Here's the crash report, let me know the reason plz
also, I selected using cpu, what should I do if I wanna change to gpu?
Code: Select all
02/23/2020 20:34:17 MainProcess _training_0 _base __init__ DEBUG training_opts: {'alignments': {'a': '/Users/holysaya/Documents/faceswap/B_face/alignments.fsa', 'b': '/Users/holysaya/Documents/faceswap/A_face/alignments.fsa'}, 'preview_scaling': 0.5, 'warp_to_landmarks': False, 'augment_color': True, 'no_flip': False, 'pingpong': False, 'snapshot_interval': 25000, 'training_size': 256, 'no_logs': False, 'coverage_ratio': 0.625, 'mask_type': None, 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'penalized_mask_loss': False}
02/23/2020 20:34:17 MainProcess _training_0 _base multiple_models_in_folder DEBUG model_files: ['original_decoder_B.h5', 'original_decoder_A.h5', 'original_encoder.h5'], retval: False
02/23/2020 20:34:17 MainProcess _training_0 original add_networks DEBUG Adding networks
02/23/2020 20:34:17 MainProcess _training_0 module_wrapper _tfmw_add_deprecation_warning DEBUG From /Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:74: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.\n
02/23/2020 20:34:17 MainProcess _training_0 module_wrapper _tfmw_add_deprecation_warning DEBUG From /Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:517: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.\n
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks upscale DEBUG inp: Tensor("input_1:0", shape=(?, 8, 8, 512), dtype=float32), filters: 256, kernel_size: 3, use_instance_norm: False, kwargs: {})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks get_name DEBUG Generating block name: upscale_8_0
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Set default kernel_initializer to: <keras.initializers.VarianceScaling object at 0x14475d2b0>
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv2d DEBUG inp: Tensor("input_1:0", shape=(?, 8, 8, 512), dtype=float32), filters: 1024, kernel_size: 3, strides: (1, 1), padding: same, kwargs: {'name': 'upscale_8_0_conv2d', 'kernel_initializer': <keras.initializers.VarianceScaling object at 0x14475d2b0>})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Using model specified initializer: <keras.initializers.VarianceScaling object at 0x14475d2b0>
02/23/2020 20:34:17 MainProcess _training_0 module_wrapper _tfmw_add_deprecation_warning DEBUG From /Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:4138: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.\n
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks upscale DEBUG inp: Tensor("upscale_8_0_pixelshuffler/Reshape_1:0", shape=(?, 16, 16, 256), dtype=float32), filters: 128, kernel_size: 3, use_instance_norm: False, kwargs: {})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks get_name DEBUG Generating block name: upscale_16_0
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Set default kernel_initializer to: <keras.initializers.VarianceScaling object at 0x14471ef60>
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv2d DEBUG inp: Tensor("upscale_8_0_pixelshuffler/Reshape_1:0", shape=(?, 16, 16, 256), dtype=float32), filters: 512, kernel_size: 3, strides: (1, 1), padding: same, kwargs: {'name': 'upscale_16_0_conv2d', 'kernel_initializer': <keras.initializers.VarianceScaling object at 0x14471ef60>})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Using model specified initializer: <keras.initializers.VarianceScaling object at 0x14471ef60>
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks upscale DEBUG inp: Tensor("upscale_16_0_pixelshuffler/Reshape_1:0", shape=(?, 32, 32, 128), dtype=float32), filters: 64, kernel_size: 3, use_instance_norm: False, kwargs: {})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks get_name DEBUG Generating block name: upscale_32_0
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Set default kernel_initializer to: <keras.initializers.VarianceScaling object at 0x14478aba8>
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv2d DEBUG inp: Tensor("upscale_16_0_pixelshuffler/Reshape_1:0", shape=(?, 32, 32, 128), dtype=float32), filters: 256, kernel_size: 3, strides: (1, 1), padding: same, kwargs: {'name': 'upscale_32_0_conv2d', 'kernel_initializer': <keras.initializers.VarianceScaling object at 0x14478aba8>})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Using model specified initializer: <keras.initializers.VarianceScaling object at 0x14478aba8>
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv2d DEBUG inp: Tensor("upscale_32_0_pixelshuffler/Reshape_1:0", shape=(?, 64, 64, 64), dtype=float32), filters: 3, kernel_size: 5, strides: (1, 1), padding: same, kwargs: {'activation': 'sigmoid', 'name': 'face_out'})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Set default kernel_initializer to: <keras.initializers.VarianceScaling object at 0x144799c88>
02/23/2020 20:34:17 MainProcess _training_0 _base add_network DEBUG network_type: 'decoder', side: 'a', network: '<keras.engine.training.Model object at 0x1447a0f98>', is_output: True
02/23/2020 20:34:17 MainProcess _training_0 _base name DEBUG model name: 'original'
02/23/2020 20:34:17 MainProcess _training_0 _base add_network DEBUG name: 'decoder_a', filename: 'original_decoder_A.h5'
02/23/2020 20:34:17 MainProcess _training_0 _base __init__ DEBUG Initializing NNMeta: (filename: '/Users/holysaya/Documents/faceswap/model/original_decoder_A.h5', network_type: 'decoder', side: 'a', network: <keras.engine.training.Model object at 0x1447a0f98>, is_output: True
02/23/2020 20:34:17 MainProcess _training_0 module_wrapper _tfmw_add_deprecation_warning DEBUG From /Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:174: The name tf.get_default_session is deprecated. Please use tf.compat.v1.get_default_session instead.\n
02/23/2020 20:34:17 MainProcess _training_0 module_wrapper _tfmw_add_deprecation_warning DEBUG From /Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:181: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.\n
