08/06/2020 16:25:19 MainProcess _training_0 multithreading start DEBUG Started all threads '_run': 2
08/06/2020 16:25:19 MainProcess _training_0 _base _set_preview_feed DEBUG Setting preview feed: (side: 'b')
08/06/2020 16:25:19 MainProcess _training_0 _base _load_generator DEBUG Loading generator: b
08/06/2020 16:25:19 MainProcess _training_0 _base _load_generator DEBUG input_size: 64, output_shapes: [(64, 64, 3)]
08/06/2020 16:25:19 MainProcess _training_0 training_data __init__ DEBUG Initializing TrainingDataGenerator: (model_input_size: 64, model_output_shapes: [(64, 64, 3)], training_opts: {'alignments': {'a': 'E:\\deepfake\\faceexport\\alignments.fsa', 'b': 'E:\\deepfake\\face2\\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': 0.6875, 'mask_type': None, 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'penalized_mask_loss': False}, landmarks: {}, masks: {}, config: {'coverage': 68.75, 'mask_type': None, 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'icnr_init': False, 'conv_aware_init': False, 'reflect_padding': False, 'penalized_mask_loss': True, 'loss_function': 'mae', 'learning_rate': 5e-05, '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})
08/06/2020 16:25:19 MainProcess _training_0 training_data __init__ DEBUG Initialized TrainingDataGenerator
08/06/2020 16:25:19 MainProcess _training_0 training_data minibatch_ab DEBUG Queue batches: (image_count: 64, batchsize: 14, side: 'b', do_shuffle: True, is_preview, True, is_timelapse: False)
08/06/2020 16:25:19 MainProcess _training_0 training_data __init__ DEBUG Initializing ImageAugmentation: (batchsize: 14, is_display: True, input_size: 64, output_shapes: [(64, 64, 3)], coverage_ratio: 0.6875, config: {'coverage': 68.75, 'mask_type': None, 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'icnr_init': False, 'conv_aware_init': False, 'reflect_padding': False, 'penalized_mask_loss': True, 'loss_function': 'mae', 'learning_rate': 5e-05, '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})
08/06/2020 16:25:19 MainProcess _training_0 training_data __init__ DEBUG Output sizes: [64]
08/06/2020 16:25:19 MainProcess _training_0 training_data __init__ DEBUG Initialized ImageAugmentation
08/06/2020 16:25:19 MainProcess _training_0 multithreading __init__ DEBUG Initializing BackgroundGenerator: (target: '_run', thread_count: 2)
08/06/2020 16:25:19 MainProcess _training_0 multithreading __init__ DEBUG Initialized BackgroundGenerator: '_run'
08/06/2020 16:25:19 MainProcess _training_0 multithreading start DEBUG Starting thread(s): '_run'
08/06/2020 16:25:19 MainProcess _training_0 multithreading start DEBUG Starting thread 1 of 2: '_run_0'
08/06/2020 16:25:19 MainProcess _run_0 training_data _minibatch DEBUG Loading minibatch generator: (image_count: 64, side: 'b', do_shuffle: True)
08/06/2020 16:25:19 MainProcess _training_0 multithreading start DEBUG Starting thread 2 of 2: '_run_1'
08/06/2020 16:25:19 MainProcess _run_1 training_data _minibatch DEBUG Loading minibatch generator: (image_count: 64, side: 'b', do_shuffle: True)
08/06/2020 16:25:19 MainProcess _training_0 multithreading start DEBUG Started all threads '_run': 2
08/06/2020 16:25:19 MainProcess _training_0 _base _set_preview_feed DEBUG Set preview feed. Batchsize: 14
08/06/2020 16:25:19 MainProcess _training_0 _base _set_tensorboard DEBUG Enabling TensorBoard Logging
