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msgstr ""
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#: lib/cli/args.py:193 lib/cli/args.py:203 lib/cli/args.py:211
#: lib/cli/args.py:221
msgid "Global Options"
msgstr ""

#: lib/cli/args.py:194
msgid ""
"R|Exclude GPUs from use by Faceswap. Select the number(s) which correspond "
"to any GPU(s) that you do not wish to be made available to Faceswap. "
"Selecting all GPUs here will force Faceswap into CPU mode.\n"
"L|{}"
msgstr ""

#: lib/cli/args.py:204
msgid ""
"Optionally overide the saved config with the path to a custom config file."
msgstr ""

#: lib/cli/args.py:212
msgid ""
"Log level. Stick with INFO or VERBOSE unless you need to file an error "
"report. Be careful with TRACE as it will generate a lot of data"
msgstr ""

#: lib/cli/args.py:222
msgid "Path to store the logfile. Leave blank to store in the faceswap folder"
msgstr ""

#: lib/cli/args.py:320 lib/cli/args.py:329 lib/cli/args.py:337
#: lib/cli/args.py:386 lib/cli/args.py:677 lib/cli/args.py:686
msgid "Data"
msgstr ""

#: lib/cli/args.py:321
msgid ""
"Input directory or video. Either a directory containing the image files you "
"wish to process or path to a video file. NB: This should be the source video/"
"frames NOT the source faces."
msgstr ""

#: lib/cli/args.py:330
msgid "Output directory. This is where the converted files will be saved."
msgstr ""

#: lib/cli/args.py:338
msgid ""
"Optional path to an alignments file. Leave blank if the alignments file is "
"at the default location."
msgstr ""

#: lib/cli/args.py:361
msgid ""
"Extract faces from image or video sources.\n"
"Extraction plugins can be configured in the 'Settings' Menu"
msgstr ""

#: lib/cli/args.py:387
msgid ""
"R|If selected then the input_dir should be a parent folder containing "
"multiple videos and/or folders of images you wish to extract from. The faces "
"will be output to separate sub-folders in the output_dir."
msgstr ""

#: lib/cli/args.py:396 lib/cli/args.py:412 lib/cli/args.py:424
#: lib/cli/args.py:463 lib/cli/args.py:481 lib/cli/args.py:493
#: lib/cli/args.py:502 lib/cli/args.py:511 lib/cli/args.py:696
#: lib/cli/args.py:723 lib/cli/args.py:761
msgid "Plugins"
msgstr ""

#: lib/cli/args.py:397
msgid ""
"R|Detector to use. Some of these have configurable settings in '/config/"
"extract.ini' or 'Settings > Configure Extract 'Plugins':\n"
"L|cv2-dnn: A CPU only extractor which is the least reliable and least "
"resource intensive. Use this if not using a GPU and time is important.\n"
"L|mtcnn: Good detector. Fast on CPU, faster on GPU. Uses fewer resources "
"than other GPU detectors but can often return more false positives.\n"
"L|s3fd: Best detector. Slow on CPU, faster on GPU. Can detect more faces and "
"fewer false positives than other GPU detectors, but is a lot more resource "
"intensive."
msgstr ""

#: lib/cli/args.py:413
msgid ""
"R|Aligner to use.\n"
"L|cv2-dnn: A CPU only landmark detector. Faster, less resource intensive, "
"but less accurate. Only use this if not using a GPU and time is important.\n"
"L|fan: Best aligner. Fast on GPU, slow on CPU."
msgstr ""

#: lib/cli/args.py:425
msgid ""
"R|Additional Masker(s) to use. The masks generated here will all take up GPU "
"RAM. You can select none, one or multiple masks, but the extraction may take "
"longer the more you select. NB: The Extended and Components (landmark based) "
"masks are automatically generated on extraction.\n"
"L|bisenet-fp: Relatively lightweight NN based mask that provides more "
"refined control over the area to be masked including full head masking "
"(configurable in mask settings).\n"
"L|custom: A dummy mask that fills the mask area with all 1s or 0s "
"(configurable in settings). This is only required if you intend to manually "
"edit the custom masks yourself in the manual tool. This mask does not use "
"the GPU so will not use any additional VRAM.\n"
"L|vgg-clear: Mask designed to provide smart segmentation of mostly frontal "
"faces clear of obstructions. Profile faces and obstructions may result in "
"sub-par performance.\n"
"L|vgg-obstructed: Mask designed to provide smart segmentation of mostly "
"frontal faces. The mask model has been specifically trained to recognize "
"some facial obstructions (hands and eyeglasses). Profile faces may result in "
"sub-par performance.\n"
"L|unet-dfl: Mask designed to provide smart segmentation of mostly frontal "
"faces. The mask model has been trained by community members and will need "
"testing for further description. Profile faces may result in sub-par "
"performance.\n"
"The auto generated masks are as follows:\n"
"L|components: Mask designed to provide facial segmentation based on the "
"positioning of landmark locations. A convex hull is constructed around the "
"exterior of the landmarks to create a mask.\n"
"L|extended: Mask designed to provide facial segmentation based on the "
"positioning of landmark locations. A convex hull is constructed around the "
"exterior of the landmarks and the mask is extended upwards onto the "
"forehead.\n"
"(eg: `-M unet-dfl vgg-clear`, `--masker vgg-obstructed`)"
msgstr ""

