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https://github.com/iperov/DeepFaceLab.git
synced 2025-07-06 21:12:07 -07:00
added VideoEd - operating video files by ffmpeg from python.
This commit is contained in:
iperov
parent
e0907423a9
commit
4196e962a8
6 changed files with 275 additions and 3 deletions
60
main.py
60
main.py
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@ -120,9 +120,65 @@ if __name__ == "__main__":
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convert_parser.add_argument('--debug', action="store_true", dest="debug", default=False, help="Debug converter.")
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convert_parser.add_argument('--force-gpu-idx', type=int, dest="force_gpu_idx", default=-1, help="Force to choose this GPU idx.")
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convert_parser.add_argument('--cpu-only', action="store_true", dest="cpu_only", default=False, help="Convert on CPU.")
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convert_parser.set_defaults(func=process_convert)
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videoed_parser = subparsers.add_parser( "videoed", help="Video processing.").add_subparsers()
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def process_videoed_extract_video(arguments):
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from mainscripts import VideoEd
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VideoEd.extract_video (arguments.input_file, arguments.output_dir, arguments.output_ext, arguments.fps)
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p = videoed_parser.add_parser( "extract-video", help="Extract images from video file.")
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p.add_argument('--input-file', required=True, action=fixPathAction, dest="input_file", help="Input file to be processed. Specify .*-extension to find first file.")
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p.add_argument('--output-dir', required=True, action=fixPathAction, dest="output_dir", help="Output directory. This is where the extracted images will be stored.")
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p.add_argument('--ouptut-ext', dest="output_ext", default='png', help="Image format (extension) of output files.")
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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.")
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p.set_defaults(func=process_videoed_extract_video)
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def process_videoed_cut_video(arguments):
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from mainscripts import VideoEd
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VideoEd.cut_video (arguments.input_file,
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arguments.from_time,
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arguments.to_time,
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arguments.audio_track_id,
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arguments.bitrate)
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p = videoed_parser.add_parser( "cut-video", help="Cut video file.")
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p.add_argument('--input-file', required=True, action=fixPathAction, dest="input_file", help="Input file to be processed. Specify .*-extension to find first file.")
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p.add_argument('--from-time', dest="from_time", default=None, help="From time, for example 00:00:00.000")
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p.add_argument('--to-time', dest="to_time", default=None, help="To time, for example 00:00:00.000")
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p.add_argument('--audio-track-id', type=int, dest="audio_track_id", default=None, help="Specify audio track id.")
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p.add_argument('--bitrate', type=int, dest="bitrate", default=None, help="Bitrate of output file in Megabits.")
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p.set_defaults(func=process_videoed_cut_video)
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def process_videoed_denoise_image_sequence(arguments):
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from mainscripts import VideoEd
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VideoEd.denoise_image_sequence (arguments.input_dir, arguments.ext, arguments.factor)
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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.")
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p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input file to be processed. Specify .*-extension to find first file.")
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p.add_argument('--ext', dest="ext", default='png', help="Image format (extension) of input files.")
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p.add_argument('--factor', type=int, dest="factor", default=None, help="Denoise factor (1-20).")
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p.set_defaults(func=process_videoed_denoise_image_sequence)
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def process_videoed_video_from_sequence(arguments):
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from mainscripts import VideoEd
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VideoEd.video_from_sequence (arguments.input_dir,
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arguments.output_file,
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arguments.reference_file,
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arguments.ext,
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arguments.fps,
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arguments.bitrate,
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arguments.lossless)
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p = videoed_parser.add_parser( "video-from-sequence", help="Make video from image sequence.")
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p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input file to be processed. Specify .*-extension to find first file.")
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p.add_argument('--output-file', required=True, action=fixPathAction, dest="output_file", help="Input file to be processed. Specify .*-extension to find first file.")
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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.")
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p.add_argument('--ext', dest="ext", default='png', help="Image format (extension) of input files.")
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p.add_argument('--fps', type=int, dest="fps", default=None, help="FPS of output file. Overwritten by reference-file.")
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p.add_argument('--bitrate', type=int, dest="bitrate", default=None, help="Bitrate of output file in Megabits.")
