def _get_writer(self, frame_dims: Tuple[int]) -> Generator[None, np.ndarray, None]:
""" Add the requested encoding options and return the writer.
Parameters
----------
frame_dims: tuple
The (rows, colums) shape of the input image
Returns
-------
generator
The imageio ffmpeg writer
"""
audio_codec = self._audio_codec
audio_path = None if audio_codec is None else self._source_video
logger.debug("writer config: %s, audio_path: '%s'", self.config, audio_path)
retval = im_ffm.write_frames(self._output_filename,
size=(frame_dims[1], frame_dims[0]),
fps=self._video_fps,
quality=None,
codec=self.config["codec"],
macro_block_size=8,
ffmpeg_log_level="error",
ffmpeg_timeout=10,
output_params=self._output_params,
audio_path=audio_path,
audio_codec=audio_codec)
logger.debug("FFMPEG Writer created: %s", retval)
retval.send(None)
return retval
def test_write1():
for n in (1, 9, 14, 279, 280, 281):
# Prepare for writing
gen = imageio_ffmpeg.write_frames(test_file2, (64, 64))
assert isinstance(gen, types.GeneratorType)
gen.send(None) # seed
# Write n frames
for i in range(n):
data = bytes([min(255, 100 + i * 10)] * 64 * 64 * 3)
gen.send(data)
gen.close()
# Check that number of frames is correct
nframes, nsecs = imageio_ffmpeg.count_frames_and_secs(test_file2)
assert nframes == n
# Check again by actually reading
gen2 = imageio_ffmpeg.read_frames(test_file2)
gen2.__next__() # == meta
count = 0
for frame in gen2:
count += 1
assert count == n
def processvideo(file):
print('processing ' + file)
cap = cv2.VideoCapture(file)
# cap.get(3) width and cap.get(4) is heigh
if int(args.framelimit) >= 0:
if args.outputfile.startswith('udp') or args.outputfile.startswith(
'rtsp'):
print("Exporting to stream: " + args.outputfile)
writer = imageio.write_frames(args.outputfile,
(int(cap.get(3)), int(cap.get(4))),
output_params=['-f', 'mpegts'])
else:
print("Exporting to file " + args.outputfile)
writer = imageio.write_frames(args.outputfile,
(int(cap.get(3)), int(cap.get(4))))
writer.send(None)
frame_counter = 0
while (cap.isOpened()):
frame_counter = frame_counter + 1
# check limits of processed frames
if int(args.framelimit) > 0 and frame_counter > int(
args.framestart) + int(args.framelimit):
print('Processed ' + args.framelimit + 'ending...')
break
# read input frame
ret, frame = cap.read()
# throttle control
if frame_counter % int(args.fpsthrottle) != 0:
continue
# check frame start
if int(args.framestart) > 0 and frame_counter < int(args.framestart):
break
if ret == True:
if not frame is None:
print('Detecting objects in frame ' + str(frame_counter),
end="\r")
image = detect(frame)
#writer.send(frame)
writer.send(image)
else:
print('Frame error in frame ' + str(frame_counter))
else:
break
cap.release()
writer.close()
def _write_frames(pixfmt, bpp, tout):
gen = imageio_ffmpeg.write_frames(test_file2, (2048, 2048),
pix_fmt_in=pixfmt,
ffmpeg_timeout=tout)
gen.send(None) # seed
for i in range(n):
data = (255 * np.random.rand(2048 * 2048 * bpp)).astype(np.uint8)
data = bytes(data)
gen.send(data)
gen.close()
def encode_video(video: np.ndarray,
output_path: str,
fps: float,
bitrate: str = "0",
crf: int = 20) -> str:
"""Encode a video with vp9 codec via imageio-ffmpeg
Parameters
----------
video : np.ndarray
Video to be encoded
output_path : str
Desired output path for encoded video
fps : float
Desired frame rate for encoded video
pix_fmt_out : str
Desired pixel format for output encoded video, by default "yuv420p"
bitrate : str, optional
Desired bitrate of output, by default "0". The default *MUST*
be zero in order to encode in constant quality mode. Other values
will result in constrained quality mode.
crf : int, optional
Desired perceptual quality of output, by default 20. Value can
be from 0 - 63. Lower values mean better quality (but bigger video
sizes).
