if __name__ == "__main__":
    # Fix for linux
    import multiprocessing
    multiprocessing.set_start_method("spawn")

    import sys
    if sys.platform != 'win32':
        import warnings
        warnings.simplefilter(action='ignore', category=UserWarning)

    from core.leras import nn
    nn.initialize_main_env()

    import os
    import sys
    import time
    import argparse

    from core import pathex
    from core import osex
    from pathlib import Path
    from core.interact import interact as io

    if sys.version_info[0] < 3 or (sys.version_info[0] == 3 and sys.version_info[1] < 6):
        raise Exception("This program requires at least Python 3.6")

    class fixPathAction(argparse.Action):
        def __call__(self, parser, namespace, values, option_string=None):
            setattr(namespace, self.dest, os.path.abspath(os.path.expanduser(values)))

    parser = argparse.ArgumentParser()
    subparsers = parser.add_subparsers()

    def process_extract(arguments):
        osex.set_process_lowest_prio()
        from mainscripts import Extractor
        Extractor.main( detector                = arguments.detector,
                        input_path              = Path(arguments.input_dir),
                        output_path             = Path(arguments.output_dir),
                        output_debug            = arguments.output_debug,
                        manual_fix              = arguments.manual_fix,
                        manual_output_debug_fix = arguments.manual_output_debug_fix,
                        manual_window_size      = arguments.manual_window_size,
                        face_type               = arguments.face_type,
                        cpu_only                = arguments.cpu_only,
                        force_gpu_idxs          = [ int(x) for x in arguments.force_gpu_idxs.split(',') ] if arguments.force_gpu_idxs is not None else None,
                      )

    p = subparsers.add_parser( "extract", help="Extract the faces from a pictures.")
    p.add_argument('--detector', dest="detector", choices=['s3fd','manual'], default=None, help="Type of detector.")
    p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input directory. A directory containing the files you wish to process.")
    p.add_argument('--output-dir', required=True, action=fixPathAction, dest="output_dir", help="Output directory. This is where the extracted files will be stored.")
    p.add_argument('--output-debug', action="store_true", dest="output_debug", default=None, help="Writes debug images to <output-dir>_debug\ directory.")
    p.add_argument('--no-output-debug', action="store_false", dest="output_debug", default=None, help="Don't writes debug images to <output-dir>_debug\ directory.")
    p.add_argument('--face-type', dest="face_type", choices=['half_face', 'full_face', 'whole_face', 'head', 'full_face_no_align', 'mark_only'], default='full_face', help="Default 'full_face'. Don't change this option, currently all models uses 'full_face'")
    p.add_argument('--manual-fix', action="store_true", dest="manual_fix", default=False, help="Enables manual extract only frames where faces were not recognized.")
    p.add_argument('--manual-output-debug-fix', action="store_true", dest="manual_output_debug_fix", default=False, help="Performs manual reextract input-dir frames which were deleted from [output_dir]_debug\ dir.")
    p.add_argument('--manual-window-size', type=int, dest="manual_window_size", default=1368, help="Manual fix window size. Default: 1368.")
    p.add_argument('--cpu-only', action="store_true", dest="cpu_only", default=False, help="Extract on CPU..")
    p.add_argument('--force-gpu-idxs', dest="force_gpu_idxs", default=None, help="Force to choose GPU indexes separated by comma.")

    p.set_defaults (func=process_extract)

    def process_dev_extract_vggface2_dataset(arguments):
        osex.set_process_lowest_prio()
        from mainscripts import dev_misc
        dev_misc.extract_vggface2_dataset( arguments.input_dir,
                                            device_args={'cpu_only'  : arguments.cpu_only,
                                                        'multi_gpu' : arguments.multi_gpu,
                                                        }
                                            )

    p = subparsers.add_parser( "dev_extract_vggface2_dataset", help="")
    p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input directory. A directory containing the files you wish to process.")
    p.add_argument('--multi-gpu', action="store_true", dest="multi_gpu", default=False, help="Enables multi GPU.")
    p.add_argument('--cpu-only', action="store_true", dest="cpu_only", default=False, help="Extract on CPU.")
    p.set_defaults (func=process_dev_extract_vggface2_dataset)

    def process_dev_extract_umd_csv(arguments):
        osex.set_process_lowest_prio()
        from mainscripts import dev_misc
        dev_misc.extract_umd_csv( arguments.input_csv_file,
                                  device_args={'cpu_only'  : arguments.cpu_only,
                                               'multi_gpu' : arguments.multi_gpu,
                                              }
                                )