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p.add_argument('--lossless', action="store_true", dest="lossless", default=False, help="PNG codec.")
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p.set_defaults(func=process_videoed_video_from_sequence)
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def bad_args(arguments):
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parser.print_help()
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exit(0)
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199
mainscripts/VideoEd.py
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199
mainscripts/VideoEd.py
Normal file
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@ -0,0 +1,199 @@
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import subprocess
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import numpy as np
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import ffmpeg
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from pathlib import Path
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from utils import Path_utils
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from interact import interact as io
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def extract_video(input_file, output_dir, output_ext=None, fps=None):
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input_file_path = Path(input_file)
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output_path = Path(output_dir)
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if not output_path.exists():
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output_path.mkdir(exist_ok=True)
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if input_file_path.suffix == '.*':
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input_file_path = Path_utils.get_first_file_by_stem (input_file_path.parent, input_file_path.stem)
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else:
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if not input_file_path.exists():
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input_file_path = None
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if input_file_path is None:
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io.log_err("input_file not found.")
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return
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if output_ext is None:
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output_ext = io.input_str ("Output image format (extension)? ( default:png ) : ", "png")
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if fps is None:
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fps = io.input_int ("Enter FPS ( ?:help skip:fullfps ) : ", 0, help_message="How many frames of every second of the video will be extracted.")
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for filename in Path_utils.get_image_paths (output_path, ['.'+output_ext]):
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Path(filename).unlink()
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job = ffmpeg.input(str(input_file_path))
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kwargs = {}
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if fps != 0:
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kwargs.update ({'r':str(fps)})
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job = job.output( str (output_path / ('%5d.'+output_ext)), **kwargs )
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try:
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job = job.run()
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except:
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io.log_err ("ffmpeg fail, job commandline:" + str(job.compile()) )
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def cut_video ( input_file, from_time=None, to_time=None, audio_track_id=None, bitrate=None):
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input_file_path = Path(input_file)
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if input_file_path is None:
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io.log_err("input_file not found.")
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return
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output_file_path = input_file_path.parent / (input_file_path.stem + "_cut" + input_file_path.suffix)
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if from_time is None:
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from_time = io.input_str ("From time (skip: 00:00:00.000) : ", "00:00:00.000")
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if to_time is None:
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to_time = io.input_str ("To time (skip: 00:00:00.000) : ", "00:00:00.000")
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if audio_track_id is None:
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audio_track_id = io.input_int ("Specify audio track id. ( skip:0 ) : ", 0)
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if bitrate is None:
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bitrate = max (1, io.input_int ("Bitrate of output file in MB/s ? (default:25) : ", 25) )
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from_time = "0:0:04.34"
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to_time = "0:0:10.000"
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kwargs = {"c:v": "libx264",
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"b:v": "%dM" %(bitrate),
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"pix_fmt": "yuv420p",
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}
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job = ffmpeg.input(str(input_file_path), ss=from_time, to=to_time)
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job_v = job['v:0']
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job_a = job['a:' + str(audio_track_id) + '?' ]
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job = ffmpeg.output (job_v, job_a, str(output_file_path), **kwargs)
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try:
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job = job.run()
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except:
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io.log_err ("ffmpeg fail, job commandline:" + str(job.compile()) )
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def denoise_image_sequence( input_dir, ext=None, factor=None ):
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input_path = Path(input_dir)
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if not input_path.exists():
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io.log_err("input_dir not found.")
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return
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if ext is None:
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ext = io.input_str ("Input image format (extension)? ( default:png ) : ", "png")
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if factor is None:
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factor = np.clip ( io.input_int ("Denoise factor? (1-20 default:5) : ", 5), 1, 20 )
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job = ( ffmpeg
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.input(str ( input_path / ('%5d.'+ext) ) )
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.filter("hqdn3d", factor, factor, 5,5)
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.output(str ( input_path / ('%5d.'+ext) ) )
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)
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try:
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job = job.run()
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except:
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io.log_err ("ffmpeg fail, job commandline:" + str(job.compile()) )
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def video_from_sequence( input_dir, output_file, reference_file=None, ext=None, fps=None, bitrate=None, lossless=None ):
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input_path = Path(input_dir)
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output_file_path = Path(output_file)
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reference_file_path = Path(reference_file) if reference_file is not None else None
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if not input_path.exists():
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io.log_err("input_dir not found.")