Returns
-------
str
Output path of the encoded video
"""
# ffmpeg expects video shape in terms of: (width, height)
video_shape = (video[0].shape[1], video[0].shape[0])
writer = mpg.write_frames(output_path,
video_shape,
pix_fmt_in="gray8",
pix_fmt_out="yuv420p",
codec="libvpx-vp9",
fps=fps,
bitrate=bitrate,
output_params=["-crf", str(crf)])
writer.send(None) # Seed ffmpeg-imageio writer generator
for frame in video:
writer.send(frame)
writer.close()
return output_path
def test_write_wmv():
# Switch to MS friendly codec when writing .wmv files
for ext, codec in [("", "h264"), (".wmv", "msmpeg4")]:
fname = test_file2 + ext
gen = imageio_ffmpeg.write_frames(fname, (64, 64))
gen.send(None) # seed
for i in range(9):
data = bytes([min(255, 100 + i * 10)] * 64 * 64 * 3)
gen.send(data)
gen.close()
#
meta = imageio_ffmpeg.read_frames(fname).__next__()
assert meta["codec"].startswith(codec)
async def write_video_to_stream(path_to_video, path_to_socket):
video_reader = imageio.get_reader(path_to_video)
sock = await create_socket(path_to_socket)
_, socket_writer = await asyncio.open_unix_connection(sock=sock)
img_writer = None
for frame in video_reader:
if img_writer is None:
img_writer = imageio_ffmpeg.write_frames(socket_writer,
size=(frame.shape[1],
frame.shape[0]))
img_writer.send(None)
img_writer.send(frame)
await socket_writer.drain()
img_writer.close()
socket_writer.close()
def test_write_close():
for i in range(N):
pids0 = get_ffmpeg_pids()
w = imageio_ffmpeg.write_frames(test_file2, (64, 64))
pids1 = get_ffmpeg_pids().difference(
pids0) # generator has not started
w.send(None)
w.send(b"x" * 64 * 64 * 3)
pids2 = get_ffmpeg_pids().difference(pids0) # now ffmpeg is running
w.close()
pids3 = get_ffmpeg_pids().difference(pids0) # now its not
assert len(pids1) == 0
assert len(pids2) == 1
assert len(pids3) == 0
def test_write_pix_fmt_in():
sizes = []
for pixfmt, bpp in [("gray", 1), ("rgb24", 3), ("rgba", 4)]:
# Prepare for writing
gen = imageio_ffmpeg.write_frames(test_file2, (64, 64), pix_fmt_in=pixfmt)
gen.send(None) # seed
for i in range(9):
data = bytes([min(255, 100 + i * 10)] * 64 * 64 * bpp)
gen.send(data)
gen.close()
with open(test_file2, "rb") as f:
sizes.append(len(f.read()))
# Check nframes
nframes, nsecs = imageio_ffmpeg.count_frames_and_secs(test_file2)
assert nframes == 9
def test_write_quality():
sizes = []
for quality in [2, 5, 9]:
# Prepare for writing
gen = imageio_ffmpeg.write_frames(test_file2, (64, 64), quality=quality)
gen.send(None) # seed
for i in range(9):
data = bytes([min(255, 100 + i * 10)] * 64 * 64 * 3)
gen.send(data)
gen.close()
with open(test_file2, "rb") as f:
sizes.append(len(f.read()))
# Check nframes
nframes, nsecs = imageio_ffmpeg.count_frames_and_secs(test_file2)
assert nframes == 9
assert sizes[0] < sizes[1] < sizes[2]
def test_write_pix_fmt_out():
sizes = []
for pixfmt in ["gray", "yuv420p"]:
# Prepare for writing
gen = imageio_ffmpeg.write_frames(test_file2, (64, 64), pix_fmt_out=pixfmt)
gen.send(None) # seed
for i in range(9):
data = bytes([min(255, 100 + i * 10)] * 64 * 64 * 3)
gen.send(data)
gen.close()
with open(test_file2, "rb") as f:
sizes.append(len(f.read()))
# Check nframes
nframes, nsecs = imageio_ffmpeg.count_frames_and_secs(test_file2)
assert nframes == 9
assert sizes[0] < sizes[1]
def test_write_macro_block_size():
frame_sizes = []
for mbz in [None, 10]: # None is default == 16
# Prepare for writing
gen = imageio_ffmpeg.write_frames(test_file2, (40, 50), macro_block_size=mbz)
gen.send(None) # seed
for i in range(9):
data = bytes([min(255, 100 + i * 10)] * 40 * 50 * 3)
gen.send(data)
gen.close()