08/06/2020 16:25:19 MainProcess _training_0 _base _set_tensorboard DEBUG Setting up TensorBoard Logging. Side: a
08/06/2020 16:25:19 MainProcess _training_0 _base name DEBUG model name: 'original'
08/06/2020 16:25:19 MainProcess _training_0 _base _tensorboard_kwargs DEBUG Tensorflow version: [1, 15, 0]
08/06/2020 16:25:19 MainProcess _training_0 _base _tensorboard_kwargs DEBUG {'histogram_freq': 0, 'batch_size': 64, 'write_graph': True, 'write_grads': True, 'update_freq': 'batch', 'profile_batch': 0}
08/06/2020 16:25:21 MainProcess _training_0 _base _set_tensorboard DEBUG Setting up TensorBoard Logging. Side: b
08/06/2020 16:25:21 MainProcess _training_0 _base name DEBUG model name: 'original'
08/06/2020 16:25:21 MainProcess _training_0 _base _tensorboard_kwargs DEBUG Tensorflow version: [1, 15, 0]
08/06/2020 16:25:21 MainProcess _training_0 _base _tensorboard_kwargs DEBUG {'histogram_freq': 0, 'batch_size': 64, 'write_graph': True, 'write_grads': True, 'update_freq': 'batch', 'profile_batch': 0}
08/06/2020 16:25:22 MainProcess _training_0 _base _set_tensorboard INFO Enabled TensorBoard Logging
08/06/2020 16:25:22 MainProcess _training_0 _base _use_mask DEBUG False
08/06/2020 16:25:22 MainProcess _training_0 _base __init__ DEBUG Initializing Samples: model: '<plugins.train.model.original.Model object at 0x000001C337F73BC8>', use_mask: False, coverage_ratio: 0.6875)
08/06/2020 16:25:22 MainProcess _training_0 _base __init__ DEBUG Initialized Samples
08/06/2020 16:25:22 MainProcess _training_0 _base _use_mask DEBUG False
08/06/2020 16:25:22 MainProcess _training_0 _base __init__ DEBUG Initializing Timelapse: model: <plugins.train.model.original.Model object at 0x000001C337F73BC8>, use_mask: False, coverage_ratio: 0.6875, image_count: 14, batchers: '{'a': <plugins.train.trainer._base.Batcher object at 0x000001C3F1652748>, 'b': <plugins.train.trainer._base.Batcher object at 0x000001C3F1652448>}')
08/06/2020 16:25:22 MainProcess _training_0 _base __init__ DEBUG Initializing Samples: model: '<plugins.train.model.original.Model object at 0x000001C337F73BC8>', use_mask: False, coverage_ratio: 0.6875)
08/06/2020 16:25:22 MainProcess _training_0 _base __init__ DEBUG Initialized Samples
08/06/2020 16:25:22 MainProcess _training_0 _base __init__ DEBUG Initialized Timelapse
08/06/2020 16:25:22 MainProcess _training_0 _base __init__ DEBUG Initialized Trainer
08/06/2020 16:25:22 MainProcess _training_0 train _load_trainer DEBUG Loaded Trainer
08/06/2020 16:25:22 MainProcess _training_0 train _run_training_cycle DEBUG Running Training Cycle
08/06/2020 16:25:22 MainProcess _run_0 training_data initialize DEBUG Initializing constants. training_size: 256
08/06/2020 16:25:22 MainProcess _run_0 training_data initialize DEBUG Initialized constants: {'clahe_base_contrast': 2, 'tgt_slices': slice(40, 216, None), 'warp_mapx': '[[[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]]', 'warp_mapy': '[[[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]]', 'warp_pad': 80, 'warp_slices': slice(8, -8, None), 'warp_lm_edge_anchors': '[[[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]]', 'warp_lm_grids': '[[[ 0. 0. 0. ... 0. 0. 0.]\n [ 1. 1. 1. ... 1. 1. 1.]\n [ 2. 2. 2. ... 2. 2. 2.]\n ...\n [253. 253. 253. ... 253. 253. 253.]\n [254. 254. 254. ... 254. 254. 254.]\n [255. 255. 255. ... 255. 255. 255.]]\n\n [[ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n ...\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]]]'}