#: lib/cli/args.py:464
msgid ""
"R|Performing normalization can help the aligner better align faces with "
"difficult lighting conditions at an extraction speed cost. Different methods "
"will yield different results on different sets. NB: This does not impact the "
"output face, just the input to the aligner.\n"
"L|none: Don't perform normalization on the face.\n"
"L|clahe: Perform Contrast Limited Adaptive Histogram Equalization on the "
"face.\n"
"L|hist: Equalize the histograms on the RGB channels.\n"
"L|mean: Normalize the face colors to the mean."
msgstr ""

#: lib/cli/args.py:482
msgid ""
"The number of times to re-feed the detected face into the aligner. Each time "
"the face is re-fed into the aligner the bounding box is adjusted by a small "
"amount. The final landmarks are then averaged from each iteration. Helps to "
"remove 'micro-jitter' but at the cost of slower extraction speed. The more "
"times the face is re-fed into the aligner, the less micro-jitter should "
"occur but the longer extraction will take."
msgstr ""

#: lib/cli/args.py:494
msgid ""
"Re-feed the initially found aligned face through the aligner. Can help "
"produce better alignments for faces that are rotated beyond 45 degrees in "
"the frame or are at extreme angles. Slows down extraction."
msgstr ""

#: lib/cli/args.py:503
msgid ""
"If a face isn't found, rotate the images to try to find a face. Can find "
"more faces at the cost of extraction speed. Pass in a single number to use "
"increments of that size up to 360, or pass in a list of numbers to enumerate "
"exactly what angles to check."
msgstr ""

#: lib/cli/args.py:512
msgid ""
"Obtain and store face identity encodings from VGGFace2. Slows down extract a "
"little, but will save time if using 'sort by face'"
msgstr ""

#: lib/cli/args.py:522 lib/cli/args.py:532 lib/cli/args.py:544
#: lib/cli/args.py:557 lib/cli/args.py:798 lib/cli/args.py:812
#: lib/cli/args.py:825 lib/cli/args.py:839
msgid "Face Processing"
msgstr ""

#: lib/cli/args.py:523
msgid ""
"Filters out faces detected below this size. Length, in pixels across the "
"diagonal of the bounding box. Set to 0 for off"
msgstr ""

#: lib/cli/args.py:533
msgid ""
"Optionally filter out people who you do not wish to extract by passing in "
"images of those people. Should be a small variety of images at different "
"angles and in different conditions. A folder containing the required images "
"or multiple image files, space separated, can be selected."
msgstr ""

#: lib/cli/args.py:545
msgid ""
"Optionally select people you wish to extract by passing in images of that "
"person. Should be a small variety of images at different angles and in "
"different conditions A folder containing the required images or multiple "
"image files, space separated, can be selected."
msgstr ""

#: lib/cli/args.py:558
msgid ""
"For use with the optional nfilter/filter files. Threshold for positive face "
"recognition. Higher values are stricter."
msgstr ""

#: lib/cli/args.py:567 lib/cli/args.py:579 lib/cli/args.py:591
#: lib/cli/args.py:603
msgid "output"
msgstr ""

#: lib/cli/args.py:568
msgid ""
"The output size of extracted faces. Make sure that the model you intend to "
"train supports your required size. This will only need to be changed for hi-"
"res models."
msgstr ""

#: lib/cli/args.py:580
msgid ""
"Extract every 'nth' frame. This option will skip frames when extracting "
"faces. For example a value of 1 will extract faces from every frame, a value "
"of 10 will extract faces from every 10th frame."
msgstr ""