# Check nframes
nframes, nsecs = imageio_ffmpeg.count_frames_and_secs(test_file2)
assert nframes == 9
# Check size
meta = imageio_ffmpeg.read_frames(test_file2).__next__()
frame_sizes.append(meta["size"])
assert frame_sizes[0] == (48, 64)
assert frame_sizes[1] == (40, 50)
def test_write_bitrate():
# Mind that we send uniform images, so the difference is marginal
sizes = []
for bitrate in ["1k", "10k", "100k"]:
# Prepare for writing
gen = imageio_ffmpeg.write_frames(test_file2, (64, 64), bitrate=bitrate)
gen.send(None) # seed
for i in range(9):
data = bytes([min(255, 100 + i * 10)] * 64 * 64 * 3)
gen.send(data)
gen.close()
with open(test_file2, "rb") as f:
sizes.append(len(f.read()))
# Check nframes
nframes, nsecs = imageio_ffmpeg.count_frames_and_secs(test_file2)
assert nframes == 9
assert sizes[0] < sizes[1] < sizes[2]
def processvideo(file):
cap = cv2.VideoCapture(file)
writer = imageio.write_frames(args.outputfile, (int(cap.get(3)), int(cap.get(4))))
writer.send(None)
frame_counter = 0
while(cap.isOpened()):
frame_counter = frame_counter + 1
ret, frame = cap.read()
print('Detecting objects in frame ' + str(frame_counter))
if ret==True:
if not frame is None:
image = detect(frame)
writer.send(frame)
else:
print('Frame error in frame ' + str(frame_counter))
else:
break
cap.release()
writer.close()
def test_write_audio_path():
# Provide an audio
gen = imageio_ffmpeg.write_frames(test_file2, (64, 64),
audio_path=test_file3,
audio_codec="aac")
gen.send(None) # seed
for i in range(9):
data = bytes([min(255, 100 + i * 10)] * 64 * 64 * 3)
gen.send(data)
gen.close()
# Check nframes
nframes, nsecs = imageio_ffmpeg.count_frames_and_secs(test_file2)
assert nframes == 9
# Check size
meta = imageio_ffmpeg.read_frames(test_file2).__next__()
audio_codec = meta["audio_codec"]
assert nframes == 9
assert audio_codec == "aac"
def write(self, frame: np.ndarray):
assert len(frame.shape) == 3
assert frame.shape[2] == 3
assert frame.dtype == np.uint8
frame_size = (frame.shape[1], frame.shape[0])
if self.out is None:
self.path.parent.mkdir(exist_ok=True, parents=True)
self.frame_size = frame_size
self.out = imageio_ffmpeg.write_frames(
str(self.path),
self.frame_size,
fps=self.fps,
codec=self.codec,
macro_block_size=1,
ffmpeg_log_level='error',
)
self.out.send(None)
else:
assert self.frame_size == frame_size, f"Wrong frame size: should be {self.frame_size}, got {frame_size}"
if self.bgr2rgb:
frame = frame[:, :, (2, 1, 0)]
self.out.send(np.ascontiguousarray(frame))
def write_video_to_stream(path_to_video, rtp_port):
video_reader = imageio.get_reader(path_to_video)
print(video_reader.get_meta_data())
rtp_url = f"rtp://localhost:{rtp_port}"
output_params = ['-f', 'rtp_mpegts']
input_params = ['-re']
img_writer = imageio_ffmpeg.write_frames(
rtp_url,
size=video_reader.get_meta_data()['size'],
output_params=output_params,
input_params=input_params,
fps=24,
codec='mpeg4',
bitrate='1024K')
img_writer.send(None)
for frame in video_reader:
try:
img_writer.send(frame)
except KeyboardInterrupt as e:
img_writer.close()
break
img_writer.close()
def write_video_to_stream(path_to_video, rtp_port):
video_reader = imageio.get_reader(path_to_video)
print(video_reader.get_meta_data())
rtp_url = f"http://localhost:{rtp_port}"
output_params = [ '-f', 'webm', '-listen', "1", '-seekable', '0',
'-headers', 'Access-Control-Allow-Origin: http://localhost:3000\r\n']
input_params = ['-re']
img_writer = imageio_ffmpeg.write_frames(
rtp_url,
size=video_reader.get_meta_data()['size'],
output_params=output_params,
input_params=input_params,
codec='vp9',
)
img_writer.send(None)
for frame in video_reader:
#try:
img_writer.send(frame)
#except KeyboardInterrupt as e:
