DeepFaceLab/mainscripts/VideoEd.py
Colombo 123bccf01a returned back
3.optional) denoise data_dst images.bat
	Apply it if dst video is very sharp.

	Denoise dst images before face extraction.
	This technique helps neural network not to learn the noise.
	The result is less pixel shake of the predicted face.
2020-03-07 15:51:30 +04:00

271 lines
8.9 KiB
Python

import subprocess
import numpy as np
import ffmpeg
from pathlib import Path
from core import pathex
from core.interact import interact as io
def extract_video(input_file, output_dir, output_ext=None, fps=None):
input_file_path = Path(input_file)
output_path = Path(output_dir)
if not output_path.exists():
output_path.mkdir(exist_ok=True)
if input_file_path.suffix == '.*':
input_file_path = pathex.get_first_file_by_stem (input_file_path.parent, input_file_path.stem)
else:
if not input_file_path.exists():
input_file_path = None
if input_file_path is None:
io.log_err("input_file not found.")
return
if fps is None:
fps = io.input_int ("Enter FPS", 0, help_message="How many frames of every second of the video will be extracted. 0 - full fps")
if output_ext is None:
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.")
for filename in pathex.get_image_paths (output_path, ['.'+output_ext]):
Path(filename).unlink()
job = ffmpeg.input(str(input_file_path))
kwargs = {'pix_fmt': 'rgb24'}
if fps != 0:
kwargs.update ({'r':str(fps)})
if output_ext == 'jpg':
kwargs.update ({'q:v':'2'}) #highest quality for jpg
job = job.output( str (output_path / ('%5d.'+output_ext)), **kwargs )
try:
job = job.run()
except:
io.log_err ("ffmpeg fail, job commandline:" + str(job.compile()) )
def cut_video ( input_file, from_time=None, to_time=None, audio_track_id=None, bitrate=None):
input_file_path = Path(input_file)
if input_file_path is None:
io.log_err("input_file not found.")
return
output_file_path = input_file_path.parent / (input_file_path.stem + "_cut" + input_file_path.suffix)
if from_time is None:
from_time = io.input_str ("From time", "00:00:00.000")
if to_time is None:
to_time = io.input_str ("To time", "00:00:00.000")
if audio_track_id is None:
audio_track_id = io.input_int ("Specify audio track id.", 0)
if bitrate is None:
bitrate = max (1, io.input_int ("Bitrate of output file in MB/s", 25) )
kwargs = {"c:v": "libx264",
"b:v": "%dM" %(bitrate),
"pix_fmt": "yuv420p",
}
job = ffmpeg.input(str(input_file_path), ss=from_time, to=to_time)
job_v = job['v:0']
job_a = job['a:' + str(audio_track_id) + '?' ]
job = ffmpeg.output(job_v, job_a, str(output_file_path), **kwargs).overwrite_output()
try:
job = job.run()
except:
io.log_err ("ffmpeg fail, job commandline:" + str(job.compile()) )
def denoise_image_sequence( input_dir, ext=None, factor=None ):
input_path = Path(input_dir)
if not input_path.exists():
io.log_err("input_dir not found.")
return
image_paths = [ Path(filepath) for filepath in pathex.get_image_paths(input_path) ]
# Check extension of all images
image_paths_suffix = None
for filepath in image_paths:
if image_paths_suffix is None:
image_paths_suffix = filepath.suffix
else:
if filepath.suffix != image_paths_suffix:
io.log_err(f"All images in {input_path.name} should be with the same extension.")
return
if factor is None:
factor = np.clip ( io.input_int ("Denoise factor?", 7, add_info="1-20"), 1, 20 )
# Rename to temporary filenames
for i,filepath in io.progress_bar_generator( enumerate(image_paths), "Renaming", leave=False):
src = filepath
dst = filepath.parent / ( f'{i+1:06}_{filepath.name}' )
try:
src.rename (dst)
except:
io.log_error ('fail to rename %s' % (src.name) )
return
# Rename to sequental filenames
for i,filepath in io.progress_bar_generator( enumerate(image_paths), "Renaming", leave=False):
src = filepath.parent / ( f'{i+1:06}_{filepath.name}' )
