# apply dust particles
if APPLY_DUST:
dust1 = plt.imread(DUST1_PATH)[0:SHAPE[0], 0:SHAPE[1],
0] #float normalized to (0,1)
dust2 = plt.imread(DUST2_PATH)[0:SHAPE[0], 0:SHAPE[1],
0] #float normalized to (0,1)
dust = ((dust1, dust2), ) * NFRAMES_DUAL
video = multiply(video, dust, dtype="uint16")
noise_model = (NOISE_MODEL, NOISE_MODEL)
video = (tuple((adc(f,
noise_model=noise_model[i],
saturation=SATURATION,
readout_noise=READOUT_NOISE,
bit_depth=BIT_DEPTH) for i, f in enumerate(frames)))
for frames in video)
#video = load(video, NFRAMES_DUAL)
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
if SAVEFIG:
video = load(video, NFRAMES_DUAL) # loads and displays progress bar
import matplotlib.pyplot as plt
plt.figure(figsize=(8, 3))
plt.subplot(121)
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()