02/23/2020 20:34:17 MainProcess _training_0 module_wrapper _tfmw_add_deprecation_warning DEBUG From /Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:186: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.\n
02/23/2020 20:34:17 MainProcess _training_0 module_wrapper _tfmw_add_deprecation_warning DEBUG From /Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:190: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.\n
02/23/2020 20:34:17 MainProcess _training_0 module_wrapper _tfmw_add_deprecation_warning DEBUG From /Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:199: The name tf.is_variable_initialized is deprecated. Please use tf.compat.v1.is_variable_initialized instead.\n
02/23/2020 20:34:17 MainProcess _training_0 module_wrapper _tfmw_add_deprecation_warning DEBUG From /Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:206: The name tf.variables_initializer is deprecated. Please use tf.compat.v1.variables_initializer instead.\n
02/23/2020 20:34:17 MainProcess _training_0 _base __init__ DEBUG Initialized NNMeta
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks upscale DEBUG inp: Tensor("input_2:0", shape=(?, 8, 8, 512), dtype=float32), filters: 256, kernel_size: 3, use_instance_norm: False, kwargs: {})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks get_name DEBUG Generating block name: upscale_8_1
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Set default kernel_initializer to: <keras.initializers.VarianceScaling object at 0x12cb760b8>
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv2d DEBUG inp: Tensor("input_2:0", shape=(?, 8, 8, 512), dtype=float32), filters: 1024, kernel_size: 3, strides: (1, 1), padding: same, kwargs: {'name': 'upscale_8_1_conv2d', 'kernel_initializer': <keras.initializers.VarianceScaling object at 0x12cb760b8>})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Using model specified initializer: <keras.initializers.VarianceScaling object at 0x12cb760b8>
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks upscale DEBUG inp: Tensor("upscale_8_1_pixelshuffler/Reshape_1:0", shape=(?, 16, 16, 256), dtype=float32), filters: 128, kernel_size: 3, use_instance_norm: False, kwargs: {})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks get_name DEBUG Generating block name: upscale_16_1
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Set default kernel_initializer to: <keras.initializers.VarianceScaling object at 0x1447c89e8>
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv2d DEBUG inp: Tensor("upscale_8_1_pixelshuffler/Reshape_1:0", shape=(?, 16, 16, 256), dtype=float32), filters: 512, kernel_size: 3, strides: (1, 1), padding: same, kwargs: {'name': 'upscale_16_1_conv2d', 'kernel_initializer': <keras.initializers.VarianceScaling object at 0x1447c89e8>})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Using model specified initializer: <keras.initializers.VarianceScaling object at 0x1447c89e8>
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks upscale DEBUG inp: Tensor("upscale_16_1_pixelshuffler/Reshape_1:0", shape=(?, 32, 32, 128), dtype=float32), filters: 64, kernel_size: 3, use_instance_norm: False, kwargs: {})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks get_name DEBUG Generating block name: upscale_32_1
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Set default kernel_initializer to: <keras.initializers.VarianceScaling object at 0x147724ac8>
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv2d DEBUG inp: Tensor("upscale_16_1_pixelshuffler/Reshape_1:0", shape=(?, 32, 32, 128), dtype=float32), filters: 256, kernel_size: 3, strides: (1, 1), padding: same, kwargs: {'name': 'upscale_32_1_conv2d', 'kernel_initializer': <keras.initializers.VarianceScaling object at 0x147724ac8>})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Using model specified initializer: <keras.initializers.VarianceScaling object at 0x147724ac8>
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv2d DEBUG inp: Tensor("upscale_32_1_pixelshuffler/Reshape_1:0", shape=(?, 64, 64, 64), dtype=float32), filters: 3, kernel_size: 5, strides: (1, 1), padding: same, kwargs: {'activation': 'sigmoid', 'name': 'face_out'})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Set default kernel_initializer to: <keras.initializers.VarianceScaling object at 0x144755ba8>
02/23/2020 20:34:17 MainProcess _training_0 _base add_network DEBUG network_type: 'decoder', side: 'b', network: '<keras.engine.training.Model object at 0x147737e80>', is_output: True
02/23/2020 20:34:17 MainProcess _training_0 _base name DEBUG model name: 'original'
02/23/2020 20:34:17 MainProcess _training_0 _base add_network DEBUG name: 'decoder_b', filename: 'original_decoder_B.h5'
02/23/2020 20:34:17 MainProcess _training_0 _base __init__ DEBUG Initializing NNMeta: (filename: '/Users/holysaya/Documents/faceswap/model/original_decoder_B.h5', network_type: 'decoder', side: 'b', network: <keras.engine.training.Model object at 0x147737e80>, is_output: True
02/23/2020 20:34:17 MainProcess _training_0 _base __init__ DEBUG Initialized NNMeta
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv DEBUG inp: Tensor("input_3:0", shape=(?, 64, 64, 3), dtype=float32), filters: 128, kernel_size: 5, strides: 2, use_instance_norm: False, kwargs: {})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks get_name DEBUG Generating block name: conv_64_0
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv2d DEBUG inp: Tensor("input_3:0", shape=(?, 64, 64, 3), dtype=float32), filters: 128, kernel_size: 5, strides: 2, padding: same, kwargs: {'name': 'conv_64_0_conv2d'})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Set default kernel_initializer to: <keras.initializers.VarianceScaling object at 0x147744710>