dst = filepath.parent / ( f'{i+1:06}{filepath.suffix}' )
try:
src.rename (dst)
except:
io.log_error ('fail to rename %s' % (src.name) )
return
# Process image sequence in ffmpeg
kwargs = {}
if image_paths_suffix == '.jpg':
kwargs.update ({'q:v':'2'})
job = ( ffmpeg
.input(str ( input_path / ('%6d'+image_paths_suffix) ) )
.filter("hqdn3d", factor, factor, 5,5)
.output(str ( input_path / ('%6d'+image_paths_suffix) ), **kwargs )
)
try:
job = job.run()
except:
io.log_err ("ffmpeg fail, job commandline:" + str(job.compile()) )
# Rename to temporary filenames
for i,filepath in io.progress_bar_generator( enumerate(image_paths), "Renaming", leave=False):
src = filepath.parent / ( f'{i+1:06}{filepath.suffix}' )
dst = filepath.parent / ( f'{i+1:06}_{filepath.name}' )
try:
src.rename (dst)
except:
io.log_error ('fail to rename %s' % (src.name) )
return
# Rename to initial filenames
for i,filepath in io.progress_bar_generator( enumerate(image_paths), "Renaming", leave=False):
src = filepath.parent / ( f'{i+1:06}_{filepath.name}' )
dst = filepath
try:
src.rename (dst)
except:
io.log_error ('fail to rename %s' % (src.name) )
return
def video_from_sequence( input_dir, output_file, reference_file=None, ext=None, fps=None, bitrate=None, include_audio=False, lossless=None ):
input_path = Path(input_dir)
output_file_path = Path(output_file)
reference_file_path = Path(reference_file) if reference_file is not None else None
if not input_path.exists():
io.log_err("input_dir not found.")
return
if not output_file_path.parent.exists():
output_file_path.parent.mkdir(parents=True, exist_ok=True)
return
out_ext = output_file_path.suffix
if ext is None:
ext = io.input_str ("Input image format (extension)", "png")
if lossless is None:
lossless = io.input_bool ("Use lossless codec", False)
video_id = None
audio_id = None
ref_in_a = None
if reference_file_path is not None:
if reference_file_path.suffix == '.*':
reference_file_path = pathex.get_first_file_by_stem (reference_file_path.parent, reference_file_path.stem)
else:
if not reference_file_path.exists():
reference_file_path = None
if reference_file_path is None:
io.log_err("reference_file not found.")
return
#probing reference file
probe = ffmpeg.probe (str(reference_file_path))
#getting first video and audio streams id with fps
for stream in probe['streams']:
if video_id is None and stream['codec_type'] == 'video':
video_id = stream['index']
fps = stream['r_frame_rate']
if audio_id is None and stream['codec_type'] == 'audio':
audio_id = stream['index']
if audio_id is not None:
#has audio track
ref_in_a = ffmpeg.input (str(reference_file_path))[str(audio_id)]
if fps is None:
#if fps not specified and not overwritten by reference-file
fps = max (1, io.input_int ("Enter FPS", 25) )
if not lossless and bitrate is None:
bitrate = max (1, io.input_int ("Bitrate of output file in MB/s", 16) )
input_image_paths = pathex.get_image_paths(input_path)
i_in = ffmpeg.input('pipe:', format='image2pipe', r=fps)
output_args = [i_in]
if include_audio and ref_in_a is not None:
output_args += [ref_in_a]
output_args += [str (output_file_path)]
output_kwargs = {}
if lossless:
output_kwargs.update ({"c:v": "libx264",
"crf": "0",
"pix_fmt": "yuv420p",
})
else:
output_kwargs.update ({"c:v": "libx264",
"b:v": "%dM" %(bitrate),
"pix_fmt": "yuv420p",
})
if include_audio and ref_in_a is not None:
output_kwargs.update ({"c:a": "aac",
"b:a": "192k",
"ar" : "48000",
"strict": "experimental"
})
job = ( ffmpeg.output(*output_args, **output_kwargs).overwrite_output() )
try:
job_run = job.run_async(pipe_stdin=True)
for image_path in input_image_paths:
with open (image_path, "rb") as f:
image_bytes = f.read()
job_run.stdin.write (image_bytes)
job_run.stdin.close()
job_run.wait()
except:
io.log_err ("ffmpeg fail, job commandline:" + str(job.compile()) )