#!/usr/bin python3 """ Command Line Arguments """ import argparse import os import sys from plugins.PluginLoader import PluginLoader class ScriptExecutor(object): """ Loads the relevant script modules and executes the script. This class is initialised in each of the argparsers for the relevant command, then execute script is called within their set_default function. """ def __init__(self, command, subparsers=None): self.command = command.lower() self.subparsers = subparsers def import_script(self): """ Only import a script's modules when running that script.""" if self.command == 'extract': from scripts.extract import Extract as script elif self.command == 'train': from scripts.train import Train as script elif self.command == 'convert': from scripts.convert import Convert as script elif self.command == 'gui': from scripts.gui import Gui as script else: script = None return script def execute_script(self, arguments): """ Run the script for called command """ script = self.import_script() args = (arguments, ) if self.command != 'gui' else (arguments, self.subparsers) process = script(*args) process.process() class FullPaths(argparse.Action): """ Expand user- and relative-paths """ def __call__(self, parser, namespace, values, option_string=None): setattr(namespace, self.dest, os.path.abspath( os.path.expanduser(values))) class DirFullPaths(FullPaths): """ Class that gui uses to determine if you need to open a directory """ pass class FileFullPaths(FullPaths): """ Class that gui uses to determine if you need to open a file. Filetypes added as an argparse argument must be an iterable, i.e. a list of lists, tuple of tuples, list of tuples etc... formatted like so: [("File Type", ["*.ext", "*.extension"])] A more realistic example: [("Video File", ["*.mkv", "mp4", "webm"])] If the file extensions are not prepended with '*.', use the prep_filetypes() method to format them in the arguments_list. """ def __init__(self, option_strings, dest, nargs=None, filetypes=None, **kwargs): super(FileFullPaths, self).__init__(option_strings, dest, **kwargs) if nargs is not None: raise ValueError("nargs not allowed") self.filetypes = filetypes @staticmethod def prep_filetypes(filetypes): all_files = ("All Files", "*.*") filetypes_l = list() for i in range(len(filetypes)): filetypes_l.append(FileFullPaths._process_filetypes(filetypes[i])) filetypes_l.append(all_files) return tuple(filetypes_l) @staticmethod def _process_filetypes(filetypes): """ """ if filetypes is None: return None filetypes_name = filetypes[0] filetypes_l = filetypes[1] if (type(filetypes_l) == list or type(filetypes_l) == tuple) \ and all("*." in i for i in filetypes_l): return filetypes # assume filetypes properly formatted if type(filetypes_l) != list and type(filetypes_l) != tuple: raise ValueError("The filetypes extensions list was " "neither a list nor a tuple: " "{}".format(filetypes_l)) filetypes_list = list() for i in range(len(filetypes_l)): filetype = filetypes_l[i].strip("*.") filetype = filetype.strip(';') filetypes_list.append("*." + filetype) return filetypes_name, filetypes_list def _get_kwargs(self): names = [ 'option_strings', 'dest', 'nargs', 'const', 'default', 'type', 'choices', 'help', 'metavar', 'filetypes' ] return [(name, getattr(self, name)) for name in names] class ComboFullPaths(FileFullPaths): """ Class that gui uses to determine if you need to open a file or a directory based on which action you are choosing """ def __init__(self, option_strings, dest, nargs=None, filetypes=None, actions_open_type=None, **kwargs): if nargs is not None: raise ValueError("nargs not allowed") super(ComboFullPaths, self).__init__(option_strings, dest, filetypes=None, **kwargs) self.actions_open_type = actions_open_type self.filetypes = filetypes @staticmethod def prep_filetypes(filetypes): all_files = ("All Files", "*.*") filetypes_d = dict() for k, v in filetypes.items(): filetypes_d[k] = () if v is None: filetypes_d[k] = None continue filetypes_l = list() for i in range(len(v)): filetypes_l.append(ComboFullPaths._process_filetypes(v[i])) filetypes_d[k] = (tuple(filetypes_l), all_files) return filetypes_d def _get_kwargs(self): names = [ 'option_strings', 'dest', 'nargs', 'const', 'default', 'type', 'choices', 'help', 'metavar', 'filetypes', 'actions_open_type' ] return [(name, getattr(self, name)) for name in names] class FullHelpArgumentParser(argparse.ArgumentParser): """ Identical to the built-in argument parser, but on error it prints full help message instead of just usage information """ def