def main():
import argparse
import pathlib
# import json
parser = argparse.ArgumentParser()
# parser.add_argument('--method', default='diff', choices=['diff', 'fft', 'corr'])
parser.add_argument('-p', '--position', nargs=2, default=[0, 0], type=int)
parser.add_argument('size', type=int)
parser.add_argument(
'vid_in') # Directly passed to PyAV which then pass on to FFmpeg
params = parser.parse_args()
# print(params)
frames_iter = pyav_single_frames_reader(params.vid_in)
vid_info = next(frames_iter)
# vid_info.pop('codec_context')
video = frames_iter
video = crop(video, (
(params.position[0], params.position[0] + params.size),
(params.position[1], params.position[1] + params.size),
))
vid_info['vid_in_path'] = str(pathlib.Path(params.vid_in).resolve())
print(vid_info)
viewer = VideoViewer(video, vmin=0, vmax=255, count=vid_info['duration'])
viewer.show()
plt.subplot(121)
plt.imshow(video[0][0], cmap="gray")
plt.colorbar()
plt.yticks([])
plt.xticks([])
plt.title("Camera 1")
plt.subplot(122)
plt.imshow(video[0][1], cmap="gray")
plt.colorbar()
plt.yticks([])
plt.xticks([])
plt.title("Camera 2")
plt.savefig("frames.pdf")
#: camera 1
viewer1 = VideoViewer(video,
count=NFRAMES_DUAL,
id=0,
vmin=0,
cmap="gray",
vmax=VMAX)
viewer1.show()
#: camera 2
viewer2 = VideoViewer(video,
count=NFRAMES_DUAL,
id=1,
vmin=0,
cmap="gray",
vmax=VMAX)
viewer2.show()
img = ax.imshow(ddm_array[:, :, 0], **imshow_kwargs)
fig.colorbar(img, ax=ax)
ti_indicator = fig.text(.02,
.98,
'$t_i$ = 0 frames\n$t$ = 0',
verticalalignment='top')
ax.set_xlabel(f'$q_x$ (${wavenumber_unit}$)')
ax.set_ylabel(f'$q_y$ (${wavenumber_unit}$)')
def change_img(ti):
img.set_data(ddm_array[:, :, ti])
ti_indicator.set_text(
f"$t_i$ = {ti} frames\n$\\tau$ = {ti*frame_interval:.3f} s")
return img,
animation = matplotlib.animation.FuncAnimation(fig,
change_img,
frames=params.frames,
blit=False,
interval=interval)
# plt.show()
animation.save(
params.save_html_path,
matplotlib.animation.HTMLWriter(fps=1000 / interval,
default_mode='loop'))
else:
ddm_iter = [ddm_array[:, :, i] for i in range(ddm_array.shape[2])]
viewer = VideoViewer(ddm_iter, count=params.frames, **imshow_kwargs)
viewer.pause_duration = interval / 1000
viewer.show()
intensity=INTENSITY,
dtype="uint16")
#: crop video to selected region of interest
video = crop(video, roi=((0, SHAPE[0]), (0, SHAPE[1])))
#: apply dust particles
if APPLY_DUST:
dust = plt.imread(DUST1_PATH)[0:SHAPE[0], 0:SHAPE[1],
0] #float normalized to (0,1)
dust = ((dust, ), ) * NFRAMES_FULL
video = multiply(video, dust)
video = (tuple((adc(f,
noise_model=NOISE_MODEL,
saturation=SATURATION,
readout_noise=READOUT_NOISE,
bit_depth=BIT_DEPTH) for f in frames)) for frames in video)
if __name__ == "__main__":
#: no need to load video, but this way we load video into memory, and we
#: can scroll back and forth with the viewer. Uncomment the line below.
#video = load(video, NFRAMES) # loads and displays progress bar
#: VideoViewer either expects a multi_frame iterator, or a numpy array
viewer = VideoViewer(video,
count=NFRAMES_FULL,
vmin=0,
cmap="gray",
vmax=VMAX)
viewer.show()
video = simple_brownian_video(t1,
t2,
shape=SIMSHAPE,
background=BACKGROUND,
sigma=SIGMA,
delta=DELTA,
intensity=INTENSITY)
#: crop video to selected region of interest
video = crop(video, roi=((0, SHAPE[0]), (0, SHAPE[1])))
#: apply dust particles
dust1 = plt.imread(DUST1_PATH)[..., 0] #float normalized to (0,1)
dust2 = plt.imread(DUST2_PATH)[..., 0]
dust = ((dust1, dust2), ) * NFRAMES
video = multiply(video, dust)
if __name__ == "__main__":
#: no need to load video, but this way we load video into memory, and we
#: can scroll back and forth with the viewer. Uncomment the line below
#video = load(video, NFRAMES) # loads and displays progress bar
#: camera 1
viewer1 = VideoViewer(video, count=NFRAMES, id=0, vmin=0, cmap="gray")
viewer1.show()
#: camera 2
viewer2 = VideoViewer(video, count=NFRAMES, id=1, vmin=0, cmap="gray")
viewer2.show()