data_tags = OrderedDict(
target=arr((n_frames, ), "int32"),
video=arr((n_frames, ) + im_shp + (n_channels, ), "float32"),
)
if n_channels == 1:
data_tags["video"] = arr((n_frames, ) + im_shp, "float32")
data_loader = Loader(preprocessors=[
LabelsCon(),
VideoLoadPrep(n_frames=n_frames,
rand_middle_frame=False,
rgb=n_channels > 1),
Augment3D(output_shape=(n_frames, ) + im_shp,
output_scale=(1, 1, 1),
mode="nearest",
interp_order=0,
augm_params={
"translation": [0, 4, 4],
"rotation": [2, 0, 0],
"shear": [0, 0, 0],
"scale": [1, 1.1, 1.1],
}),
ClassPerFrame(n_frames=n_frames),
],
inputs=data_tags)
# TRAINING
############
learning_rate = 3e-5 * batch_size
learning_rate_decay = 3e-5
augm_params={
"translation": [0, 16, 16],
"rotation": [8, 0, 0],
"shear": [0, 0, 0],
"scale": [1, 1.5, 1.5],
"reflection": [0, 0, .5] # Bernoulli p
}
print "augm_params", augm_params
data_loader = Loader(
data_path=paths.CON_PREP2,
preprocessors=[
LabelsCon(),
VideoLoadPrep(n_frames=n_frames, rand_middle_frame=True, rgb=n_channels>1,
use_bcolz=True, tolerance=0, rgbbias=-127),
Augment3D(output_shape=(n_frames,)+im_shp, output_scale=(1,1,1), mode="constant", dbias=-127,
interp_order=1, augm_params=augm_params),
ClassPerFrame(n_frames=n_frames),
],
inputs = data_tags
)
# TRAINING
############
learning_rate = 3e-5 * batch_size
learning_rate_decay = 3e-5
validate_every_n_samples = 20*1024
validate_every_n_chunks = int(np.ceil(validate_every_n_samples/float(chunk_size)))
augm_params = {
"translation": [0, 16, 16],
"rotation": [4, 0, 0],
"shear": [0, 0, 0],
"scale": [1, 1.2, 1.2],
"reflection": [0, 0, .5] # Bernoulli p
}
print "augm_params", augm_params
data_loader = Loader(preprocessors=[
LabelsCon(),
VideoLoadPrep(n_frames=n_frames,
rand_middle_frame=False,
rgb=n_channels > 1,
tolerance=4),
Augment3D(output_shape=(n_frames, ) + im_shp,
output_scale=(1, 1, 1),
mode="nearest",
interp_order=0,
augm_params=augm_params),
ClassPerFrame(n_frames=n_frames),
],
inputs=data_tags)
# TRAINING
############
learning_rate = 3e-5 * batch_size
learning_rate_decay = 3e-5
validate_every_n_samples = 20 * 1024
validate_every_n_chunks = int(