error(self, message): self.print_help(sys.stderr) args = {"prog": self.prog, "message": message} self.exit(2, "%(prog)s: error: %(message)s\n" % args) class FaceSwapArgs(object): """ Faceswap argument parser functions that are universal to all commands. Should be the parent function of all subsequent argparsers """ def __init__(self, subparser, command, description="default", subparsers=None): self.argument_list = self.get_argument_list() self.optional_arguments = self.get_optional_arguments() self.parser = self.create_parser(subparser, command, description) self.add_arguments() script = ScriptExecutor(command, subparsers) self.parser.set_defaults(func=script.execute_script) @staticmethod def get_argument_list(): """ Put the arguments in a list so that they are accessible from both argparse and gui override for command specific arguments """ argument_list = [] return argument_list @staticmethod def get_optional_arguments(): """ Put the arguments in a list so that they are accessible from both argparse and gui. This is used for when there are sub-children (e.g. convert and extract) Override this for custom arguments """ argument_list = [] return argument_list @staticmethod def create_parser(subparser, command, description): """ Create the parser for the selected command """ parser = subparser.add_parser( command, help=description, description=description, epilog="Questions and feedback: \ https://github.com/deepfakes/faceswap-playground") return parser def add_arguments(self): """ Parse the arguments passed in from argparse """ for option in self.argument_list + self.optional_arguments: args = option["opts"] kwargs = {key: option[key] for key in option.keys() if key != "opts"} self.parser.add_argument(*args, **kwargs) class ExtractConvertArgs(FaceSwapArgs): """ This class is used as a parent class to capture arguments that will be used in both the extract and convert process. Arguments that can be used in both of these processes should be placed here, but no further processing should be done. This class just captures arguments """ @staticmethod def get_argument_list(): """ Put the arguments in a list so that they are accessible from both argparse and gui """ alignments_filetypes = [["Serializers", ['json', 'yaml', 'p']], ["JSON", ["json"]], ["Pickle", ["p"]], ["YAML", ["yaml"]]] alignments_filetypes = FileFullPaths.prep_filetypes(alignments_filetypes) argument_list = list() argument_list.append({"opts": ("-i", "--input-dir"), "action": DirFullPaths, "dest": "input_dir", "default": "input", "help": "Input directory. A directory " "containing the files you wish to " "process. Defaults to 'input'"}) argument_list.append({"opts": ("-o", "--output-dir"), "action": DirFullPaths, "dest": "output_dir", "default": "output", "help": "Output directory. This is where the " "converted files will be stored. " "Defaults to 'output'"}) argument_list.append({"opts": ("--alignments", ), "action": FileFullPaths, "filetypes": alignments_filetypes, "type": str, "dest": "alignments_path", "help": "optional path to alignments file"}) argument_list.append({"opts": ("--serializer", ), "type": str.lower, "dest": "serializer", "choices": ("json", "pickle", "yaml"), "help": "serializer for alignments file"}) argument_list.append({"opts": ("-D", "--detector"), "type": str, # case sensitive because this is used to load a plugin. "choices": ("hog", "cnn", "all"), "default": "hog", "help": "Detector to use. 'cnn' detects many " "more angles but will be much more " "resource intensive and may fail on " "large files"}) argument_list.append({"opts": ("-l", "--ref_threshold"), "type": float, "dest": "ref_threshold", "default": 0.6, "help": "Threshold for positive face recognition"}) argument_list.append({"opts": ("-n", "--nfilter"), "type": str, "dest": "nfilter", "nargs": "+", "default": None, "help": "Reference image for the persons you do " "not want to process. Should be a front " "portrait. Multiple images can be added " "space separated"}) argument_list.append({"opts": ("-f", "--filter"), "type": str, "dest": "filter", "nargs": "+", "default": None, "help": "Reference images for the person you " "want to process. Should be a front " "portrait. Multiple images can be added " "space separated"}) argument_list.append({"opts": ("-v", "--verbose"), "action": "store_true", "dest": "verbose", "default": False, "help": "Show verbose output"}) return argument_list class ExtractArgs(ExtractConvertArgs): """ Class to parse the command line arguments for extraction. Inherits base options from