08/06/2020 16:25:22 MainProcess _run_0 training_data initialize DEBUG Initializing constants. training_size: 265
08/06/2020 16:25:22 MainProcess _run_1 training_data initialize DEBUG Initializing constants. training_size: 265
08/06/2020 16:25:22 MainProcess _run_1 training_data initialize DEBUG Initialized constants: {'clahe_base_contrast': 2, 'tgt_slices': slice(41, 223, None), 'warp_mapx': '[[[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]]', 'warp_mapy': '[[[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]]', 'warp_pad': 80, 'warp_slices': slice(8, -8, None), 'warp_lm_edge_anchors': '[[[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]]', 'warp_lm_grids': '[[[ 0. 0. 0. ... 0. 0. 0.]\n [ 1. 1. 1. ... 1. 1. 1.]\n [ 2. 2. 2. ... 2. 2. 2.]\n ...\n [262. 262. 262. ... 262. 262. 262.]\n [263. 263. 263. ... 263. 263. 263.]\n [264. 264. 264. ... 264. 264. 264.]]\n\n [[ 0. 1. 2. ... 262. 263. 264.]\n [ 0. 1. 2. ... 262. 263. 264.]\n [ 0. 1. 2. ... 262. 263. 264.]\n ...\n [ 0. 1. 2. ... 262. 263. 264.]\n [ 0. 1. 2. ... 262. 263. 264.]\n [ 0. 1. 2. ... 262. 263. 264.]]]'}
08/06/2020 16:25:22 MainProcess _run_0 training_data initialize DEBUG Initialized constants: {'clahe_base_contrast': 2, 'tgt_slices': slice(41, 223, None), 'warp_mapx': '[[[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]]', 'warp_mapy': '[[[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]]', 'warp_pad': 80, 'warp_slices': slice(8, -8, None), 'warp_lm_edge_anchors': '[[[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]]', 'warp_lm_grids': '[[[ 0. 0. 0. ... 0. 0. 0.]\n [ 1. 1. 1. ... 1. 1. 1.]\n [ 2. 2. 2. ... 2. 2. 2.]\n ...\n [262. 262. 262. ... 262. 262. 262.]\n [263. 263. 263. ... 263. 263. 263.]\n [264. 264. 264. ... 264. 264. 264.]]\n\n [[ 0. 1. 2. ... 262. 263. 264.]\n [ 0. 1. 2. ... 262. 263. 264.]\n [ 0. 1. 2. ... 262. 263. 264.]\n ...\n [ 0. 1. 2. ... 262. 263. 264.]\n [ 0. 1. 2. ... 262. 263. 264.]\n [ 0. 1. 2. ... 262. 263. 264.]]]'}
08/06/2020 16:25:22 MainProcess _run_1 training_data initialize DEBUG Initializing constants. training_size: 265
08/06/2020 16:25:22 MainProcess _run_1 training_data initialize DEBUG Initialized constants: {'clahe_base_contrast': 2, 'tgt_slices': slice(41, 223, None), 'warp_mapx': '[[[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]\n\n [[ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]\n [ 41. 86.5 132. 177.5 223. ]]]', 'warp_mapy': '[[[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]\n\n [[ 41. 41. 41. 41. 41. ]\n [ 86.5 86.5 86.5 86.5 86.5]\n [132. 132. 132. 132. 132. ]\n [177.5 177.5 177.5 177.5 177.5]\n [223. 223. 223. 223. 223. ]]]', 'warp_pad': 80, 'warp_slices': slice(8, -8, None), 'warp_lm_edge_anchors': '[[[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]\n\n [[ 0 0]\n [ 0 264]\n [264 264]\n [264 0]\n [131 0]\n [131 264]\n [264 131]\n [ 0 131]]]', 'warp_lm_grids': '[[[ 0. 0. 0. ... 0. 0. 0.]\n [ 1. 1. 1. ... 1. 1. 1.]\n [ 2. 2. 2. ... 2. 2. 2.]\n ...\n [262. 262. 262. ... 262. 262. 262.]\n [263. 263. 263. ... 263. 263. 263.]\n [264. 264. 264. ... 264. 264. 264.]]\n\n [[ 0. 1. 2. ... 262. 263. 264.]\n [ 0. 1. 2. ... 262. 263. 264.]\n [ 0. 1. 2. ... 262. 263. 264.]\n ...\n [ 0. 1. 2. ... 262. 263. 264.]\n [ 0. 1. 2. ... 262. 263. 264.]\n [ 0. 1. 2. ... 262. 263. 264.]]]'}