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv DEBUG inp: Tensor("conv_64_0_leakyrelu/LeakyRelu:0", shape=(?, 32, 32, 128), dtype=float32), filters: 256, kernel_size: 5, strides: 2, use_instance_norm: False, kwargs: {})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks get_name DEBUG Generating block name: conv_32_0
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv2d DEBUG inp: Tensor("conv_64_0_leakyrelu/LeakyRelu:0", shape=(?, 32, 32, 128), dtype=float32), filters: 256, kernel_size: 5, strides: 2, padding: same, kwargs: {'name': 'conv_32_0_conv2d'})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Set default kernel_initializer to: <keras.initializers.VarianceScaling object at 0x147755cf8>
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv DEBUG inp: Tensor("conv_32_0_leakyrelu/LeakyRelu:0", shape=(?, 16, 16, 256), dtype=float32), filters: 512, kernel_size: 5, strides: 2, use_instance_norm: False, kwargs: {})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks get_name DEBUG Generating block name: conv_16_0
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv2d DEBUG inp: Tensor("conv_32_0_leakyrelu/LeakyRelu:0", shape=(?, 16, 16, 256), dtype=float32), filters: 512, kernel_size: 5, strides: 2, padding: same, kwargs: {'name': 'conv_16_0_conv2d'})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Set default kernel_initializer to: <keras.initializers.VarianceScaling object at 0x14a6a07b8>
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv DEBUG inp: Tensor("conv_16_0_leakyrelu/LeakyRelu:0", shape=(?, 8, 8, 512), dtype=float32), filters: 1024, kernel_size: 5, strides: 2, use_instance_norm: False, kwargs: {})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks get_name DEBUG Generating block name: conv_8_0
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv2d DEBUG inp: Tensor("conv_16_0_leakyrelu/LeakyRelu:0", shape=(?, 8, 8, 512), dtype=float32), filters: 1024, kernel_size: 5, strides: 2, padding: same, kwargs: {'name': 'conv_8_0_conv2d'})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Set default kernel_initializer to: <keras.initializers.VarianceScaling object at 0x14a6a8ba8>
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks upscale DEBUG inp: Tensor("reshape_1/Reshape:0", shape=(?, 4, 4, 1024), dtype=float32), filters: 512, kernel_size: 3, use_instance_norm: False, kwargs: {})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks get_name DEBUG Generating block name: upscale_4_0
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Set default kernel_initializer to: <keras.initializers.VarianceScaling object at 0x14a6cc278>
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks conv2d DEBUG inp: Tensor("reshape_1/Reshape:0", shape=(?, 4, 4, 1024), dtype=float32), filters: 2048, kernel_size: 3, strides: (1, 1), padding: same, kwargs: {'name': 'upscale_4_0_conv2d', 'kernel_initializer': <keras.initializers.VarianceScaling object at 0x14a6cc278>})
02/23/2020 20:34:17 MainProcess _training_0 nn_blocks set_default_initializer DEBUG Using model specified initializer: <keras.initializers.VarianceScaling object at 0x14a6cc278>
02/23/2020 20:34:17 MainProcess _training_0 _base add_network DEBUG network_type: 'encoder', side: 'None', network: '<keras.engine.training.Model object at 0x14a6dea58>', is_output: False
02/23/2020 20:34:17 MainProcess _training_0 _base name DEBUG model name: 'original'
02/23/2020 20:34:17 MainProcess _training_0 _base add_network DEBUG name: 'encoder', filename: 'original_encoder.h5'
02/23/2020 20:34:17 MainProcess _training_0 _base __init__ DEBUG Initializing NNMeta: (filename: '/Users/holysaya/Documents/faceswap/model/original_encoder.h5', network_type: 'encoder', side: 'None', network: <keras.engine.training.Model object at 0x14a6dea58>, is_output: False
02/23/2020 20:34:17 MainProcess _training_0 _base __init__ DEBUG Initialized NNMeta
02/23/2020 20:34:17 MainProcess _training_0 original add_networks DEBUG Added networks
02/23/2020 20:34:17 MainProcess _training_0 _base load_models DEBUG Load model: (swapped: False)
02/23/2020 20:34:17 MainProcess _training_0 _base models_exist DEBUG Pre-existing models exist: True
02/23/2020 20:34:17 MainProcess _training_0 _base models_exist DEBUG Pre-existing models exist: True
02/23/2020 20:34:17 MainProcess _training_0 module_wrapper _tfmw_add_deprecation_warning DEBUG From /Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:95: The name tf.reset_default_graph is deprecated. Please use tf.compat.v1.reset_default_graph instead.\n
02/23/2020 20:34:17 MainProcess _training_0 module_wrapper _tfmw_add_deprecation_warning DEBUG From /Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:98: The name tf.placeholder_with_default is deprecated. Please use tf.compat.v1.placeholder_with_default instead.\n
02/23/2020 20:34:17 MainProcess _training_0 _base map_models DEBUG Map models: (swapped: False)
02/23/2020 20:34:17 MainProcess _training_0 _base map_models DEBUG Mapped models: (models_map: {'a': {'decoder': '/Users/holysaya/Documents/faceswap/model/original_decoder_A.h5'}, 'b': {'decoder': '/Users/holysaya/Documents/faceswap/model/original_decoder_B.h5'}})
02/23/2020 20:34:17 MainProcess _training_0 _base load DEBUG Loading model: '/Users/holysaya/Documents/faceswap/model/original_decoder_A.h5'
02/23/2020 20:34:18 MainProcess _training_0 _base convert_legacy_weights INFO Adding model topology to legacy weights file: '/Users/holysaya/Documents/faceswap/model/original_decoder_A.h5'
02/23/2020 20:34:18 MainProcess _training_0 multithreading run DEBUG Error in thread (_training_0): Tensor("Placeholder:0", shape=(3, 3, 512, 1024), dtype=float32) must be from the same graph as Tensor("upscale_8_0_conv2d/kernel:0", shape=(3, 3, 512, 1024), dtype=float32_ref).
02/23/2020 20:34:18 MainProcess MainThread train _monitor DEBUG Thread error detected
02/23/2020 20:34:18 MainProcess MainThread train _monitor DEBUG Closed Monitor
02/23/2020 20:34:18 MainProcess MainThread train _end_thread DEBUG Ending Training thread
02/23/2020 20:34:18 MainProcess MainThread train _end_thread CRITICAL Error caught! Exiting...