# print(e)
# img_writer.close()
# break
img_writer.close()
break
cap.release()
writer.close()
# Doing some Object Detection on a video
classes = None
with open(args.classes, 'r') as f:
classes = [line.strip() for line in f.readlines()]
COLORS = np.random.uniform(0, 255, size=(len(classes), 3))
if args.input.startswith('rtsp'):
cap = cv2.VideoCapture(args.input)
if int(args.framelimit) > 0:
writer = imageio.write_frames(args.outputfile, (int(cap.get(3)), int(cap.get(4))))
writer.send(None)
frame_counter = 0
while(True):
if int(args.framelimit) > 0 and frame_counter > int(args.framestart) + int(args.framelimit):
writer.close()
break
if frame_counter % int(args.fpsthrottle) ==0:
ret, frame = cap.read()
if ret and frame_counter >= int(args.framestart):
print('Detecting objects in frame ' + str(frame_counter))
frame = detect(frame)
if int(args.framelimit) > 0:
writer.send(frame)
else:
def style_video(video_path,
style,
output_name=None,
alpha=1.0,
preserve_color=False,
custom_resolution=None):
toTensor = ToTensor()
reader = imageio.get_reader(video_path)
resolution = None
if custom_resolution is None:
resolution = reader.get_meta_data()["source_size"]
else:
resolution = custom_resolution
fps = reader.get_meta_data()["fps"]
style = transform.resize(style, resolution)
if not preserve_color:
style_tensor = torch.tensor(np.expand_dims(toTensor(style),
0)).float().to(device)
style_tensor = net.encode(style_tensor)
frame_number = 0
driving_video = []
for frame_number in tqdm(range(reader.get_meta_data()['nframes'])):
try:
content = reader.get_next_data()
except imageio.core.CannotReadFrameError:
break
except IndexError:
break
else:
if custom_resolution is not None:
content = transform.resize(content, list(resolution)[::-1])
else:
content = content.astype(float) / 255
if preserve_color:
style_tensor = preserve_color_stable(content, style)
style_tensor = torch.tensor(
np.expand_dims(toTensor(style_tensor),
0)).float().to(device)
style_tensor = net.encode(style_tensor)
x = torch.tensor(toTensor(content)).unsqueeze(0).float().to(device)
x = net.encode(x)
result = adaIN(x, style_tensor)
result = (1 - alpha) * x + alpha * result
result = test(content, result, alpha, False, False)
result = cv2.convertScaleAbs(result * 255)
driving_video.append(result)
reader.close()
if output_name == None:
return driving_video
writer = imageio_ffmpeg.write_frames(f'{output_name}.mp4', (resolution),
fps=fps,
macro_block_size=1)
writer.send(None) # seed the generator
for frame in driving_video:
writer.send(frame)
writer.close()
prediction = model(in_data)
torch.cuda.synchronize()
end = time.time()
times.append(end - start)
# store video frame(s)
x = in_data[:, data.N_FRAMES, 0:3, :, :] if 'reproj' in args.type else in_data[:, 0:3, :, :]
p = prediction[:, 0:3, :, :]
y = target[:, 0:3, :, :]
# postprocess
frame = (torch.sqrt(torch.clamp(torch.cat((x, p, y), dim=-1), 0, 1)) * 255).to(torch.uint8)
frame = frame.transpose_(-3, -1).transpose_(-3, -2)
video[args.batch_size*idx:args.batch_size*idx+p.size(0)] = frame.cpu().numpy()
# write images to disk?
if args.images:
img = torch.cat((x, p, y), dim=-1) if args.cmp else p
data.write([f'{name}/{name}_{args.batch_size*idx+j:06}.{args.format}' for j in range(frame.size(0))], img.cpu().numpy())
tq.update(args.batch_size)
tq.close()
print(f'avg inference time (in s):', np.array(times).mean(), 'std:', np.array(times).std())
# write video
ffmpeg = imageio_ffmpeg.write_frames(f'{name}/{name}.mp4', (3*sample.shape[-1], sample.shape[-2]), fps=args.fps, quality=5)
ffmpeg.send(None) # seed
ffmpeg.send(video)
ffmpeg.close()
print(f'{name}/{name}.mp4 written.')