08/06/2020 16:25:22 MainProcess _run_1 training_data initialize DEBUG Initializing constants. training_size: 256
08/06/2020 16:25:22 MainProcess _run_1 training_data initialize DEBUG Initialized constants: {'clahe_base_contrast': 2, 'tgt_slices': slice(40, 216, None), 'warp_mapx': '[[[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]]', 'warp_mapy': '[[[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]]', 'warp_pad': 80, 'warp_slices': slice(8, -8, None), 'warp_lm_edge_anchors': '[[[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]]', 'warp_lm_grids': '[[[ 0. 0. 0. ... 0. 0. 0.]\n [ 1. 1. 1. ... 1. 1. 1.]\n [ 2. 2. 2. ... 2. 2. 2.]\n ...\n [253. 253. 253. ... 253. 253. 253.]\n [254. 254. 254. ... 254. 254. 254.]\n [255. 255. 255. ... 255. 255. 255.]]\n\n [[ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n ...\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]]]'}
08/06/2020 16:25:23 MainProcess _training_0 module_wrapper _tfmw_add_deprecation_warning DEBUG From C:\Users\michalek\MiniConda3\envs\faceswap\lib\site-packages\keras\backend\tensorflow_backend.py:986: The name tf.assign_add is deprecated. Please use tf.compat.v1.assign_add instead.\n
08/06/2020 16:25:23 MainProcess _training_0 module_wrapper _tfmw_add_deprecation_warning DEBUG From C:\Users\michalek\MiniConda3\envs\faceswap\lib\site-packages\keras\backend\tensorflow_backend.py:973: The name tf.assign is deprecated. Please use tf.compat.v1.assign instead.\n
08/06/2020 16:25:31 MainProcess _training_0 _base generate_preview DEBUG Generating preview
08/06/2020 16:25:31 MainProcess _training_0 _base largest_face_index DEBUG 0
08/06/2020 16:25:31 MainProcess _training_0 _base compile_sample DEBUG Compiling samples: (side: 'a', samples: 14)
08/06/2020 16:25:36 MainProcess _training_0 _base generate_preview DEBUG Generating preview
08/06/2020 16:25:36 MainProcess _training_0 _base largest_face_index DEBUG 0
08/06/2020 16:25:36 MainProcess _training_0 _base compile_sample DEBUG Compiling samples: (side: 'b', samples: 14)
08/06/2020 16:25:36 MainProcess _training_0 _base show_sample DEBUG Showing sample
08/06/2020 16:25:36 MainProcess _training_0 _base _get_predictions DEBUG Getting Predictions
08/06/2020 16:25:37 MainProcess _training_0 _base _get_predictions DEBUG Returning predictions: {'a_a': (14, 64, 64, 3), 'b_a': (14, 64, 64, 3), 'a_b': (14, 64, 64, 3), 'b_b': (14, 64, 64, 3)}
08/06/2020 16:25:37 MainProcess _training_0 _base _to_full_frame DEBUG side: 'a', number of sample arrays: 3, prediction.shapes: [(14, 64, 64, 3), (14, 64, 64, 3)])
08/06/2020 16:25:37 MainProcess _training_0 _base _frame_overlay DEBUG full_size: 256, target_size: 176, color: (0, 0, 255)
08/06/2020 16:25:37 MainProcess _training_0 _base _frame_overlay DEBUG Overlayed background. Shape: (14, 256, 256, 3)
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 64, 64, 3), target_size: 176, scale: 2.75)
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 176, 176, 3))
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 64, 64, 3), target_size: 176, scale: 2.75)
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 176, 176, 3))
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 64, 64, 3), target_size: 176, scale: 2.75)
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 176, 176, 3))