    p = subparsers.add_parser( "dev_extract_umd_csv", help="")
    p.add_argument('--input-csv-file', required=True, action=fixPathAction, dest="input_csv_file", help="input_csv_file")
    p.add_argument('--multi-gpu', action="store_true", dest="multi_gpu", default=False, help="Enables multi GPU.")
    p.add_argument('--cpu-only', action="store_true", dest="cpu_only", default=False, help="Extract on CPU.")
    p.set_defaults (func=process_dev_extract_umd_csv)


    def process_dev_apply_celebamaskhq(arguments):
        osex.set_process_lowest_prio()
        from mainscripts import dev_misc
        dev_misc.apply_celebamaskhq( arguments.input_dir )

    p = subparsers.add_parser( "dev_apply_celebamaskhq", help="")
    p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir")
    p.set_defaults (func=process_dev_apply_celebamaskhq)

    def process_dev_test(arguments):
        osex.set_process_lowest_prio()
        from mainscripts import dev_misc
        dev_misc.dev_test( arguments.input_dir )

    p = subparsers.add_parser( "dev_test", help="")
    p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir")
    p.set_defaults (func=process_dev_test)

    def process_sort(arguments):
        osex.set_process_lowest_prio()
        from mainscripts import Sorter
        Sorter.main (input_path=Path(arguments.input_dir), sort_by_method=arguments.sort_by_method)

    p = subparsers.add_parser( "sort", help="Sort faces in a directory.")
    p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input directory. A directory containing the files you wish to process.")
    p.add_argument('--by', dest="sort_by_method", default=None, choices=("blur", "face-yaw", "face-pitch", "hist", "hist-dissim", "brightness", "hue", "black", "origname", "oneface", "final", "absdiff"), help="Method of sorting. 'origname' sort by original filename to recover original sequence." )
    p.set_defaults (func=process_sort)

    def process_util(arguments):
        osex.set_process_lowest_prio()
        from mainscripts import Util

        if arguments.convert_png_to_jpg:
            Util.convert_png_to_jpg_folder (input_path=arguments.input_dir)

        if arguments.add_landmarks_debug_images:
            Util.add_landmarks_debug_images (input_path=arguments.input_dir)

        if arguments.recover_original_aligned_filename:
            Util.recover_original_aligned_filename (input_path=arguments.input_dir)

        #if arguments.remove_fanseg:
        #    Util.remove_fanseg_folder (input_path=arguments.input_dir)

        if arguments.remove_ie_polys:
            Util.remove_ie_polys_folder (input_path=arguments.input_dir)

        if arguments.save_faceset_metadata:
            Util.save_faceset_metadata_folder (input_path=arguments.input_dir)

        if arguments.restore_faceset_metadata:
            Util.restore_faceset_metadata_folder (input_path=arguments.input_dir)

        if arguments.pack_faceset:
            io.log_info ("Performing faceset packing...\r\n")
            from samplelib import PackedFaceset
            PackedFaceset.pack( Path(arguments.input_dir) )

        if arguments.unpack_faceset:
            io.log_info ("Performing faceset unpacking...\r\n")
            from samplelib import PackedFaceset
            PackedFaceset.unpack( Path(arguments.input_dir) )

    p = subparsers.add_parser( "util", help="Utilities.")
    p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input directory. A directory containing the files you wish to process.")
    p.add_argument('--convert-png-to-jpg', action="store_true", dest="convert_png_to_jpg", default=False, help="Convert DeepFaceLAB PNG files to JPEG.")
    p.add_argument('--add-landmarks-debug-images', action="store_true", dest="add_landmarks_debug_images", default=False, help="Add landmarks debug image for aligned faces.")
    p.add_argument('--recover-original-aligned-filename', action="store_true", dest="recover_original_aligned_filename", default=False, help="Recover original aligned filename.")
    #p.add_argument('--remove-fanseg', action="store_true", dest="remove_fanseg", default=False, help="Remove fanseg mask from aligned faces.")
    p.add_argument('--remove-ie-polys', action="store_true", dest="remove_ie_polys", default=False, help="Remove ie_polys from aligned faces.")
    p.add_argument('--save-faceset-metadata', action="store_true", dest="save_faceset_metadata", default=False, help="Save faceset metadata to file.")
    p.add_argument('--restore-faceset-metadata', action="store_true", dest="restore_faceset_metadata", default=False, help="Restore faceset metadata to file. Image filenames must be the same as used with save.")
    p.add_argument('--pack-faceset', action="store_true", dest="pack_faceset", default=False, help="")
    p.add_argument('--unpack-faceset', action="store_true", dest="unpack_faceset", default=False, help="")