02/23/2020 20:34:18 MainProcess MainThread multithreading join DEBUG Joining Threads: '_training'
02/23/2020 20:34:18 MainProcess MainThread multithreading join DEBUG Joining Thread: '_training_0'
02/23/2020 20:34:18 MainProcess MainThread multithreading join ERROR Caught exception in thread: '_training_0'
Traceback (most recent call last):
File "/Users/holysaya/Documents/faceswap/plugins/train/model/_base.py", line 836, in load
network = load_model(self.filename, custom_objects=get_custom_objects())
File "/Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/engine/saving.py", line 419, in load_model
model = _deserialize_model(f, custom_objects, compile)
File "/Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/engine/saving.py", line 221, in _deserialize_model
model_config = f['model_config']
File "/Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/utils/io_utils.py", line 302, in __getitem__
raise ValueError('Cannot create group in read only mode.')
ValueError: Cannot create group in read only mode.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Users/holysaya/Documents/faceswap/lib/cli.py", line 128, in execute_script
process.process()
File "/Users/holysaya/Documents/faceswap/scripts/train.py", line 159, in process
self._end_thread(thread, err)
File "/Users/holysaya/Documents/faceswap/scripts/train.py", line 199, in _end_thread
thread.join()
File "/Users/holysaya/Documents/faceswap/lib/multithreading.py", line 121, in join
raise thread.err[1].with_traceback(thread.err[2])
File "/Users/holysaya/Documents/faceswap/lib/multithreading.py", line 37, in run
self._target(*self._args, **self._kwargs)
File "/Users/holysaya/Documents/faceswap/scripts/train.py", line 224, in _training
raise err
File "/Users/holysaya/Documents/faceswap/scripts/train.py", line 212, in _training
model = self._load_model()
File "/Users/holysaya/Documents/faceswap/scripts/train.py", line 253, in _load_model
predict=False)
File "/Users/holysaya/Documents/faceswap/plugins/train/model/original.py", line 25, in __init__
super().__init__(*args, **kwargs)
File "/Users/holysaya/Documents/faceswap/plugins/train/model/_base.py", line 126, in __init__
self.build()
File "/Users/holysaya/Documents/faceswap/plugins/train/model/_base.py", line 245, in build
self.load_models(swapped=False)
File "/Users/holysaya/Documents/faceswap/plugins/train/model/_base.py", line 457, in load_models
is_loaded = network.load(fullpath=model_mapping[network.side][network.type])
File "/Users/holysaya/Documents/faceswap/plugins/train/model/_base.py", line 839, in load
self.convert_legacy_weights()
File "/Users/holysaya/Documents/faceswap/plugins/train/model/_base.py", line 865, in convert_legacy_weights
self.network.load_weights(self.filename)
File "/Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/engine/network.py", line 1166, in load_weights
f, self.layers, reshape=reshape)
File "/Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/engine/saving.py", line 1058, in load_weights_from_hdf5_group
K.batch_set_value(weight_value_tuples)
File "/Users/holysaya/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py", line 2465, in batch_set_value
assign_op = x.assign(assign_placeholder)
File "/Users/holysaya/anaconda3/lib/python3.6/site-packages/tensorflow_core/python/ops/variables.py", line 2067, in assign
self._variable, value, use_locking=use_locking, name=name)
File "/Users/holysaya/anaconda3/lib/python3.6/site-packages/tensorflow_core/python/ops/state_ops.py", line 227, in assign
validate_shape=validate_shape)
File "/Users/holysaya/anaconda3/lib/python3.6/site-packages/tensorflow_core/python/ops/gen_state_ops.py", line 66, in assign
use_locking=use_locking, name=name)
File "/Users/holysaya/anaconda3/lib/python3.6/site-packages/tensorflow_core/python/framework/op_def_library.py", line 367, in _apply_op_helper
g = ops._get_graph_from_inputs(_Flatten(keywords.values()))
File "/Users/holysaya/anaconda3/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 5979, in _get_graph_from_inputs
_assert_same_graph(original_graph_element, graph_element)
File "/Users/holysaya/anaconda3/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 5914, in _assert_same_graph
(item, original_item))
ValueError: Tensor("Placeholder:0", shape=(3, 3, 512, 1024), dtype=float32) must be from the same graph as Tensor("upscale_8_0_conv2d/kernel:0", shape=(3, 3, 512, 1024), dtype=float32_ref).