08/06/2020 16:25:37 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 256, 256, 3)
08/06/2020 16:25:37 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 256, 256, 3)
08/06/2020 16:25:37 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 256, 256, 3)
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 256, 256, 3), target_size: 128, scale: 0.5)
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 128, 128, 3))
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 256, 256, 3), target_size: 128, scale: 0.5)
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 128, 128, 3))
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 256, 256, 3), target_size: 128, scale: 0.5)
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 128, 128, 3))
08/06/2020 16:25:37 MainProcess _training_0 _base _get_headers DEBUG side: 'a', width: 128
08/06/2020 16:25:37 MainProcess _training_0 _base _get_headers DEBUG height: 32, total_width: 384
08/06/2020 16:25:37 MainProcess _training_0 _base _get_headers DEBUG texts: ['Original (A)', 'Original > Original', 'Original > Swap'], text_sizes: [(72, 9), (116, 9), (102, 9)], text_x: [28, 134, 269], text_y: 20
08/06/2020 16:25:37 MainProcess _training_0 _base _get_headers DEBUG header_box.shape: (32, 384, 3)
08/06/2020 16:25:37 MainProcess _training_0 _base _to_full_frame DEBUG side: 'b', number of sample arrays: 3, prediction.shapes: [(14, 64, 64, 3), (14, 64, 64, 3)])
08/06/2020 16:25:37 MainProcess _training_0 _base _frame_overlay DEBUG full_size: 265, target_size: 182, color: (0, 0, 255)
08/06/2020 16:25:37 MainProcess _training_0 _base _frame_overlay DEBUG Overlayed background. Shape: (14, 265, 190, 3)
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 64, 64, 3), target_size: 182, scale: 2.84375)
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 182, 182, 3))
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 64, 64, 3), target_size: 182, scale: 2.84375)
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 182, 182, 3))
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 64, 64, 3), target_size: 182, scale: 2.84375)
08/06/2020 16:25:37 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 182, 182, 3))
08/06/2020 16:25:37 MainProcess _training_0 multithreading run DEBUG Error in thread (_training_0): could not broadcast input array from shape (182,182,3) into shape (182,149,3)
08/06/2020 16:25:38 MainProcess MainThread train _monitor DEBUG Thread error detected
08/06/2020 16:25:38 MainProcess MainThread train _monitor DEBUG Closed Monitor
08/06/2020 16:25:38 MainProcess MainThread train _end_thread DEBUG Ending Training thread
08/06/2020 16:25:38 MainProcess MainThread train _end_thread CRITICAL Error caught! Exiting...
08/06/2020 16:25:38 MainProcess MainThread multithreading join DEBUG Joining Threads: '_training'
08/06/2020 16:25:38 MainProcess MainThread multithreading join DEBUG Joining Thread: '_training_0'
08/06/2020 16:25:38 MainProcess MainThread multithreading join ERROR Caught exception in thread: '_training_0'
Traceback (most recent call last):
File "C:\Users\michalek\faceswap\lib\cli\launcher.py", line 155, in execute_script
process.process()
File "C:\Users\michalek\faceswap\scripts\train.py", line 161, in process
self._end_thread(thread, err)
File "C:\Users\michalek\faceswap\scripts\train.py", line 201, in _end_thread