    p.set_defaults (func=process_util)

    def process_train(arguments):
        osex.set_process_lowest_prio()


        kwargs = {'model_class_name'         : arguments.model_name,
                  'saved_models_path'        : Path(arguments.model_dir),
                  'training_data_src_path'   : Path(arguments.training_data_src_dir),
                  'training_data_dst_path'   : Path(arguments.training_data_dst_dir),
                  'pretraining_data_path'    : Path(arguments.pretraining_data_dir) if arguments.pretraining_data_dir is not None else None,
                  'pretrained_model_path'    : Path(arguments.pretrained_model_dir) if arguments.pretrained_model_dir is not None else None,
                  'no_preview'               : arguments.no_preview,
                  'force_model_name'         : arguments.force_model_name,
                  'force_gpu_idxs'           : arguments.force_gpu_idxs,
                  'cpu_only'                 : arguments.cpu_only,
                  'execute_programs'         : [ [int(x[0]), x[1] ] for x in arguments.execute_program ],
                  'debug'                    : arguments.debug,
                  }
        from mainscripts import Trainer
        Trainer.main(**kwargs)

    p = subparsers.add_parser( "train", help="Trainer")
    p.add_argument('--training-data-src-dir', required=True, action=fixPathAction, dest="training_data_src_dir", help="Dir of extracted SRC faceset.")
    p.add_argument('--training-data-dst-dir', required=True, action=fixPathAction, dest="training_data_dst_dir", help="Dir of extracted DST faceset.")
    p.add_argument('--pretraining-data-dir', action=fixPathAction, dest="pretraining_data_dir", default=None, help="Optional dir of extracted faceset that will be used in pretraining mode.")
    p.add_argument('--pretrained-model-dir', action=fixPathAction, dest="pretrained_model_dir", default=None, help="Optional dir of pretrain model files. (Currently only for Quick96).")
    p.add_argument('--model-dir', required=True, action=fixPathAction, dest="model_dir", help="Saved models dir.")
    p.add_argument('--model', required=True, dest="model_name", choices=pathex.get_all_dir_names_startswith ( Path(__file__).parent / 'models' , 'Model_'), help="Model class name.")
    p.add_argument('--debug', action="store_true", dest="debug", default=False, help="Debug samples.")
    p.add_argument('--no-preview', action="store_true", dest="no_preview", default=False, help="Disable preview window.")
    p.add_argument('--force-model-name', dest="force_model_name", default=None, help="Forcing to choose model name from model/ folder.")
    p.add_argument('--cpu-only', action="store_true", dest="cpu_only", default=False, help="Train on CPU.")
    p.add_argument('--force-gpu-idxs', dest="force_gpu_idxs", default=None, help="Force to choose GPU indexes separated by comma.")
    p.add_argument('--execute-program', dest="execute_program", default=[], action='append', nargs='+')
    p.set_defaults (func=process_train)

    def process_merge(arguments):
        osex.set_process_lowest_prio()
        from mainscripts import Merger
        Merger.main ( model_class_name       = arguments.model_name,
                      saved_models_path      = Path(arguments.model_dir),
                      training_data_src_path = Path(arguments.training_data_src_dir) if arguments.training_data_src_dir is not None else None,
                      force_model_name       = arguments.force_model_name,
                      input_path             = Path(arguments.input_dir),
                      output_path            = Path(arguments.output_dir),
                      output_mask_path       = Path(arguments.output_mask_dir),
                      aligned_path           = Path(arguments.aligned_dir) if arguments.aligned_dir is not None else None,
                      force_gpu_idxs         = arguments.force_gpu_idxs,
                      cpu_only               = arguments.cpu_only)