============ System Information ============
encoding: UTF-8
git_branch: Not Found
git_commits: Not Found
gpu_cuda: Unsupported OS. Check Conda packages for Conda Cuda
gpu_cudnn: Unsupported OS. Check Conda packages for Conda cuDNN
gpu_devices:
gpu_devices_active:
gpu_driver: 0
gpu_vram:
os_machine: x86_64
os_platform: Darwin-18.6.0-x86_64-i386-64bit
os_release: 18.6.0
py_command: faceswap.py train -A /Users/holysaya/Documents/faceswap/B_face -B /Users/holysaya/Documents/faceswap/A_face -m /Users/holysaya/Documents/faceswap/model -p
py_conda_version: conda 4.8.2
py_implementation: CPython
py_version: 3.6.10
py_virtual_env: False
sys_cores: 8
sys_processor: i386
sys_ram: Total: 16384MB, Available: 6987MB, Used: 16314MB, Free: 28MB
=============== Pip Packages ===============
absl-py==0.9.0
alabaster==0.7.10
anaconda-client==1.6.5
anaconda-navigator==1.6.9
anaconda-project==0.8.0
appdirs==1.4.3
appnope==0.1.0
appscript==1.0.1
asn1crypto==0.22.0
astor==0.8.1
astroid==1.5.3
astropy==2.0.2
Babel==2.5.0
backports.shutil-get-terminal-size==1.0.0
beautifulsoup4==4.6.0
bitarray==0.8.1
bkcharts==0.2
blaze==0.11.3
bleach==2.0.0
bokeh==0.12.10
boto==2.48.0
Bottleneck==1.2.1
cachetools==4.0.0
certifi==2019.11.28
cffi==1.10.0
chardet==3.0.4
click==6.7
cloudpickle==0.4.0
clyent==1.2.2
cmake==3.16.3
colorama==0.3.9
conda==4.8.2
conda-build==3.0.27
conda-package-handling==1.6.0
conda-verify==2.0.0
contextlib2==0.5.5
cryptography==2.8
cycler==0.10.0
Cython==0.26.1
cytoolz==0.8.2
dask==0.15.3
datashape==0.5.4
decorator==4.1.2
distlib==0.3.0
distributed==1.19.1
dlib==19.9.0
docutils==0.14
entrypoints==0.2.3
et-xmlfile==1.0.1
fastcache==1.0.2
fastcluster==1.1.26
ffmpy==0.2.2
filelock==3.0.12
Flask==0.12.2
Flask-Cors==3.0.3
gast==0.2.2
gevent==1.2.2
glob2==0.5
gmpy2==2.0.8
google-auth==1.11.2
google-auth-oauthlib==0.4.1
google-pasta==0.1.8
greenlet==0.4.12
grpcio==1.27.2
h5py==2.9.0
heapdict==1.0.0
html5lib==0.999999999
idna==2.9
imageio==2.6.1
imageio-ffmpeg==0.4.0
imagesize==0.7.1
importlib-metadata==1.5.0
importlib-resources==1.0.2
ipykernel==4.6.1
ipython==6.1.0
ipython-genutils==0.2.0
ipywidgets==7.0.0
isort==4.2.15
itsdangerous==0.24
jdcal==1.3
jedi==0.10.2
Jinja2==2.9.6
jsonschema==2.6.0
jupyter-client==5.1.0
jupyter-console==5.2.0
jupyter-core==4.3.0
jupyterlab==0.27.0
jupyterlab-launcher==0.4.0
Keras==2.2.4
Keras-Applications==1.0.8
Keras-Preprocessing==1.1.0
kiwisolver==1.1.0
lazy-object-proxy==1.3.1
llvmlite==0.20.0
locket==0.2.0
lxml==4.1.0
Markdown==3.2.1
MarkupSafe==1.0
matplotlib==3.1.1
mccabe==0.6.1
mistune==0.7.4
mpmath==0.19
msgpack-python==0.4.8
multipledispatch==0.4.9
navigator-updater==0.1.0
nbconvert==5.3.1
nbformat==4.4.0
networkx==2.0
nltk==3.2.4
nose==1.3.7
notebook==5.0.0
numba==0.35.0+6.gaa35fb1
numexpr==2.6.2
numpy==1.17.4
numpydoc==0.7.0
nvidia-ml-py3==7.352.1
oauthlib==3.1.0
odo==0.5.1
olefile==0.44
opencv-python==4.1.2.30
openpyxl==2.4.8
opt-einsum==3.1.0
packaging==16.8
pandas==0.20.3
pandocfilters==1.4.2
partd==0.3.8
path.py==10.3.1
pathlib==1.0.1
pathlib2==2.3.0
patsy==0.4.1
pep8==1.7.0
pexpect==4.2.1
pickleshare==0.7.4
Pillow==6.2.1
pkginfo==1.4.1
ply==3.10
prompt-toolkit==1.0.15
protobuf==3.11.3
psutil==5.4.0
ptyprocess==0.5.2
py==1.4.34
pyasn1==0.4.8
pyasn1-modules==0.2.8
pycodestyle==2.3.1
pycosat==0.6.3
pycparser==2.18
pycrypto==2.6.1
pycurl==7.43.0.2
pyflakes==1.6.0
Pygments==2.2.0
pylint==1.7.4
pynvx==1.0.0
pyodbc==4.0.17
pyOpenSSL==17.2.0
pyparsing==2.2.0
PySocks==1.6.7
pytest==3.2.1
python-dateutil==2.6.1
pytz==2017.2
PyWavelets==0.5.2
PyYAML==3.12
pyzmq==16.0.2
QtAwesome==0.4.4
qtconsole==4.3.1
QtPy==1.3.1
requests==2.23.0
requests-oauthlib==1.3.0
rope==0.10.5
rsa==4.0
ruamel-yaml==0.11.14
scikit-image==0.13.0
scikit-learn==0.19.1
scipy==1.4.1
seaborn==0.8
simplegeneric==0.8.1
singledispatch==3.4.0.3
six==1.14.0
snowballstemmer==1.2.1