thread.join()
File "C:\Users\michalek\faceswap\lib\multithreading.py", line 121, in join
raise thread.err[1].with_traceback(thread.err[2])
File "C:\Users\michalek\faceswap\lib\multithreading.py", line 37, in run
self._target(*self._args, **self._kwargs)
File "C:\Users\michalek\faceswap\scripts\train.py", line 226, in _training
raise err
File "C:\Users\michalek\faceswap\scripts\train.py", line 216, in _training
self._run_training_cycle(model, trainer)
File "C:\Users\michalek\faceswap\scripts\train.py", line 305, in _run_training_cycle
trainer.train_one_step(viewer, timelapse)
File "C:\Users\michalek\faceswap\plugins\train\trainer\_base.py", line 316, in train_one_step
raise err
File "C:\Users\michalek\faceswap\plugins\train\trainer\_base.py", line 306, in train_one_step
samples = self._samples.show_sample()
File "C:\Users\michalek\faceswap\plugins\train\trainer\_base.py", line 635, in show_sample
display = self._to_full_frame(side, samples, predictions)
File "C:\Users\michalek\faceswap\plugins\train\trainer\_base.py", line 736, in _to_full_frame
images = [self._overlay_foreground(frame, image) for image in images]
File "C:\Users\michalek\faceswap\plugins\train\trainer\_base.py", line 736, in <listcomp>
images = [self._overlay_foreground(frame, image) for image in images]
File "C:\Users\michalek\faceswap\plugins\train\trainer\_base.py", line 828, in _overlay_foreground
offset:offset + foregrounds[idx].shape[1], :3] = foregrounds[idx]
ValueError: could not broadcast input array from shape (182,182,3) into shape (182,149,3)
============ System Information ============
encoding: cp1252
git_branch: master
git_commits: 3fd26b5 Manual Tool (#1038)
gpu_cuda: 11.0
gpu_cudnn: No global version found. Check Conda packages for Conda cuDNN
gpu_devices: GPU_0: GeForce GTX 1050 Ti
gpu_devices_active: GPU_0
gpu_driver: 451.48
gpu_vram: GPU_0: 4096MB
os_machine: AMD64
os_platform: Windows-10-10.0.19041-SP0
os_release: 10
py_command: C:\Users\michalek\faceswap\faceswap.py train -A E:/deepfake/faceexport -B E:/deepfake/face2 -m E:/deepfake/model burger -t original -bs 32 -it 1000000 -g 1 -s 100 -ss 25000 -ps 50 -L INFO -gui
py_conda_version: conda 4.8.3
py_implementation: CPython
py_version: 3.7.7
py_virtual_env: True
sys_cores: 4
sys_processor: Intel64 Family 6 Model 94 Stepping 3, GenuineIntel
sys_ram: Total: 8082MB, Available: 3350MB, Used: 4731MB, Free: 3350MB
=============== Pip Packages ===============
absl-py==0.9.0
astor==0.8.0
blinker==1.4
brotlipy==0.7.0
cachetools==4.1.0
certifi==2020.6.20
cffi==1.14.0
chardet==3.0.4
click==7.1.2
cloudpickle @ file:///tmp/build/80754af9/cloudpickle_1594141588948/work
cryptography==2.9.2
cycler==0.10.0
cytoolz==0.10.1
dask @ file:///tmp/build/80754af9/dask-core_1594156306305/work
decorator==4.4.2
fastcluster==1.1.26
ffmpy==0.2.3
gast==0.2.2
google-auth @ file:///tmp/build/80754af9/google-auth_1594357566944/work
google-auth-oauthlib==0.4.1
google-pasta==0.2.0
grpcio==1.27.2
h5py==2.10.0
idna @ file:///tmp/build/80754af9/idna_1593446292537/work
imageio @ file:///tmp/build/80754af9/imageio_1594161405741/work
imageio-ffmpeg @ file:///home/conda/feedstock_root/build_artifacts/imageio-ffmpeg_1589202782679/work
joblib @ file:///tmp/build/80754af9/joblib_1594236160679/work
Keras==2.2.4
Keras-Applications @ file:///tmp/build/80754af9/keras-applications_1594366238411/work