#: lib/cli/args.py:592
msgid ""
"Automatically save the alignments file after a set amount of frames. By "
"default the alignments file is only saved at the end of the extraction "
"process. NB: If extracting in 2 passes then the alignments file will only "
"start to be saved out during the second pass. WARNING: Don't interrupt the "
"script when writing the file because it might get corrupted. Set to 0 to "
"turn off"
msgstr ""

#: lib/cli/args.py:604
msgid "Draw landmarks on the ouput faces for debugging purposes."
msgstr ""

#: lib/cli/args.py:610 lib/cli/args.py:619 lib/cli/args.py:627
#: lib/cli/args.py:634 lib/cli/args.py:852 lib/cli/args.py:863
#: lib/cli/args.py:871 lib/cli/args.py:890 lib/cli/args.py:896
msgid "settings"
msgstr ""

#: lib/cli/args.py:611
msgid ""
"Don't run extraction in parallel. Will run each part of the extraction "
"process separately (one after the other) rather than all at the smae time. "
"Useful if VRAM is at a premium."
msgstr ""

#: lib/cli/args.py:620
msgid ""
"Skips frames that have already been extracted and exist in the alignments "
"file"
msgstr ""

#: lib/cli/args.py:628
msgid "Skip frames that already have detected faces in the alignments file"
msgstr ""

#: lib/cli/args.py:635
msgid "Skip saving the detected faces to disk. Just create an alignments file"
msgstr ""

#: lib/cli/args.py:657
msgid ""
"Swap the original faces in a source video/images to your final faces.\n"
"Conversion plugins can be configured in the 'Settings' Menu"
msgstr ""

#: lib/cli/args.py:678
msgid ""
"Only required if converting from images to video. Provide The original video "
"that the source frames were extracted from (for extracting the fps and "
"audio)."
msgstr ""

#: lib/cli/args.py:687
msgid ""
"Model directory. The directory containing the trained model you wish to use "
"for conversion."
msgstr ""

#: lib/cli/args.py:697
msgid ""
"R|Performs color adjustment to the swapped face. Some of these options have "
"configurable settings in '/config/convert.ini' or 'Settings > Configure "
"Convert Plugins':\n"
"L|avg-color: Adjust the mean of each color channel in the swapped "
"reconstruction to equal the mean of the masked area in the original image.\n"
"L|color-transfer: Transfers the color distribution from the source to the "
"target image using the mean and standard deviations of the L*a*b* color "
"space.\n"
"L|manual-balance: Manually adjust the balance of the image in a variety of "
"color spaces. Best used with the Preview tool to set correct values.\n"
"L|match-hist: Adjust the histogram of each color channel in the swapped "
"reconstruction to equal the histogram of the masked area in the original "
"image.\n"
"L|seamless-clone: Use cv2's seamless clone function to remove extreme "
"gradients at the mask seam by smoothing colors. Generally does not give very "
"satisfactory results.\n"
"L|none: Don't perform color adjustment."
msgstr ""

#: lib/cli/args.py:724
msgid ""
"R|Masker to use. NB: The mask you require must exist within the alignments "
"file. You can add additional masks with the Mask Tool.\n"
"L|none: Don't use a mask.\n"
"L|bisenet-fp_face: Relatively lightweight NN based mask that provides more "
"refined control over the area to be masked (configurable in mask settings). "
"Use this version of bisenet-fp if your model is trained with 'face' or "
"'legacy' centering.\n"
"L|bisenet-fp_head: Relatively lightweight NN based mask that provides more "
"refined control over the area to be masked (configurable in mask settings). "
"Use this version of bisenet-fp if your model is trained with 'head' "
"centering.\n"
"L|custom_face: Custom user created, face centered mask.\n"
"L|custom_head: Custom user created, head centered mask.\n"
"L|components: Mask designed to provide facial segmentation based on the "
"positioning of landmark locations. A convex hull is constructed around the "
"exterior of the landmarks to create a mask.\n"
"L|extended: Mask designed to provide facial segmentation based on the "
"positioning of landmark locations. A convex hull is constructed around the "
"exterior of the landmarks and the mask is extended upwards onto the "
"forehead.\n"
"L|vgg-clear: Mask designed to provide smart segmentation of mostly frontal "
"faces clear of obstructions. Profile faces and obstructions may result in "
"sub-par performance.\n"
"L|vgg-obstructed: Mask designed to provide smart segmentation of mostly "
"frontal faces. The mask model has been specifically trained to recognize "
"some facial obstructions (hands and eyeglasses). Profile faces may result in "
"sub-par performance.\n"
"L|unet-dfl: Mask designed to provide smart segmentation of mostly frontal "
"faces. The mask model has been trained by community members and will need "
"testing for further description. Profile faces may result in sub-par "
"performance.\n"
"L|predicted: If the 'Learn Mask' option was enabled during training, this "
"will use the mask that was created by the trained model."
msgstr ""