    p = subparsers.add_parser( "merge", help="Merger")
    p.add_argument('--training-data-src-dir', action=fixPathAction, dest="training_data_src_dir", default=None, help="(optional, may be required by some models) Dir of extracted SRC faceset.")
    p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input directory. A directory containing the files you wish to process.")
    p.add_argument('--output-dir', required=True, action=fixPathAction, dest="output_dir", help="Output directory. This is where the merged files will be stored.")
    p.add_argument('--output-mask-dir', required=True, action=fixPathAction, dest="output_mask_dir", help="Output mask directory. This is where the mask files will be stored.")
    p.add_argument('--aligned-dir', action=fixPathAction, dest="aligned_dir", default=None, help="Aligned directory. This is where the extracted of dst faces stored.")
    p.add_argument('--model-dir', required=True, action=fixPathAction, dest="model_dir", help="Model dir.")
    p.add_argument('--model', required=True, dest="model_name", choices=pathex.get_all_dir_names_startswith ( Path(__file__).parent / 'models' , 'Model_'), help="Model class name.")
    p.add_argument('--force-model-name', dest="force_model_name", default=None, help="Forcing to choose model name from model/ folder.")
    p.add_argument('--cpu-only', action="store_true", dest="cpu_only", default=False, help="Merge on CPU.")
    p.add_argument('--force-gpu-idxs', dest="force_gpu_idxs", default=None, help="Force to choose GPU indexes separated by comma.")
    p.set_defaults(func=process_merge)

    videoed_parser = subparsers.add_parser( "videoed", help="Video processing.").add_subparsers()

    def process_videoed_extract_video(arguments):
        osex.set_process_lowest_prio()
        from mainscripts import VideoEd
        VideoEd.extract_video (arguments.input_file, arguments.output_dir, arguments.output_ext, arguments.fps)
    p = videoed_parser.add_parser( "extract-video", help="Extract images from video file.")
    p.add_argument('--input-file', required=True, action=fixPathAction, dest="input_file", help="Input file to be processed. Specify .*-extension to find first file.")
    p.add_argument('--output-dir', required=True, action=fixPathAction, dest="output_dir", help="Output directory. This is where the extracted images will be stored.")
    p.add_argument('--output-ext', dest="output_ext", default=None, help="Image format (extension) of output files.")
    p.add_argument('--fps', type=int, dest="fps", default=None, help="How many frames of every second of the video will be extracted. 0 - full fps.")
    p.set_defaults(func=process_videoed_extract_video)

    def process_videoed_cut_video(arguments):
        osex.set_process_lowest_prio()
        from mainscripts import VideoEd
        VideoEd.cut_video (arguments.input_file,
                           arguments.from_time,
                           arguments.to_time,
                           arguments.audio_track_id,
                           arguments.bitrate)
    p = videoed_parser.add_parser( "cut-video", help="Cut video file.")
    p.add_argument('--input-file', required=True, action=fixPathAction, dest="input_file", help="Input file to be processed. Specify .*-extension to find first file.")
    p.add_argument('--from-time', dest="from_time", default=None, help="From time, for example 00:00:00.000")
    p.add_argument('--to-time', dest="to_time", default=None, help="To time, for example 00:00:00.000")
    p.add_argument('--audio-track-id', type=int, dest="audio_track_id", default=None, help="Specify audio track id.")
    p.add_argument('--bitrate', type=int, dest="bitrate", default=None, help="Bitrate of output file in Megabits.")
    p.set_defaults(func=process_videoed_cut_video)

    def process_videoed_denoise_image_sequence(arguments):
        osex.set_process_lowest_prio()
        from mainscripts import VideoEd
        VideoEd.denoise_image_sequence (arguments.input_dir, arguments.ext, arguments.factor)
    p = videoed_parser.add_parser( "denoise-image-sequence", help="Denoise sequence of images, keeping sharp edges. This allows you to make the final fake more believable, since the neural network is not able to make a detailed skin texture, but it makes the edges quite clear. Therefore, if the whole frame is more `blurred`, then a fake will seem more believable. Especially true for scenes of the film, which are usually very clear.")
    p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input file to be processed. Specify .*-extension to find first file.")
    p.add_argument('--ext', dest="ext", default=None, help="Image format (extension) of input files.")
    p.add_argument('--factor', type=int, dest="factor", default=None, help="Denoise factor (1-20).")
    p.set_defaults(func=process_videoed_denoise_image_sequence)

    def process_videoed_video_from_sequence(arguments):
        osex.set_process_lowest_prio()
        from mainscripts import VideoEd
        VideoEd.video_from_sequence (input_dir      = arguments.input_dir,
                                     output_file    = arguments.output_file,
                                     reference_file = arguments.reference_file,
                                     ext      = arguments.ext,
                                     fps      = arguments.fps,
                                     bitrate  = arguments.bitrate,
                                     include_audio = arguments.include_audio,
                                     lossless = arguments.lossless)