Keras-Preprocessing==1.1.0
kiwisolver==1.2.0
Markdown==3.1.1
matplotlib @ file:///C:/ci/matplotlib-base_1592846084747/work
mkl-fft==1.1.0
mkl-random==1.1.1
mkl-service==2.3.0
networkx @ file:///tmp/build/80754af9/networkx_1594377231366/work
numpy @ file:///C:/ci/numpy_and_numpy_base_1596233945180/work
nvidia-ml-py3 @ git+https://github.com/deepfakes/nvidia-ml-py3.git@6fc29ac84b32bad877f078cb4a777c1548a00bf6
oauthlib==3.1.0
olefile==0.46
opencv-python==4.3.0.36
opt-einsum==3.1.0
Pillow @ file:///C:/ci/pillow_1594298234712/work
protobuf==3.12.3
psutil==5.7.0
pyasn1==0.4.8
pyasn1-modules==0.2.7
pycparser @ file:///tmp/build/80754af9/pycparser_1594388511720/work
PyJWT==1.7.1
pyOpenSSL @ file:///tmp/build/80754af9/pyopenssl_1594392929924/work
pyparsing==2.4.7
pyreadline==2.1
PySocks @ file:///C:/ci/pysocks_1594394709107/work
python-dateutil==2.8.1
PyWavelets==1.1.1
pywin32==227
PyYAML==5.3.1
requests @ file:///tmp/build/80754af9/requests_1592841827918/work
requests-oauthlib==1.3.0
rsa==4.0
scikit-image==0.16.2
scikit-learn @ file:///C:/ci/scikit-learn_1592847564598/work
scipy @ file:///C:/ci/scipy_1592916958183/work
six==1.15.0
tensorboard==2.2.1
tensorboard-plugin-wit==1.6.0
tensorflow==1.15.0
tensorflow-estimator==1.15.1
termcolor==1.1.0
threadpoolctl @ file:///tmp/tmp9twdgx9k/threadpoolctl-2.1.0-py3-none-any.whl
toolz==0.10.0
toposort==1.5
tornado==6.0.4
tqdm @ file:///tmp/build/80754af9/tqdm_1593446365756/work
urllib3==1.25.9
Werkzeug==0.16.1
win-inet-pton==1.1.0
wincertstore==0.2
wrapt==1.12.1
============== Conda Packages ==============
# packages in environment at C:\Users\michalek\MiniConda3\envs\faceswap:
#
# Name Version Build Channel
_tflow_select 2.1.0 gpu
absl-py 0.9.0 py37_0
astor 0.8.0 py37_0
blas 1.0 mkl
blinker 1.4 py37_0
brotlipy 0.7.0 py37he774522_1000
ca-certificates 2020.6.24 0
cachetools 4.1.0 py_1
certifi 2020.6.20 py37_0
cffi 1.14.0 py37h7a1dbc1_0
chardet 3.0.4 py37_1003
click 7.1.2 py_0
cloudpickle 1.5.0 py_0
cryptography 2.9.2 py37h7a1dbc1_0
cudatoolkit 10.0.130 0
cudnn 7.6.5 cuda10.0_0
cycler 0.10.0 py37_0
cytoolz 0.10.1 py37he774522_0
dask-core 2.20.0 py_0
decorator 4.4.2 py_0
fastcluster 1.1.26 py37h9b59f54_1 conda-forge
ffmpeg 4.3 ha925a31_1 conda-forge
ffmpy 0.2.3 pypi_0 pypi
freetype 2.10.2 hd328e21_0
gast 0.2.2 py37_0
git 2.23.0 h6bb4b03_0
google-auth 1.17.2 py_0
google-auth-oauthlib 0.4.1 py_2
google-pasta 0.2.0 py_0
grpcio 1.27.2 py37h351948d_0
h5py 2.10.0 py37h5e291fa_0
hdf5 1.10.4 h7ebc959_0
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha925a31_3
idna 2.10 py_0
imageio 2.9.0 py_0
imageio-ffmpeg 0.4.2 py_0 conda-forge
intel-openmp 2020.1 216
joblib 0.16.0 py_0
jpeg 9b hb83a4c4_2
keras 2.2.4 0
keras-applications 1.0.8 py_1
keras-base 2.2.4 py37_0
keras-preprocessing 1.1.0 py_1
kiwisolver 1.2.0 py37h74a9793_0
libpng 1.6.37 h2a8f88b_0
libprotobuf 3.12.3 h7bd577a_0
libtiff 4.1.0 h56a325e_1
lz4-c 1.9.2 h62dcd97_1
markdown 3.1.1 py37_0
matplotlib 3.2.2 0
matplotlib-base 3.2.2 py37h64f37c6_0
mkl 2020.1 216
mkl-service 2.3.0 py37hb782905_0
mkl_fft 1.1.0 py37h45dec08_0
mkl_random 1.1.1 py37h47e9c7a_0
networkx 2.4 py_1
numpy 1.19.1 py37h5510c5b_0
numpy-base 1.19.1 py37ha3acd2a_0
nvidia-ml-py3 7.352.1 pypi_0 pypi
oauthlib 3.1.0 py_0
olefile 0.46 py37_0
opencv-python 4.3.0.36 pypi_0 pypi
openssl 1.1.1g he774522_0
opt_einsum 3.1.0 py_0
pathlib 1.0.1 py37_2
pillow 7.2.0 py37hcc1f983_0