# make sure images were written
data.pool.close()
data.pool.join()
# %% Write a series of large frames
# In earlier versions of imageio-ffmpeg, the ffmpeg process was given a timeout
# to complete, but this timeout must be longer for longer movies. The default
# is now to wait for ffmpeg.
import os
import numpy as np
import imageio_ffmpeg
ims = [
np.random.uniform(0, 255, size=(1000, 1000, 3)).astype(np.uint8) for i in range(10)
]
filename = os.path.expanduser("~/Desktop/foo.mp4")
w = imageio_ffmpeg.write_frames(filename, (1000, 1000), ffmpeg_timeout=0)
w.send(None)
for i in range(200):
w.send(ims[i % 10])
print(i)
w.close()
# %% Behavior of KeyboardInterrupt / Ctrl+C
import os
import imageio_ffmpeg
filename = os.path.expanduser("~/.imageio/images/cockatoo.mp4")
reader = imageio_ffmpeg.read_frames(filename)
def OpenWriter(cam_params):
n_cam = cam_params["n_cam"]
folder_name = os.path.join(cam_params["videoFolder"],
cam_params["cameraName"])
if cam_params["cameraMake"] == "emu":
cam_params["videoFilename"] = "emu" + cam_params["videoFilename"]
full_file_name = os.path.join(folder_name, cam_params["videoFilename"])
if not os.path.isdir(folder_name):
os.makedirs(folder_name)
print('Made directory {}.'.format(folder_name))
# Load defaults
pix_fmt_out = cam_params["pixelFormatOutput"]
codec = cam_params["codec"]
gpu_params = []
# CPU compression
if cam_params["gpuID"] == -1:
print('Opened: {} using CPU to compress the stream.'.format(
full_file_name))
if pix_fmt_out == 'rgb0':
pix_fmt_out = 'yuv420p'
if cam_params["codec"] == 'h264':
codec = 'libx264'
elif cam_params["codec"] == 'h265':
codec = 'libx265'
gpu_params = [
'-r:v',
str(cam_params["frameRate"]),
'-preset',
'fast',
'-tune',
'fastdecode',
'-crf',
cam_params["quality"],
'-bufsize',
'20M',
'-maxrate',
'10M',
'-bf:v',
'4',
'-vsync',
'0',
]
# GPU compression
else:
print('Opened: {} using GPU {} to compress the stream.'.format(
full_file_name, cam_params["gpuID"]))
if cam_params["gpuMake"] == 'nvidia':
if cam_params["codec"] == 'h264':
codec = 'h264_nvenc'
elif cam_params["codec"] == 'h265':
codec = 'hevc_nvenc'
gpu_params = [
'-r:v',
str(cam_params["frameRate"]
), # important to play nice with vsync '0'
'-preset',
'fast', # set to 'fast', 'llhp', or 'llhq' for h264 or hevc
'-qp',
cam_params["quality"],
'-bf:v',
'0',
'-vsync',
'0',
'-2pass',
'0',
'-gpu',
str(cam_params["gpuID"]),
]
elif cam_params["gpuMake"] == 'amd':
if pix_fmt_out == 'rgb0':
pix_fmt_out = 'yuv420p'
if cam_params["codec"] == 'h264':
codec = 'h264_amf'
elif cam_params["codec"] == 'h265':
codec = 'hevc_amf'
gpu_params = [
'-r:v',
str(cam_params["frameRate"]),
'-usage',
'lowlatency',
'-rc',
'cqp', # constant quantization parameter
'-qp_i',
cam_params["quality"],
'-qp_p',
cam_params["quality"],
'-qp_b',
cam_params["quality"],
'-bf:v',
'0',
'-hwaccel',
'auto',
'-hwaccel_device',
str(cam_params["gpuID"]),
]
elif cam_params["gpuMake"] == 'intel':
if pix_fmt_out == 'rgb0':
pix_fmt_out = 'nv12'
if cam_params["codec"] == 'h264':
codec = 'h264_qsv'
elif cam_params["codec"] == 'h265':
codec = 'hevc_qsv'
gpu_params = [
'-r:v',
str(cam_params["frameRate"]),
'-bf:v',
'0',
]
# Initialize writer object (imageio-ffmpeg)
while (True):
try:
try:
writer = write_frames(
full_file_name,
[cam_params["frameWidth"], cam_params["frameHeight"]
], # size [W,H]
fps=cam_params["frameRate"],
quality=None,
codec=codec,
pix_fmt_in=cam_params[
"pixelFormatInput"], # 'bayer_bggr8', 'gray', 'rgb24', 'bgr0', 'yuv420p'
pix_fmt_out=pix_fmt_out,
bitrate=None,
ffmpeg_log_level=cam_params[
"ffmpegLogLevel"], # 'warning', 'quiet', 'info'
input_params=['-an'], # '-an' no audio
output_params=gpu_params,
)
writer.send(None) # Initialize the generator
break
except Exception as e:
logging.error('Caught exception: {}'.format(e))
time.sleep(0.1)
except KeyboardInterrupt:
break
return writer
def make_movie(simulation,
dynstate,
name: str,
pfilm=5,
fps=24,
callback=None):
"""
Makes a .mp4 movie of simulation from the history saved in dynstate.
