mirror of
https://github.com/iperov/DeepFaceLab.git
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SAEHD: added new option GAN power 0.0 .. 10.0 Train the network in Generative Adversarial manner. Forces the neural network to learn small details of the face. You can enable/disable this option at any time, but better to enable it when the network is trained enough. Typical value is 1.0 GAN power with pretrain mode will not work. Example of enabling GAN on 81k iters +5k iters https://i.imgur.com/OdXHLhU.jpg https://i.imgur.com/CYAJmJx.jpg dfhd: default Decoder dimensions are now 48 the preview for 256 res is now correctly displayed fixed model naming/renaming/removing Improvements for those involved in post-processing in AfterEffects: Codec is reverted back to x264 in order to properly use in AfterEffects and video players. Merger now always outputs the mask to workspace\data_dst\merged_mask removed raw modes except raw-rgb raw-rgb mode now outputs selected face mask_mode (before square mask) 'export alpha mask' button is replaced by 'show alpha mask'. You can view the alpha mask without recompute the frames. 8) 'merged *.bat' now also output 'result_mask.' video file. 8) 'merged lossless' now uses x264 lossless codec (before PNG codec) result_mask video file is always lossless. Thus you can use result_mask video file as mask layer in the AfterEffects.
217 lines
6.9 KiB
Python
217 lines
6.9 KiB
Python
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 core import pathex
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from core.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 = pathex.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 fps is None:
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fps = io.input_int ("Enter FPS", 0, help_message="How many frames of every second of the video will be extracted. 0 - full fps")
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if output_ext is None:
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output_ext = io.input_str ("Output image format", "png", ["png","jpg"], help_message="png is lossless, but extraction is x10 slower for HDD, requires x10 more disk space than jpg.")
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for filename in pathex.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 = {'pix_fmt': 'rgb24'}
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if fps != 0:
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kwargs.update ({'r':str(fps)})
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if output_ext == 'jpg':
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kwargs.update ({'q:v':'2'}) #highest quality for jpg
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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", "00:00:00.000")
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if to_time is None:
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to_time = io.input_str ("To time", "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.", 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", 25) )
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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).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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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)", "png")
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if factor is None:
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factor = np.clip ( io.input_int ("Denoise factor?", 5, add_info="1-20"), 1, 20 )
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kwargs = {}
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if ext == 'jpg':
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kwargs.update ({'q:v':'2'})
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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) ), **kwargs )
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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, include_audio=False, 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)", "png")
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if lossless is None:
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lossless = io.input_bool ("Use lossless codec", 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 = pathex.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 ("Enter FPS", 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", 16) )
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input_image_paths = pathex.get_image_paths(input_path)
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i_in = ffmpeg.input('pipe:', format='image2pipe', r=fps)
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output_args = [i_in]
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if include_audio and 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": "libx264",
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"crf": "0",
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"pix_fmt": "yuv420p",
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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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if include_audio and ref_in_a is not None:
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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_run = job.run_async(pipe_stdin=True)
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for image_path in input_image_paths:
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with open (image_path, "rb") as f:
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image_bytes = f.read()
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job_run.stdin.write (image_bytes)
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job_run.stdin.close()
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job_run.wait()
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except:
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io.log_err ("ffmpeg fail, job commandline:" + str(job.compile()) )
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