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return
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if not output_file_path.parent.exists():
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output_file_path.parent.mkdir(parents=True, exist_ok=True)
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return
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out_ext = output_file_path.suffix
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if ext is None:
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ext = io.input_str ("Input image format (extension)? ( default:png ) : ", "png")
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if lossless is None:
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lossless = io.input_bool ("Use lossless codec ? ( default:no ) : ", False)
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video_id = None
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audio_id = None
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ref_in_a = None
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if reference_file_path is not None:
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if reference_file_path.suffix == '.*':
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reference_file_path = Path_utils.get_first_file_by_stem (reference_file_path.parent, reference_file_path.stem)
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else:
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if not reference_file_path.exists():
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reference_file_path = None
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if reference_file_path is None:
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io.log_err("reference_file not found.")
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return
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#probing reference file
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probe = ffmpeg.probe (str(reference_file_path))
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#getting first video and audio streams id with fps
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for stream in probe['streams']:
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if video_id is None and stream['codec_type'] == 'video':
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video_id = stream['index']
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fps = stream['r_frame_rate']
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if audio_id is None and stream['codec_type'] == 'audio':
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audio_id = stream['index']
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if audio_id is not None:
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#has audio track
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ref_in_a = ffmpeg.input (str(reference_file_path))[str(audio_id)]
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if fps is None:
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#if fps not specified and not overwritten by reference-file
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fps = max (1, io.input_int ("FPS ? (default:25) : ", 25) )
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if not lossless and bitrate is None:
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bitrate = max (1, io.input_int ("Bitrate of output file in MB/s ? (default:16) : ", 16) )
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i_in = ffmpeg.input(str (input_path / ('%5d.'+ext)), r=fps)
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output_args = [i_in]
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if ref_in_a is not None:
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output_args += [ref_in_a]
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output_args += [str (output_file_path)]
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output_kwargs = {}
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if lossless:
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output_kwargs.update ({"c:v": "png"
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})
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else:
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output_kwargs.update ({"c:v": "libx264",
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"b:v": "%dM" %(bitrate),
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"pix_fmt": "yuv420p",
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})
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output_kwargs.update ({"c:a": "aac",
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"b:a": "192k",
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"ar" : "48000"
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})
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job = ( ffmpeg.output(*output_args, **output_kwargs).overwrite_output() )
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try:
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job = job.run()
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except:
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io.log_err ("ffmpeg fail, job commandline:" + str(job.compile()) )
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@ -8,4 +8,5 @@ tensorflow==1.13.1
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scikit-image
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dlib==19.16.0
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tqdm
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ffmpeg-python==0.1.17
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git+https://www.github.com/keras-team/keras-contrib.git
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@ -9,4 +9,5 @@ plaidml-keras==0.5.0
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scikit-image
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dlib==19.16.0
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tqdm
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ffmpeg-python==0.1.17
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git+https://www.github.com/keras-team/keras-contrib.git
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@ -8,4 +8,5 @@ tensorflow==1.13.1
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plaidml-keras==0.5.0
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scikit-image
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tqdm
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ffmpeg-python==0.1.17
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git+https://www.github.com/keras-team/keras-contrib.git
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@ -3,7 +3,7 @@ from scandir import scandir
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image_extensions = [".jpg", ".jpeg", ".png", ".tif", ".tiff"]
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def get_image_paths(dir_path):
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def get_image_paths(dir_path, image_extensions=image_extensions):
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dir_path = Path (dir_path)
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result = []
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@ -38,3 +38,17 @@ def get_all_dir_names_startswith (dir_path, startswith):
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if x.name.lower().startswith(startswith):
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result.append ( x.name[len(startswith):] )
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return result
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def get_first_file_by_stem (dir_path, stem, exts=None):
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dir_path = Path (dir_path)
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stem = stem.lower()
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if dir_path.exists():
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for x in list(scandir(str(dir_path))):
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if not x.is_file():
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continue
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xp = Path(x.path)
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if xp.stem.lower() == stem and (exts is None or xp.suffix.lower() in exts):
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return xp
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return None
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