0',
'[0.0] Background style power ( 0.0..100.0 ?:help ) : ' : '0.0',
'[lct] Color transfer for src faceset ( none/rct/lct/mkl/idt/sot ?:help ) : ' : 'lct',
'[n] Use interactive merger? ( y/n ) : ' : 'n',
'[1] 2 : ' : '1',
'[1] 3 : ' : '4',
'[0] Choose erode mask modifier ( -400..400 ) : ' : '100',
'[0] Choose blur mask modifier ( 0..400 ) : ' : '150',
'[0] Choose motion blur power ( 0..100 ) : ' : '0',
'[0] Choose output face scale modifier ( -50..50 ) : ' : '0',
'[0] 1 ( ?:help ) : ' : '0',
'[0] Choose super resolution power ( 0..100 ?:help ) : ' : '0',
'[0] Choose image degrade by denoise power ( 0..500 ) : ' : '0',
'[0] Choose image degrade by bicubic rescale power ( 0..100 ) : ' : '0',
'[0] Degrade color power of final image ( 0..100 ) : ' : '0',
'Color transfer to predicted face ( rct/lct/mkl/mkl-m/idt/idt-m/sot-m/mix-m ) : ' : 'rct',
'[8] Number of workers? ( 1-8 ?:help ) : ' : '8',
'[16] Bitrate of output file in MB/s : ' : '16',
} }
with open('/home/deepfake/interact_dict.pkl', 'wb') as handle: with open('/home/deepfake/interact_dict.pkl', 'wb') as handle:
pickle.dump(dictionary, handle, protocol=4) pickle.dump(dictionary, handle, protocol=4)
with open('/home/deepfake/interact_dict.pkl', 'rb') as handle: with open('/home/deepfake/interact_dict.pkl', 'rb') as handle:
d = pickle.load(handle) d = pickle.load(handle)
s = "Use saved"
res = dict(filter(lambda item: s in item[0], d.items()))
print(list(res.values())[0]) print(d['Color transfer to predicted face'])