#: lib/cli/args.py:762
msgid ""
"R|The plugin to use to output the converted images. The writers are "
"configurable in '/config/convert.ini' or 'Settings > Configure Convert "
"Plugins:'\n"
"L|ffmpeg: [video] Writes out the convert straight to video. When the input "
"is a series of images then the '-ref' (--reference-video) parameter must be "
"set.\n"
"L|gif: [animated image] Create an animated gif.\n"
"L|opencv: [images] The fastest image writer, but less options and formats "
"than other plugins.\n"
"L|pillow: [images] Slower than opencv, but has more options and supports "
"more formats."
msgstr ""

#: lib/cli/args.py:781 lib/cli/args.py:788 lib/cli/args.py:882
msgid "Frame Processing"
msgstr ""

#: lib/cli/args.py:782
#, python-format
msgid ""
"Scale the final output frames by this amount. 100%% will output the frames "
"at source dimensions. 50%% at half size 200%% at double size"
msgstr ""

#: lib/cli/args.py:789
msgid ""
"Frame ranges to apply transfer to e.g. For frames 10 to 50 and 90 to 100 use "
"--frame-ranges 10-50 90-100. Frames falling outside of the selected range "
"will be discarded unless '-k' (--keep-unchanged) is selected. NB: If you are "
"converting from images, then the filenames must end with the frame-number!"
msgstr ""

#: lib/cli/args.py:799
msgid ""
"If you have not cleansed your alignments file, then you can filter out faces "
"by defining a folder here that contains the faces extracted from your input "
"files/video. If this folder is defined, then only faces that exist within "
"your alignments file and also exist within the specified folder will be "
"converted. Leaving this blank will convert all faces that exist within the "
"alignments file."
msgstr ""

#: lib/cli/args.py:813
msgid ""
"Optionally filter out people who you do not wish to process by passing in an "
"image of that person. Should be a front portrait with a single person in the "
"image. Multiple images can be added space separated. NB: Using face filter "
"will significantly decrease extraction speed and its accuracy cannot be "
"guaranteed."
msgstr ""

#: lib/cli/args.py:826
msgid ""
"Optionally select people you wish to process by passing in an image of that "
"person. Should be a front portrait with a single person in the image. "
"Multiple images can be added space separated. NB: Using face filter will "
"significantly decrease extraction speed and its accuracy cannot be "
"guaranteed."
msgstr ""

#: lib/cli/args.py:840
msgid ""
"For use with the optional nfilter/filter files. Threshold for positive face "
"recognition. Lower values are stricter. NB: Using face filter will "
"significantly decrease extraction speed and its accuracy cannot be "
"guaranteed."
msgstr ""

#: lib/cli/args.py:853
msgid ""
"The maximum number of parallel processes for performing conversion. "
"Converting images is system RAM heavy so it is possible to run out of memory "
"if you have a lot of processes and not enough RAM to accommodate them all. "
"Setting this to 0 will use the maximum available. No matter what you set "
"this to, it will never attempt to use more processes than are available on "
"your system. If singleprocess is enabled this setting will be ignored."
msgstr ""

#: lib/cli/args.py:864
msgid ""
"[LEGACY] This only needs to be selected if a legacy model is being loaded or "
"if there are multiple models in the model folder"
msgstr ""

#: lib/cli/args.py:872
msgid ""
"Enable On-The-Fly Conversion. NOT recommended. You should generate a clean "
"alignments file for your destination video. However, if you wish you can "
"generate the alignments on-the-fly by enabling this option. This will use an "
"inferior extraction pipeline and will lead to substandard results. If an "
"alignments file is found, this option will be ignored."
msgstr ""

#: lib/cli/args.py:883
msgid ""
"When used with --frame-ranges outputs the unchanged frames that are not "
"processed instead of discarding them."
msgstr ""

#: lib/cli/args.py:891
msgid "Swap the model. Instead converting from of A -> B, converts B -> A"
msgstr ""