sortedcollections==0.5.3
sortedcontainers==1.5.7
Sphinx==1.6.3
sphinxcontrib-websupport==1.0.1
spyder==3.2.4
SQLAlchemy==1.1.13
statsmodels==0.8.0
sympy==1.1.1
tables==3.4.2
tblib==1.3.2
tensorboard==1.15.0
tensorflow==1.15.0
tensorflow-estimator==1.15.1
tensorflow-gpu==1.1.0
termcolor==1.1.0
terminado==0.6
testpath==0.3.1
toolz==0.8.2
toposort==1.5
tornado==4.5.2
tqdm==4.42.1
traitlets==4.3.2
typing==3.6.2
unicodecsv==0.14.1
urllib3==1.25.8
virtualenv==20.0.5
wcwidth==0.1.7
webencodings==0.5.1
Werkzeug==1.0.0
widgetsnbextension==3.0.2
wrapt==1.12.0
xlrd==1.1.0
XlsxWriter==1.0.2
xlwings==0.11.4
xlwt==1.2.0
zict==0.1.3
zipp==3.0.0
============== Conda Packages ==============
# packages in environment at /Users/holysaya/anaconda3:
#
# Name Version Build Channel
_ipyw_jlab_nb_ext_conf 0.1.0 py36h2fc01ae_0
absl-py 0.9.0 pypi_0 pypi
alabaster 0.7.10 py36h174008c_0
anaconda 5.0.1 py36h6e48e2d_1
anaconda-client 1.6.5 py36h04cfe59_0
anaconda-navigator 1.6.9 py36ha31b149_0
anaconda-project 0.8.0 py36h99320b2_0
appdirs 1.4.3 pypi_0 pypi
appnope 0.1.0 py36hf537a9a_0
appscript 1.0.1 py36h9e71e49_1
asn1crypto 0.22.0 py36hb705621_1
astor 0.8.1 pypi_0 pypi
astroid 1.5.3 py36h1333018_0
astropy 2.0.2 py36hf79c81d_4
babel 2.5.0 py36h9f161ff_0
backports 1.0 py36ha3c1827_1
backports.shutil_get_terminal_size 1.0.0 py36hd7a2ee4_2
beautifulsoup4 4.6.0 py36h72d3c9f_1
bitarray 0.8.1 py36h20fa61d_0
bkcharts 0.2 py36h073222e_0
blaze 0.11.3 py36h02e7a37_0
bleach 2.0.0 py36h8fcea71_0
bokeh 0.12.10 py36hfd5be35_0
boto 2.48.0 py36hdbc59ac_1
bottleneck 1.2.1 py36hbd380ad_0
bzip2 1.0.6 h92991f9_1
ca-certificates 2017.08.26 ha1e5d58_0
cachetools 4.0.0 pypi_0 pypi
certifi 2019.11.28 pypi_0 pypi
cffi 1.10.0 py36h880867e_1
chardet 3.0.4 pypi_0 pypi
click 6.7 py36hec950be_0
cloudpickle 0.4.0 py36h13b7e56_0
clyent 1.2.2 py36hae3ad88_0
cmake 3.16.3 pypi_0 pypi
colorama 0.3.9 py36hd29a30c_0
conda 4.8.2 py36_0
conda-build 3.0.27 py36hb78d8cd_0
conda-env 2.6.0 1
conda-package-handling 1.6.0 py36h1de35cc_0
conda-verify 2.0.0 py36he837df3_0
contextlib2 0.5.5 py36hd66e5e7_0
cryptography 2.8 py36ha12b0ac_0
curl 7.64.0 ha441bb4_2
cycler 0.10.0 py36hfc81398_0
cython 0.26.1 py36hd51f8eb_0
cytoolz 0.8.2 py36h290905f_0
dask 0.15.3 py36hc3ad2d6_0
dask-core 0.15.3 py36hc0be6b7_0
datashape 0.5.4 py36hfb22df8_0
dbus 1.10.22 h50d9ad6_0
decorator 4.1.2 py36h69a1b52_0
distlib 0.3.0 pypi_0 pypi
distributed 1.19.1 py36h4ae75d2_0
dlib 19.9.0 pypi_0 pypi
docutils 0.14 py36hbfde631_0
entrypoints 0.2.3 py36hd81d71f_2
et_xmlfile 1.0.1 py36h1315bdc_0
expat 2.2.6 h0a44026_0
fastcache 1.0.2 py36h8606a76_0
fastcluster 1.1.26 pypi_0 pypi
ffmpy 0.2.2 pypi_0 pypi
filelock 3.0.12 pypi_0 pypi
flask 0.12.2 py36h5658096_0
flask-cors 3.0.3 py36h7387b97_0
freetype 2.8 h143eb01_0
gast 0.2.2 pypi_0 pypi
get_terminal_size 1.0.0 h7520d66_0
gettext 0.19.8.1 hb0f4f8b_2
gevent 1.2.2 py36ha70b9d6_0
glib 2.53.6 ha08cb78_1
glob2 0.5 py36h12393a9_0
gmp 6.1.2 h4a9834d_0
gmpy2 2.0.8 py36h7ef02cb_1
google-auth 1.11.2 pypi_0 pypi
google-auth-oauthlib 0.4.1 pypi_0 pypi
google-pasta 0.1.8 pypi_0 pypi
greenlet 0.4.12 py36hf09ba7b_0
grpcio 1.27.2 pypi_0 pypi
h5py 2.10.0 pypi_0 pypi
hdf5 1.10.1 h6090a45_0
heapdict 1.0.0 py36h27a9ac6_0
html5lib 0.999999999 py36h79312fd_0
icu 58.2 hea21ae5_0
idna 2.9 pypi_0 pypi
imageio 2.6.1 pypi_0 pypi
imageio-ffmpeg 0.4.0 pypi_0 pypi
imagesize 0.7.1 py36h3495948_0
importlib-metadata 1.5.0 pypi_0 pypi
importlib-resources 1.0.2 pypi_0 pypi
intel-openmp 2018.0.0 h68bdfb3_7
ipykernel 4.6.1 py36h3208c25_0
ipython 6.1.0 py36hf612aae_1
ipython_genutils 0.2.0 py36h241746c_0
ipywidgets 7.0.0 py36h24d3910_0
isort 4.2.15 py36hceb2a01_0
itsdangerous 0.24 py36h49fbb8d_1
jbig 2.1 h4d881f8_0
jdcal 1.3 py36h1986823_0
jedi 0.10.2 py36h6325097_0
jinja2 2.9.6 py36hde4beb4_1
jpeg 9b haccd157_1
jsonschema 2.6.0 py36hb385e00_0