Parameters
----------
simulation : Simulation
The simulation object
dynstate : DynState
The dynState object containing the position history file.
name : str
The path (and name) of the file to be writen.
pfilm : int
To make the movie, takes every pfilm position.
fps : int
The number of frame per seconds of the film.
callback : function
An optional callback function that is called every time a
frame is made and is passed the current iteration number.
Returns
-------
"""
# ouverture pour la lecture
npas = simulation.current_iter
YlimB = simulation.model.y_lim_inf
YlimH = simulation.model.y_lim_sup
XlimG = simulation.model.x_lim_inf
XlimD = simulation.model.x_lim_sup
if not name.endswith(".mp4"):
name += ".mp4"
with dynstate.open(dynstate.POS_H, 'r') as fix:
# liste de k ou tracer le graph
klist = set(range(0, npas, pfilm))
# boucle pour creer le film
figure_size = (1920, 1088)
try:
os.remove(name)
except FileNotFoundError:
pass
gen = write_frames(name, figure_size, fps=fps, quality=9)
gen.send(None)
fig = plt.figure(figsize=(figure_size[0] / (72 * 2),
figure_size[1] / (72 * 2)))
plt.clf()
# definition du domaine de dessin
plt.ioff() # pour ne pas afficher les graphs)
plt.axis('scaled')
plt.ylim(YlimB, YlimH)
plt.xlim(XlimG, XlimD)
pos = fix.load()
line1, = plt.plot(*pos[:simulation.model.n_a, :].T,
'ro',
markersize=0.5)
line2, = plt.plot(*pos[simulation.model.n_a:, :].T,
'bo',
markersize=0.5)
plt.xlabel("0")
temp = io.BytesIO()
for k in range(1, npas):
# dessin a chaque pas (ne s'ouvre pas: est sauvegarde de maniere incrementale)
if k in klist:
temp.seek(0)
plt.xlabel("Iteration : {}".format(k))
plt.title(f"T = {simulation.state_fct['T'][k]:.2f} K")
line1.set_data(*pos[:simulation.model.n_a, :].T)
line2.set_data(*pos[simulation.model.n_a:, :].T)
fig.savefig(temp, format='raw',
dpi=72 * 2) # sauvegarde incrementale
temp.seek(0)
if callback: callback(k)
gen.send(
Image.frombytes('RGBA', figure_size,
temp.read()).convert('RGB').tobytes())
pos = fix.load() # on charge a chaque pas de temps
gen.close()
plt.close(fig)
def main():
home = '/Users/Max/'
filename = home + '/Documents/videos/daily_dose1.mp4'
out_filename = home + '/Documents/videos/daily_dose1_edited.mp4'
reader = get_reader(filename)
meta = reader.get_meta_data()
writer = write_frames(out_filename, meta['size'], fps=meta['fps'])
writer.send(None)
start_offset = 4170
looper = Looper(meta)
looper.set_video(reader)
looper.set_offset(start_offset)
looper.set_loop_length(500)
looper.set_frame_interval(5)
looper1 = Looper(meta)
looper1.set_video(reader)
looper1.set_offset(start_offset - 1000)
looper1.set_loop_length(500)
looper1.set_frame_interval(5)
reducer = BitReducer(meta)
sharpen = Sharpener(meta)
delay = VideoDelay(meta)
net = ModuleNet()
net.add_module(looper)
# net.add_module(looper1)
net.add_module(sharpen, input_names=(['Looper0'], [], []))
net.add_module(reducer,
input_names=(['Sharpener0'], [], []),
output_names=(['OUT'], [], []))
# net.add_module(reducer, input_names=(['Looper0'], [], []), output_names=(['OUT'], [], []))
# net.add_module(delay, input_names=(['Looper0'], [], []), output_names=(['OUT'], [], []))
# net.add_connection('Looper1', 'VideoDelay0', 'video')
net.nodes['BitReducer0'].module.set_num_bits(4)