#: lib/cli/args.py:897
msgid "Disable multiprocessing. Slower but less resource intensive."
msgstr ""

#: lib/cli/args.py:913
msgid ""
"Train a model on extracted original (A) and swap (B) faces.\n"
"Training models can take a long time. Anything from 24hrs to over a week\n"
"Model plugins can be configured in the 'Settings' Menu"
msgstr ""

#: lib/cli/args.py:932 lib/cli/args.py:941
msgid "faces"
msgstr ""

#: lib/cli/args.py:933
msgid ""
"Input directory. A directory containing training images for face A. This is "
"the original face, i.e. the face that you want to remove and replace with "
"face B."
msgstr ""

#: lib/cli/args.py:942
msgid ""
"Input directory. A directory containing training images for face B. This is "
"the swap face, i.e. the face that you want to place onto the head of person "
"A."
msgstr ""

#: lib/cli/args.py:950 lib/cli/args.py:962 lib/cli/args.py:978
#: lib/cli/args.py:1003 lib/cli/args.py:1013
msgid "model"
msgstr ""

#: lib/cli/args.py:951
msgid ""
"Model directory. This is where the training data will be stored. You should "
"always specify a new folder for new models. If starting a new model, select "
"either an empty folder, or a folder which does not exist (which will be "
"created). If continuing to train an existing model, specify the location of "
"the existing model."
msgstr ""

#: lib/cli/args.py:963
msgid ""
"R|Load the weights from a pre-existing model into a newly created model. For "
"most models this will load weights from the Encoder of the given model into "
"the encoder of the newly created model. Some plugins may have specific "
"configuration options allowing you to load weights from other layers. "
"Weights will only be loaded when creating a new model. This option will be "
"ignored if you are resuming an existing model. Generally you will also want "
"to 'freeze-weights' whilst the rest of your model catches up with your "
"Encoder.\n"
"NB: Weights can only be loaded from models of the same plugin as you intend "
"to train."
msgstr ""

#: lib/cli/args.py:979
msgid ""
"R|Select which trainer to use. Trainers can be configured from the Settings "
"menu or the config folder.\n"
"L|original: The original model created by /u/deepfakes.\n"
"L|dfaker: 64px in/128px out model from dfaker. Enable 'warp-to-landmarks' "
"for full dfaker method.\n"
"L|dfl-h128: 128px in/out model from deepfacelab\n"
"L|dfl-sae: Adaptable model from deepfacelab\n"
"L|dlight: A lightweight, high resolution DFaker variant.\n"
"L|iae: A model that uses intermediate layers to try to get better details\n"
"L|lightweight: A lightweight model for low-end cards. Don't expect great "
"results. Can train as low as 1.6GB with batch size 8.\n"
"L|realface: A high detail, dual density model based on DFaker, with "
"customizable in/out resolution. The autoencoders are unbalanced so B>A swaps "
"won't work so well. By andenixa et al. Very configurable.\n"
"L|unbalanced: 128px in/out model from andenixa. The autoencoders are "
"unbalanced so B>A swaps won't work so well. Very configurable.\n"
"L|villain: 128px in/out model from villainguy. Very resource hungry (You "
"will require a GPU with a fair amount of VRAM). Good for details, but more "
"susceptible to color differences."
msgstr ""

#: lib/cli/args.py:1004
msgid ""
"Output a summary of the model and exit. If a model folder is provided then a "
"summary of the saved model is displayed. Otherwise a summary of the model "
"that would be created by the chosen plugin and configuration settings is "
"displayed."
msgstr ""

#: lib/cli/args.py:1014
msgid ""
"Freeze the weights of the model. Freezing weights means that some of the "
"parameters in the model will no longer continue to learn, but those that are "
"not frozen will continue to learn. For most models, this will freeze the "
"encoder, but some models may have configuration options for freezing other "
"layers."
msgstr ""

#: lib/cli/args.py:1027 lib/cli/args.py:1039 lib/cli/args.py:1050
#: lib/cli/args.py:1061 lib/cli/args.py:1144
msgid "training"
msgstr ""

#: lib/cli/args.py:1028
msgid ""
"Batch size. This is the number of images processed through the model for "
"each side per iteration. NB: As the model is fed 2 sides at a time, the "
"actual number of images within the model at any one time is double the "
"number that you set here. Larger batches require more GPU RAM."
msgstr ""