    p = videoed_parser.add_parser( "video-from-sequence", help="Make video from image sequence.")
    p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input file to be processed. Specify .*-extension to find first file.")
    p.add_argument('--output-file', required=True, action=fixPathAction, dest="output_file", help="Input file to be processed. Specify .*-extension to find first file.")
    p.add_argument('--reference-file', action=fixPathAction, dest="reference_file", help="Reference file used to determine proper FPS and transfer audio from it. Specify .*-extension to find first file.")
    p.add_argument('--ext', dest="ext", default='png', help="Image format (extension) of input files.")
    p.add_argument('--fps', type=int, dest="fps", default=None, help="FPS of output file. Overwritten by reference-file.")
    p.add_argument('--bitrate', type=int, dest="bitrate", default=None, help="Bitrate of output file in Megabits.")
    p.add_argument('--include-audio', action="store_true", dest="include_audio", default=False, help="Include audio from reference file.")
    p.add_argument('--lossless', action="store_true", dest="lossless", default=False, help="PNG codec.")

    p.set_defaults(func=process_videoed_video_from_sequence)

    def process_labelingtool_edit_mask(arguments):
        from mainscripts import MaskEditorTool
        MaskEditorTool.mask_editor_main (arguments.input_dir, arguments.confirmed_dir, arguments.skipped_dir, no_default_mask=arguments.no_default_mask)

    labeling_parser = subparsers.add_parser( "labelingtool", help="Labeling tool.").add_subparsers()
    p = labeling_parser.add_parser ( "edit_mask", help="")
    p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input directory of aligned faces.")
    p.add_argument('--confirmed-dir', required=True, action=fixPathAction, dest="confirmed_dir", help="This is where the labeled faces will be stored.")
    p.add_argument('--skipped-dir', required=True, action=fixPathAction, dest="skipped_dir", help="This is where the labeled faces will be stored.")
    p.add_argument('--no-default-mask', action="store_true", dest="no_default_mask", default=False, help="Don't use default mask.")

    p.set_defaults(func=process_labelingtool_edit_mask)

    facesettool_parser = subparsers.add_parser( "facesettool", help="Faceset tools.").add_subparsers()

    def process_faceset_enhancer(arguments):
        osex.set_process_lowest_prio()
        from mainscripts import FacesetEnhancer
        FacesetEnhancer.process_folder ( Path(arguments.input_dir),
                                         cpu_only=arguments.cpu_only,
                                         force_gpu_idxs=arguments.force_gpu_idxs
                                       )

    p = facesettool_parser.add_parser ("enhance", help="Enhance details in DFL faceset.")
    p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input directory of aligned faces.")
    p.add_argument('--cpu-only', action="store_true", dest="cpu_only", default=False, help="Process on CPU.")
    p.add_argument('--force-gpu-idxs', dest="force_gpu_idxs", default=None, help="Force to choose GPU indexes separated by comma.")

    p.set_defaults(func=process_faceset_enhancer)

    """
    def process_relight_faceset(arguments):
        osex.set_process_lowest_prio()
        from mainscripts import FacesetRelighter
        FacesetRelighter.relight (arguments.input_dir, arguments.lighten, arguments.random_one)

    def process_delete_relighted(arguments):
        osex.set_process_lowest_prio()
        from mainscripts import FacesetRelighter
        FacesetRelighter.delete_relighted (arguments.input_dir)

    p = facesettool_parser.add_parser ("relight", help="Synthesize new faces from existing ones by relighting them. With the relighted faces neural network will better reproduce face shadows.")
    p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input directory of aligned faces.")
    p.add_argument('--lighten', action="store_true", dest="lighten", default=None, help="Lighten the faces.")
    p.add_argument('--random-one', action="store_true", dest="random_one", default=None, help="Relight the faces only with one random direction, otherwise relight with all directions.")
    p.set_defaults(func=process_relight_faceset)

    p = facesettool_parser.add_parser ("delete_relighted", help="Delete relighted faces.")
    p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input directory of aligned faces.")
    p.set_defaults(func=process_delete_relighted)
    """

    def bad_args(arguments):
        parser.print_help()
        exit(0)
    parser.set_defaults(func=bad_args)

    arguments = parser.parse_args()
    arguments.func(arguments)

    print ("Done.")

'''
import code
code.interact(local=dict(globals(), **locals()))
'''