jupyter 1.0.0 py36h598a6cc_0
jupyter_client 5.1.0 py36hf6c435f_0
jupyter_console 5.2.0 py36hccf5b1c_1
jupyter_core 4.3.0 py36h93810fe_0
jupyterlab 0.27.0 py36hd3092eb_2
jupyterlab_launcher 0.4.0 py36h93e02e9_0
keras 2.2.4 pypi_0 pypi
keras-applications 1.0.8 pypi_0 pypi
keras-preprocessing 1.1.0 pypi_0 pypi
kiwisolver 1.1.0 pypi_0 pypi
krb5 1.16.4 hddcf347_0
lazy-object-proxy 1.3.1 py36h2fbbe47_0
libcurl 7.64.0 h051b688_2
libcxx 4.0.1 h579ed51_0
libcxxabi 4.0.1 hebd6815_0
libedit 3.1.20181209 hb402a30_0
libffi 3.2.1 hd939716_3
libgfortran 3.0.1 h93005f0_2
libiconv 1.15 h99df5da_5
libpng 1.6.32 hce72d48_2
libsodium 1.0.13 hba5e272_2
libssh2 1.8.0 h1218725_2
libtiff 4.0.8 h8cd0352_9
libxml2 2.9.4 hbd0960b_5
libxslt 1.1.29 h95a2935_5
llvmlite 0.20.0 py36_0
locket 0.2.0 py36hca03003_1
lxml 4.1.0 py36h8179fc0_0
lzo 2.10 hb6b8854_1
markdown 3.2.1 pypi_0 pypi
markupsafe 1.0 py36h3a1e703_1
matplotlib 3.1.1 pypi_0 pypi
mccabe 0.6.1 py36hdaeb55d_0
mistune 0.7.4 py36hccd6237_0
mkl 2018.0.0 h5ef208c_6
mkl-service 1.1.2 py36h7ea6df4_4
mpc 1.0.3 hc455b36_4
mpfr 3.1.5 h7fa3772_1
mpmath 0.19 py36h9185fea_2
msgpack-python 0.4.8 py36h46767b2_0
multipledispatch 0.4.9 py36hc5f92b5_0
navigator-updater 0.1.0 py36h7aee5fb_0
nbconvert 5.3.1 py36h810822e_0
nbformat 4.4.0 py36h827af21_0
ncurses 6.1 h0a44026_1
networkx 2.0 py36hefccab9_0
nltk 3.2.4 py36h27d1ea0_0
nose 1.3.7 py36h73fae2b_2
notebook 5.0.0 py36h462289e_2
numba 0.35.0 np113py36_6
numexpr 2.6.2 py36h0f4f1da_1
numpy 1.18.1 pypi_0 pypi
numpydoc 0.7.0 py36he54d08e_0
nvidia-ml-py3 7.352.1 pypi_0 pypi
oauthlib 3.1.0 pypi_0 pypi
odo 0.5.1 py36hc1af34a_0
olefile 0.44 py36ha08bf50_0
opencv-python 4.1.2.30 pypi_0 pypi
openpyxl 2.4.8 py36he899640_1
openssl 1.1.1d h1de35cc_4
opt-einsum 3.1.0 pypi_0 pypi
packaging 16.8 py36he5e8135_0
pandas 0.20.3 py36hd6655d8_2
pandoc 1.19.2.1 ha5e8f32_1
pandocfilters 1.4.2 py36h3b0b094_1
partd 0.3.8 py36hf5c4cb8_0
path.py 10.3.1 py36hd33c240_0
pathlib 1.0.1 pypi_0 pypi
pathlib2 2.3.0 py36h877a6d8_0
patsy 0.4.1 py36ha1b3fa5_0
pcre 8.41 h29eefc5_0
pep8 1.7.0 py36hc268eb1_0
pexpect 4.2.1 py36h3eac828_0
pickleshare 0.7.4 py36hf512f8e_0
pillow 6.2.1 pypi_0 pypi
pip 20.0.2 pypi_0 pypi
pkginfo 1.4.1 py36h25bf955_0
ply 3.10 py36h10e714e_0
prompt_toolkit 1.0.15 py36haeda067_0
protobuf 3.11.3 pypi_0 pypi
psutil 5.4.0 py36ha052210_0
ptyprocess 0.5.2 py36he6521c3_0
py 1.4.34 py36hecf431b_1
pyasn1 0.4.8 pypi_0 pypi
pyasn1-modules 0.2.8 pypi_0 pypi
pycodestyle 2.3.1 py36h83e8646_0
pycosat 0.6.3 py36h1de35cc_0
pycparser 2.18 py36h724b2fc_1
pycrypto 2.6.1 py36h72f2894_1
pycurl 7.43.0.2 py36ha12b0ac_0
pyflakes 1.6.0 py36hea45e83_0
pygments 2.2.0 py36h240cd3f_0
pylint 1.7.4 py36hdee9077_0
pynvx 1.0.0 pypi_0 pypi
pyodbc 4.0.17 py36h5478161_0
pyopenssl 17.2.0 py36h5d7bf08_0
pyparsing 2.2.0 py36hb281f35_0
pyqt 5.6.0 py36he5c6137_6
pysocks 1.6.7 py36hfa33cec_1
pytables 3.4.2 py36hfbd7ab0_2
pytest 3.2.1 py36h9963153_1
python 3.6.10 h359304d_0
python-dateutil 2.6.1 py36h86d2abb_1
python.app 2 py36h7fe2238_6
pytz 2017.2 py36h2e7dfbc_1
pywavelets 0.5.2 py36h2710a04_0
pyyaml 3.12 py36h2ba1e63_1
pyzmq 16.0.2 py36h087ffad_2
qt 5.6.2 h9975529_14
qtawesome 0.4.4 py36h468c6fb_0
qtconsole 4.3.1 py36hd96c0ff_0
qtpy 1.3.1 py36h16bb863_0
readline 7.0 h1de35cc_5
requests 2.23.0 pypi_0 pypi
requests-oauthlib 1.3.0 pypi_0 pypi
rhash 1.3.8 ha12b0ac_0
rope 0.10.5 py36h5764ad1_0
rsa 4.0 pypi_0 pypi
ruamel_yaml 0.11.14 py36h9d7ade0_2
scikit-image 0.13.0 py36h398857d_1
scikit-learn 0.19.1 py36hffbff8c_0
scipy 1.4.1 pypi_0 pypi
seaborn 0.8.0 py36h74df97e_0
setuptools 45.2.0 pypi_0 pypi
simplegeneric 0.8.1 py36he5b5b09_0
singledispatch 3.4.0.3 py36hf20db9d_0
sip 4.18.1 py36h2824476_2
six 1.14.0 pypi_0 pypi
snowballstemmer 1.2.1 py36h6c7b616_0
sortedcollections 0.5.3 py36he9c3ed6_0
sortedcontainers 1.5.7 py36ha982688_0