#: lib/cli/args.py:1040
msgid ""
"Length of training in iterations. This is only really used for automation. "
"There is no 'correct' number of iterations a model should be trained for. "
"You should stop training when you are happy with the previews. However, if "
"you want the model to stop automatically at a set number of iterations, you "
"can set that value here."
msgstr ""

#: lib/cli/args.py:1051
msgid ""
"[Deprecated - Use '-D, --distribution-strategy' instead] Use the Tensorflow "
"Mirrored Distrubution Strategy to train on multiple GPUs."
msgstr ""

#: lib/cli/args.py:1062
msgid ""
"R|Select the distribution stategy to use.\n"
"L|default: Use Tensorflow's default distribution strategy.\n"
"L|central-storage: Centralizes variables on the CPU whilst operations are "
"performed on 1 or more local GPUs. This can help save some VRAM at the cost "
"of some speed by not storing variables on the GPU. Note: Mixed-Precision is "
"not supported on multi-GPU setups.\n"
"L|mirrored: Supports synchronous distributed training across multiple local "
"GPUs. A copy of the model and all variables are loaded onto each GPU with "
"batches distributed to each GPU at each iteration."
msgstr ""

#: lib/cli/args.py:1079 lib/cli/args.py:1089
msgid "Saving"
msgstr ""

#: lib/cli/args.py:1080
msgid "Sets the number of iterations between each model save."
msgstr ""

#: lib/cli/args.py:1090
msgid ""
"Sets the number of iterations before saving a backup snapshot of the model "
"in it's current state. Set to 0 for off."
msgstr ""

#: lib/cli/args.py:1097 lib/cli/args.py:1108 lib/cli/args.py:1119
msgid "timelapse"
msgstr ""

#: lib/cli/args.py:1098
msgid ""
"Optional for creating a timelapse. Timelapse will save an image of your "
"selected faces into the timelapse-output folder at every save iteration. "
"This should be the input folder of 'A' faces that you would like to use for "
"creating the timelapse. You must also supply a --timelapse-output and a --"
"timelapse-input-B parameter."
msgstr ""

#: lib/cli/args.py:1109
msgid ""
"Optional for creating a timelapse. Timelapse will save an image of your "
"selected faces into the timelapse-output folder at every save iteration. "
"This should be the input folder of 'B' faces that you would like to use for "
"creating the timelapse. You must also supply a --timelapse-output and a --"
"timelapse-input-A parameter."
msgstr ""

#: lib/cli/args.py:1120
msgid ""
"Optional for creating a timelapse. Timelapse will save an image of your "
"selected faces into the timelapse-output folder at every save iteration. If "
"the input folders are supplied but no output folder, it will default to your "
"model folder /timelapse/"
msgstr ""

#: lib/cli/args.py:1129 lib/cli/args.py:1136
msgid "preview"
msgstr ""

#: lib/cli/args.py:1130
msgid "Show training preview output. in a separate window."
msgstr ""

#: lib/cli/args.py:1137
msgid ""
"Writes the training result to a file. The image will be stored in the root "
"of your FaceSwap folder."
msgstr ""

#: lib/cli/args.py:1145
msgid ""
"Disables TensorBoard logging. NB: Disabling logs means that you will not be "
"able to use the graph or analysis for this session in the GUI."
msgstr ""

#: lib/cli/args.py:1152 lib/cli/args.py:1161 lib/cli/args.py:1170
#: lib/cli/args.py:1179
msgid "augmentation"
msgstr ""

#: lib/cli/args.py:1153
msgid ""
"Warps training faces to closely matched Landmarks from the opposite face-set "
"rather than randomly warping the face. This is the 'dfaker' way of doing "
"warping."
msgstr ""

#: lib/cli/args.py:1162
msgid ""
"To effectively learn, a random set of images are flipped horizontally. "
"Sometimes it is desirable for this not to occur. Generally this should be "
"left off except for during 'fit training'."
msgstr ""

#: lib/cli/args.py:1171
msgid ""
"Color augmentation helps make the model less susceptible to color "
"differences between the A and B sets, at an increased training time cost. "
"Enable this option to disable color augmentation."
msgstr ""

#: lib/cli/args.py:1180
msgid ""
"Warping is integral to training the Neural Network. This option should only "
"be enabled towards the very end of training to try to bring out more detail. "
"Think of it as 'fine-tuning'. Enabling this option from the beginning is "
"likely to kill a model and lead to terrible results."
msgstr ""

#: lib/cli/args.py:1205
msgid "Output to Shell console instead of GUI console"
msgstr ""