ExtractConvertArgs where arguments that are used for both extract and convert should be placed """ @staticmethod def get_optional_arguments(): """ Put the arguments in a list so that they are accessible from both argparse and gui """ argument_list = [] argument_list.append({"opts": ("-r", "--rotate-images"), "type": str, "dest": "rotate_images", "default": None, "help": "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"}) argument_list.append({"opts": ("-bt", "--blur-threshold"), "type": int, "dest": "blur_thresh", "default": None, "help": "Automatically discard images blurrier " "than the specified threshold. " "Discarded images are moved into a " "\"blurry\" sub-folder. Lower values " "allow more blur"}) argument_list.append({"opts": ("-j", "--processes"), "type": int, "default": 1, "help": "Number of CPU processes to use. " "WARNING: ONLY USE THIS IF YOU ARE NOT " "EXTRACTING ON A GPU. Anything above 1 " "process on a GPU will run out of " "memory and will crash"}) argument_list.append({"opts": ("-s", "--skip-existing"), "action": "store_true", "dest": "skip_existing", "default": False, "help": "Skips frames that have already been extracted"}) argument_list.append({"opts": ("-dl", "--debug-landmarks"), "action": "store_true", "dest": "debug_landmarks", "default": False, "help": "Draw landmarks on the ouput faces for debug"}) argument_list.append({"opts": ("-ae", "--align-eyes"), "action": "store_true", "dest": "align_eyes", "default": False, "help": "Perform extra alignment to ensure " "left/right eyes are at the same " "height"}) return argument_list class ConvertArgs(ExtractConvertArgs): """ Class to parse the command line arguments for conversion. Inherits base options from ExtractConvertArgs where arguments that are used for both extract and convert should be placed """ @staticmethod def get_optional_arguments(): """ Put the arguments in a list so that they are accessible from both argparse and gui """ argument_list = [] argument_list.append({"opts": ("-m", "--model-dir"), "action": DirFullPaths, "dest": "model_dir", "default": "models", "help": "Model directory. A directory " "containing the trained model you wish " "to process. Defaults to 'models'"}) argument_list.append({"opts": ("-a", "--input-aligned-dir"), "action": DirFullPaths, "dest": "input_aligned_dir", "default": None, "help": "Input \"aligned directory\". A " "directory that should contain the " "aligned faces extracted from the input " "files. If you delete faces from this " "folder, they'll be skipped during " "conversion. If no aligned dir is " "specified, all faces will be converted"}) argument_list.append({"opts": ("-t", "--trainer"), "type": str, # case sensitive because this is used to load a plug-in. "choices": PluginLoader.get_available_models(), "default": PluginLoader.get_default_model(), "help": "Select the trainer that was used to create the model"}) argument_list.append({"opts": ("-c", "--converter"), "type": str, # case sensitive because this is used to load a plugin. "choices": ("Masked", "Adjust"), "default": "Masked", "help": "Converter to use"}) argument_list.append({"opts": ("-b", "--blur-size"), "type": int, "default": 2, "help": "Blur size. (Masked converter only)"}) argument_list.append({"opts": ("-e", "--erosion-kernel-size"), "dest": "erosion_kernel_size", "type": int, "default": None, "help": "Erosion kernel size. Positive values " "apply erosion which reduces the edge " "of the swapped face. Negative values " "apply dilation which allows the " "swapped face to cover more space. " "(Masked converter only)"}) argument_list.append({"opts": ("-M", "--mask-type"), # lowercase this, because it's just a string later on. "type": str.lower, "dest": "mask_type", "choices": ["rect", "facehull", "facehullandrect"], "default": "facehullandrect", "help": "Mask to use to replace faces. (Masked converter only)"}) argument_list.append({"opts": ("-sh", "--sharpen"), "type": str.lower, "dest": "sharpen_image", "choices": ["bsharpen", "gsharpen"], "default": None, "help": "Use Sharpen Image. bsharpen for Box " "Blur, gsharpen for Gaussian Blur " "(Masked converter only)"}) argument_list.append({"opts": ("-g", "--gpus"), "type": int, "default": 1, "help": "Number of GPUs to use for conversion"}) argument_list.append({"opts": ("-fr", "--frame-ranges"), "nargs": "+", "type": str, "help": "frame ranges to apply transfer to e.g. " "For frames 10 to 50 and 90 to 100 use " "--frame-ranges 10-50 90-100. Files " "must have the frame-number as the last " "number in the name!"