sphinx 1.6.3 py36hcd1b3e7_0
sphinxcontrib 1.0 py36h9364dc8_1
sphinxcontrib-websupport 1.0.1 py36h92f4a7a_1
spyder 3.2.4 py36h908396f_0
sqlalchemy 1.1.13 py36h156b851_0
sqlite 3.31.1 ha441bb4_0
statsmodels 0.8.0 py36h9c68fc9_0
sympy 1.1.1 py36h7f3cf04_0
tblib 1.3.2 py36hda67792_0
tensorboard 1.15.0 pypi_0 pypi
tensorflow 1.15.0 pypi_0 pypi
tensorflow-estimator 1.15.1 pypi_0 pypi
tensorflow-gpu 1.1.0 pypi_0 pypi
termcolor 1.1.0 pypi_0 pypi
terminado 0.6 py36h656782e_0
testpath 0.3.1 py36h625a49b_0
tk 8.6.8 ha441bb4_0
toolz 0.8.2 py36h7b95164_0
toposort 1.5 pypi_0 pypi
tornado 4.5.2 py36h468dda9_0
tqdm 4.42.1 py_0
traitlets 4.3.2 py36h65bd3ce_0
typing 3.6.2 py36haa2d9ef_0
unicodecsv 0.14.1 py36he531d66_0
unixodbc 2.3.4 h4cb4dde_1
urllib3 1.25.8 pypi_0 pypi
virtualenv 20.0.5 pypi_0 pypi
wcwidth 0.1.7 py36h8c6ec74_0
webencodings 0.5.1 py36h3b9701d_1
werkzeug 1.0.0 pypi_0 pypi
wheel 0.34.2 pypi_0 pypi
widgetsnbextension 3.0.2 py36h91f43ea_1
wrapt 1.12.0 pypi_0 pypi
xlrd 1.1.0 py36h336f4a2_1
xlsxwriter 1.0.2 py36h3736301_0
xlwings 0.11.4 py36hc75f156_0
xlwt 1.2.0 py36h5ad1178_0
xz 5.2.4 h1de35cc_4
yaml 0.1.7 hff548bb_1
zeromq 4.2.2 h131e0f7_1
zict 0.1.3 py36h71da714_0
zipp 3.0.0 pypi_0 pypi
zlib 1.2.11 h60db283_1
================= Configs ==================
--------- convert.ini ---------
[color.color_transfer]
clip: True
preserve_paper: True
[color.match_hist]
threshold: 99.0
[color.manual_balance]
colorspace: HSV
balance_1: 0.0
balance_2: 0.0
balance_3: 0.0
contrast: 0.0
brightness: 0.0
[writer.pillow]
format: png
draw_transparent: False
optimize: False
gif_interlace: True
jpg_quality: 75
png_compress_level: 3
tif_compression: tiff_deflate
[writer.ffmpeg]
container: mp4
codec: libx264
crf: 23
preset: medium
tune: none
profile: auto
level: auto
[writer.gif]
fps: 25
loop: 0
palettesize: 256
subrectangles: False
[writer.opencv]
format: png
draw_transparent: False
jpg_quality: 75
png_compress_level: 3
[mask.mask_blend]
type: normalized
kernel_size: 3
passes: 4
threshold: 4
erosion: 0.0
[mask.box_blend]
type: gaussian
distance: 11.0
radius: 5.0
passes: 1
[scaling.sharpen]
method: unsharp_mask
amount: 150
radius: 0.3
threshold: 5.0
--------- gui.ini ---------
[global]
fullscreen: False
tab: extract
options_panel_width: 30
console_panel_height: 20
icon_size: 14
font: default
font_size: 9
autosave_last_session: prompt
timeout: 120
auto_load_model_stats: True
--------- .faceswap ---------
backend: cpu
--------- extract.ini ---------
[global]
allow_growth: False
[detect.mtcnn]
minsize: 20
threshold_1: 0.6
threshold_2: 0.7
threshold_3: 0.7
scalefactor: 0.709
batch-size: 8
[detect.cv2_dnn]
confidence: 50
[detect.s3fd]
confidence: 70
batch-size: 4
[align.fan]
batch-size: 12
[mask.unet_dfl]
batch-size: 8
[mask.vgg_obstructed]
batch-size: 2
[mask.vgg_clear]
batch-size: 6
--------- train.ini ---------
[global]
coverage: 68.75
mask_type: none
mask_blur_kernel: 3
mask_threshold: 4
learn_mask: False
icnr_init: False
conv_aware_init: False
subpixel_upscaling: False
reflect_padding: False
penalized_mask_loss: True
loss_function: mae
learning_rate: 5e-05
[model.realface]
input_size: 64
output_size: 128
dense_nodes: 1536
complexity_encoder: 128
complexity_decoder: 512
[model.dfl_sae]
input_size: 128
clipnorm: True
architecture: df
autoencoder_dims: 0
encoder_dims: 42
decoder_dims: 21
multiscale_decoder: False
[model.unbalanced]
input_size: 128
lowmem: False
clipnorm: True
nodes: 1024
complexity_encoder: 128
complexity_decoder_a: 384
complexity_decoder_b: 512
[model.dlight]
features: best
details: good
output_size: 256
[model.villain]
lowmem: False
[model.original]
lowmem: False
[model.dfl_h128]
lowmem: False
[trainer.original]
preview_images: 14
zoom_amount: 5
rotation_range: 10
shift_range: 5
flip_chance: 50
color_lightness: 30
color_ab: 8
color_clahe_chance: 50
color_clahe_max_size: 4
