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()
t2,
shape=SIMSHAPE,
background=0,
num_particles=NUM_PARTICLES2,
dt=DT_DUAL,
sigma=SIGMA2,
delta=DELTA2,
intensity=INTENSITY2,
dtype="uint16")
video = add(video1, video2)
#video = (move_pixels(frames) for frames in video)
#: crop video to selected region of interest
video = crop(video, roi=((0, SHAPE[0]), (0, SHAPE[1])))
# 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],
def main():
import argparse
import pathlib
import json
parser = argparse.ArgumentParser()
# parser.add_argument('--method', default='diff', choices=['diff', 'fft', 'corr'])
parser.add_argument('--kmax', default=None, type=int)
parser.add_argument('-p', '--position', nargs=2, default=[0, 0], type=int)
parser.add_argument('-r', '--framerate', type=str, default=None)
parser.add_argument('-f', '--select', nargs=2, type=int)
parser.add_argument('size', type=int)
parser.add_argument('vid_in') # Directly passed to PyAV which then pass on to FFmpeg
# parser.add_argument('fft_out', type=argparse.FileType('wb')) # pass to np.save
parser.add_argument('fft_out', type=pathlib.Path)
params = parser.parse_args()
# print(params)
try:
params.fft_out.mkdir(mode=0o755, parents=True, exist_ok=True)
except FileExistsError:
parser.error('fft_out must be a directory')
copt = dict()
if params.framerate:
copt['framerate'] = params.framerate
if params.select:
copt['start_number'] = str(params.select[0])
frames_iter = pyav_single_frames_reader(
params.vid_in,
container_options=copt,
frame_count=params.select[1] if params.select else None,
)
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),
))
fft_path = params.fft_out / 'fft_array'
if params.select:
frame_count = vid_info['framecount']
else:
frame_count = vid_info['duration']
fft_info = fft_save(video, str(fft_path), params.size, count=frame_count, kmax=params.kmax)
vid_info['vid_in_path'] = str(pathlib.Path(params.vid_in).resolve())
fft_info['position'] = params.position
fft_info['size'] = params.size
vid_info['fft'] = fft_info
def fraction_serializer(obj):
try:
return [obj.numerator, obj.denominator]
except AttributeError:
raise TypeError
with open(params.fft_out / 'vid_info.json', 'w') as j:
json.dump(vid_info, j, indent=4, default=fraction_serializer)
def test_crop(self):
video = fromarrays((vid, ))
with self.assertRaises(ValueError):
list(crop(video, roi=((0, 4), 0, 2)))
out, = asarrays(crop(video, roi=((0, 2), (0, 2))), 128)
self.assertTrue(np.allclose(out[:], vid[:, 0:2, 0:2]))
