def write_remix_video(remix_filenames, video_filename):
# Concatenate clips together
video_file_clips = [
VideoFileClip(remix_filename) for remix_filename in remix_filenames
]
remix_video = concatenate_videoclips(video_file_clips)
remix_filename = REMIX_DIRECTORY + 'remix-' + video_filename
remix_filename_noaudio = remix_filename.replace('.mp4', '-noaudio.mp4')
remix_video.write_videofile(remix_filename_noaudio)
audio_filename = AUDIO_DIRECTORY + video_filename.replace('mp4', 'mp3')
ffmpeg_extract_audio(VIDEO_DIRECTORY + video_filename, audio_filename)
ffmpeg_merge_video_audio(remix_filename_noaudio, audio_filename,
remix_filename)
os.remove(remix_filename_noaudio)
def merge_audio_and_video(videofname, audiofname, outputfile):
logger.debug("Merging video and audio data...")
ffmpeg_tools.ffmpeg_merge_video_audio(videofname, audiofname, outputfile)
def merge_audio_video(self):
print("Merging audio and video.")
self.get_audio_clip()
mv.ffmpeg_merge_video_audio(self.tempresult, self.audiofile,
self.result)
remove(self.audiofile)
def set_audio(self):
print("set audio...")
audio = self.__audio_concat()
cis.wavwrite(self.outfile+".wav", self.afps, audio)
ffmpeg_merge_video_audio(video=self.outfile+".avi", audio=self.outfile+".wav", output=self.outfile+"_demo.avi")
def ffwd_video(path_in,
path_out,
checkpoint_dir,
device_t='/gpu:0',
batch_size=4):
video_clip = VideoFileClip(path_in, audio=False)
# Create a temporary file to store the audio.
fp = tempfile.NamedTemporaryFile(suffix='.aac')
temp_audio_file_name = fp.name
fp.close()
# Create a temporary file to store the video.
fp = tempfile.NamedTemporaryFile(suffix='.mp4')
temp_video_file_name = fp.name
fp.close()
# Extract the audio.
ffmpeg_tools.ffmpeg_extract_audio(path_in, temp_audio_file_name)
video_writer = ffmpeg_writer.FFMPEG_VideoWriter(
temp_video_file_name,
video_clip.size,
video_clip.fps,
codec="libx264",
preset="medium",
audiofile=None,
threads=None,
ffmpeg_params=["-b:v", "2000k"])
g = tf.Graph()
soft_config = tf.compat.v1.ConfigProto(allow_soft_placement=True)
soft_config.gpu_options.allow_growth = True
with g.as_default(), g.device(device_t), \
tf.compat.v1.Session(config=soft_config) as sess:
batch_shape = (batch_size, video_clip.size[1], video_clip.size[0], 3)
img_placeholder = tf.compat.v1.placeholder(tf.float32,
shape=batch_shape,
name='img_placeholder')
preds = src.transform.net(img_placeholder)
saver = tf.compat.v1.train.Saver()
if os.path.isdir(checkpoint_dir):
ckpt = tf.train.get_checkpoint_state(checkpoint_dir)
if ckpt and ckpt.model_checkpoint_path:
saver.restore(sess, ckpt.model_checkpoint_path)
else:
raise Exception("No checkpoint found...")
else:
saver.restore(sess, checkpoint_dir)
X = np.zeros(batch_shape, dtype=np.float32)
def style_and_write(count):
for i in range(count, batch_size):
X[i] = X[count - 1] # Use last frame to fill X
_preds = sess.run(preds, feed_dict={img_placeholder: X})
for i in range(0, count):
video_writer.write_frame(
np.clip(_preds[i], 0, 255).astype(np.uint8))
frame_count = 0 # The frame count that written to X
for frame in video_clip.iter_frames():
X[frame_count] = frame
frame_count += 1
if frame_count == batch_size:
style_and_write(frame_count)
frame_count = 0
if frame_count != 0:
style_and_write(frame_count)
video_writer.close()
# Merge audio and video
ffmpeg_tools.ffmpeg_merge_video_audio(temp_video_file_name,
temp_audio_file_name, path_out)
# Delete temporary files
os.remove(temp_video_file_name)
os.remove(temp_audio_file_name)