pip 20.1.1 py37_1
protobuf 3.12.3 py37h33f27b4_0
psutil 5.7.0 py37he774522_0
pyasn1 0.4.8 py_0
pyasn1-modules 0.2.7 py_0
pycparser 2.20 py_2
pyjwt 1.7.1 py37_0
pyopenssl 19.1.0 py_1
pyparsing 2.4.7 py_0
pyqt 5.9.2 py37h6538335_2
pyreadline 2.1 py37_1
pysocks 1.7.1 py37_1
python 3.7.7 h81c818b_4
python-dateutil 2.8.1 py_0
python_abi 3.7 1_cp37m conda-forge
pywavelets 1.1.1 py37he774522_0
pywin32 227 py37he774522_1
pyyaml 5.3.1 py37he774522_1
qt 5.9.7 vc14h73c81de_0
requests 2.24.0 py_0
requests-oauthlib 1.3.0 py_0
rsa 4.0 py_0
scikit-image 0.16.2 py37h47e9c7a_0
scikit-learn 0.23.1 py37h25d0782_0
scipy 1.5.0 py37h9439919_0
setuptools 49.2.0 py37_0
sip 4.19.8 py37h6538335_0
six 1.15.0 py_0
sqlite 3.32.3 h2a8f88b_0
tensorboard 2.2.1 pyh532a8cf_0
tensorboard-plugin-wit 1.6.0 py_0
tensorflow 1.15.0 gpu_py37hc3743a6_0
tensorflow-base 1.15.0 gpu_py37h1afeea4_0
tensorflow-estimator 1.15.1 pyh2649769_0
tensorflow-gpu 1.15.0 h0d30ee6_0
termcolor 1.1.0 py37_1
threadpoolctl 2.1.0 pyh5ca1d4c_0
tk 8.6.10 he774522_0
toolz 0.10.0 py_0
toposort 1.5 py_3 conda-forge
tornado 6.0.4 py37he774522_1
tqdm 4.47.0 py_0
urllib3 1.25.9 py_0
vc 14.1 h0510ff6_4
vs2015_runtime 14.16.27012 hf0eaf9b_3
werkzeug 0.16.1 py_0
wheel 0.34.2 py37_0
win_inet_pton 1.1.0 py37_0
wincertstore 0.2 py37_0
wrapt 1.12.1 py37he774522_1
xz 5.2.5 h62dcd97_0
yaml 0.2.5 he774522_0
zlib 1.2.11 h62dcd97_4
zstd 1.4.5 h04227a9_0
================= Configs ==================
--------- .faceswap ---------
backend: nvidia
--------- convert.ini ---------
[color.color_transfer]
clip: True
preserve_paper: True
[color.manual_balance]
colorspace: HSV
balance_1: 0.0
balance_2: 0.0
balance_3: 0.0
contrast: 0.0
brightness: 0.0
[color.match_hist]
threshold: 99.0
[mask.box_blend]
type: gaussian
distance: 11.0
radius: 5.0
passes: 1
[mask.mask_blend]
type: normalized
kernel_size: 3
passes: 4
threshold: 4
erosion: 0.0
[scaling.sharpen]
method: unsharp_mask
amount: 150
radius: 0.3
threshold: 5.0
[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
[writer.pillow]
format: png
draw_transparent: False
optimize: False
gif_interlace: True
jpg_quality: 75
png_compress_level: 3
tif_compression: tiff_deflate
--------- extract.ini ---------
[global]
allow_growth: False
[align.fan]
batch-size: 12
[detect.cv2_dnn]
confidence: 50
[detect.mtcnn]
minsize: 20
threshold_1: 0.6
threshold_2: 0.7
threshold_3: 0.7
scalefactor: 0.709
batch-size: 8
[detect.s3fd]
confidence: 70
batch-size: 4
[mask.unet_dfl]
batch-size: 8
[mask.vgg_clear]
batch-size: 6
[mask.vgg_obstructed]
batch-size: 2
--------- 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
--------- 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
reflect_padding: False
penalized_mask_loss: True
loss_function: mae
learning_rate: 5e-05
[model.dfl_h128]
lowmem: False
[model.dfl_sae]
input_size: 128
clipnorm: True
architecture: df
autoencoder_dims: 0
encoder_dims: 42
decoder_dims: 21
multiscale_decoder: False
[model.dlight]
features: best
details: good
output_size: 256
[model.original]
lowmem: False
[model.realface]
input_size: 64
output_size: 128
dense_nodes: 1536
complexity_encoder: 128
complexity_decoder: 512
[model.unbalanced]
input_size: 128
lowmem: False
clipnorm: True
nodes: 1024
complexity_encoder: 128
complexity_decoder_a: 384
complexity_decoder_b: 512
[model.villain]
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