}) argument_list.append({"opts": ("-d", "--discard-frames"), "action": "store_true", "dest": "discard_frames", "default": False, "help": "When used with --frame-ranges discards " "frames that are not processed instead " "of writing them out unchanged"}) argument_list.append({"opts": ("-s", "--swap-model"), "action": "store_true", "dest": "swap_model", "default": False, "help": "Swap the model. Instead of A -> B, swap B -> A"}) argument_list.append({"opts": ("-S", "--seamless"), "action": "store_true", "dest": "seamless_clone", "default": False, "help": "Use cv2's seamless clone. (Masked converter only)"}) argument_list.append({"opts": ("-mh", "--match-histogram"), "action": "store_true", "dest": "match_histogram", "default": False, "help": "Use histogram matching. (Masked converter only)"}) argument_list.append({"opts": ("-sm", "--smooth-mask"), "action": "store_true", "dest": "smooth_mask", "default": True, "help": "Smooth mask (Adjust converter only)"}) argument_list.append({"opts": ("-aca", "--avg-color-adjust"), "action": "store_true", "dest": "avg_color_adjust", "default": True, "help": "Average color adjust. (Adjust converter only)"}) return argument_list class TrainArgs(FaceSwapArgs): """ Class to parse the command line arguments for training """ @staticmethod def get_argument_list(): """ Put the arguments in a list so that they are accessible from both argparse and gui """ argument_list = list() argument_list.append({"opts": ("-A", "--input-A"), "action": DirFullPaths, "dest": "input_A", "default": "input_A", "help": "Input directory. A directory " "containing training images for face A. " "Defaults to 'input'"}) argument_list.append({"opts": ("-B", "--input-B"), "action": DirFullPaths, "dest": "input_B", "default": "input_B", "help": "Input directory. A directory " "containing training images for face B. " "Defaults to 'input'"}) argument_list.append({"opts": ("-m", "--model-dir"), "action": DirFullPaths, "dest": "model_dir", "default": "models", "help": "Model directory. This is where the " "training data will be stored. " "Defaults to 'model'"}) argument_list.append({"opts": ("-s", "--save-interval"), "type": int, "dest": "save_interval", "default": 100, "help": "Sets the number of iterations before " "saving the model"}) argument_list.append({"opts": ("-t", "--trainer"), "type": str, "choices": PluginLoader.get_available_models(), "default": PluginLoader.get_default_model(), "help": "Select which trainer to use, Use " "LowMem for cards with less than 2GB of " "VRAM"}) argument_list.append({"opts": ("-bs", "--batch-size"), "type": int, "default": 64, "help": "Batch size, as a power of 2 (64, 128, 256, etc)"}) argument_list.append({"opts": ("-ep", "--epochs"), "type": int, "default": 1000000, "help": "Length of training in epochs"}) argument_list.append({"opts": ("-g", "--gpus"), "type": int, "default": 1, "help": "Number of GPUs to use for training"}) argument_list.append({"opts": ("-p", "--preview"), "action": "store_true", "dest": "preview", "default": False, "help": "Show preview output. If not specified, " "write progress to file"}) argument_list.append({"opts": ("-w", "--write-image"), "action": "store_true", "dest": "write_image", "default": False, "help": "Writes the training result to a file " "even on preview mode"}) argument_list.append({"opts": ("-pl", "--use-perceptual-loss"), "action": "store_true", "dest": "perceptual_loss", "default": False, "help": "Use perceptual loss while training"}) argument_list.append({"opts": ("-ag", "--allow-growth"), "action": "store_true", "dest": "allow_growth", "default": False, "help": "Sets allow_growth option of Tensorflow " "to spare memory on some configs"}) argument_list.append({"opts": ("-v", "--verbose"), "action": "store_true", "dest": "verbose", "default": False, "help": "Show verbose output"}) # This is a hidden argument to indicate that the GUI is being used, # so the preview window should be redirected Accordingly argument_list.append({"opts": ("-gui", "--gui"), "action": "store_true", "dest": "redirect_gui", "default": False, "help": argparse.SUPPRESS}) return argument_list class GuiArgs(FaceSwapArgs): """ Class to parse the command line arguments for training """ @staticmethod def get_argument_list(): """ Put the arguments in a list so that they are accessible from both argparse and gui """ argument_list = [] argument_list.append({"opts": ("-d", "--debug"), "action": "store_true", "dest": "debug", "default": False, "help": "Output to Shell console instead of GUI console"}) return argument_list