# net.nodes['Sharpener0'].module.set_strength(7)
# net.nodes['VideoDelay0'].module.disable()
sharpen_max_strength = 20
sharpen_min_strength = 10
sharpen_delta = (sharpen_max_strength - sharpen_min_strength) / 2
angular_period = 2 * np.pi / 30
instrument = Instrument()
instrument.net = net
total_frames = 300
start_time = timer()
for i in range(total_frames):
net.nodes['Sharpener0'].module.set_strength(sharpen_min_strength +
sharpen_delta +
sharpen_delta *
np.sin(angular_period * i))
#
# net.nodes['Looper0'].tick()
# net.nodes['Sharpener0'].tick()
# net.nodes['BitReducer0'].tick()
# instrument.reset_flags()
# print(net.nodes['Looper0'].module.current_frame)
# if i == 100:
# net.nodes['VideoDelay0'].module.disable()
# print(i)
video_frame = instrument.tick()
# frame = net.nodes['BitReducer0'].module.video_output_buffer
writer.send(video_frame)
# # print(looper.current_frame)
end_time = timer()
reader.close()
writer.close()
print(
f"Time taken to run {total_frames} frames: {end_time - start_time}s.")
def style_video(video_path,
style,
output_name=None,
alpha=1.0,
preserve_color=False,
custom_resolution=None,
frame_skip=1):
toTensor = ToTensor()
reader = imageio.get_reader(video_path)
resolution = None
if custom_resolution is None:
resolution = reader.get_meta_data()["source_size"]
else:
resolution = custom_resolution
fps = reader.get_meta_data()["fps"] / frame_skip
style = transform.resize(style, (resolution[1], resolution[0]))
if not preserve_color:
style_tensor = torch.tensor(np.expand_dims(toTensor(style),
0)).float().to(device)
style_tensor = net.encode(style_tensor)
driving_video = []
for frame_number in tqdm(range(reader.count_frames())):
try:
content = reader.get_next_data()
except IndexError:
break
else:
if frame_number % frame_skip == 0:
if custom_resolution is not None:
content = transform.resize(content,
(resolution[1], resolution[0]))
else:
content = content.astype(float) / 255
if preserve_color:
style_tensor = preserve_color_stable(content, style)
style_tensor = torch.tensor(
np.expand_dims(toTensor(style_tensor),
0)).float().to(device)
style_tensor = net.encode(style_tensor)
x = torch.tensor(
toTensor(content)).unsqueeze(0).float().to(device)
x = net.encode(x)
result = adaIN(x, style_tensor)
result = (1 - alpha) * x + alpha * result
result = test(content, result, alpha, False, False)
result = cv2.convertScaleAbs(result * 255)
driving_video.append(result)
reader.close()
if output_name == None:
return driving_video
writer = imageio_ffmpeg.write_frames(f'{output_name}_plain.mp4',
(resolution),
fps=fps,
macro_block_size=1)
writer.send(None)
for frame in driving_video:
writer.send(frame)
writer.close()
os.system(
f'ffmpeg -y -i "{video_path}" -vn -acodec copy "output_audio.aac"')
os.system(
f'ffmpeg -y -i "{output_name}_plain.mp4" -i "output_audio.aac" -c:v copy -c:a aac "{output_name}.mp4"'
)
if os.path.isfile("output_audio.aac"):
os.remove("output_audio.aac")
if not os.path.isfile(f"{output_name}.mp4"):
os.rename(f"{output_name}_plain.mp4", f"{output_name}.mp4")
else:
os.remove(f'{output_name}_plain.mp4')
