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def test_tile_overlap(n_depth, kern_size, pool_size):
K.clear_session()
img_size = 1280 if pool_size > 1 else 160
rf_x, rf_y = receptive_field_unet(n_depth,kern_size,pool_size,n_dim=2,img_size=img_size)
assert rf_x == rf_y
rf = rf_x
assert np.abs(rf[0]-rf[1]) < 10
assert sum(rf)+1 < img_size
assert max(rf) == tile_overlap(n_depth,kern_size,pool_size)
# print("receptive field of n_depth %d and kernel size %d: %s"%(n_depth,kern_size,rf));
def _axes_tile_overlap(self, query_axes):
query_axes = axes_check_and_normalize(query_axes)
overlap = tile_overlap(self.config.unet_n_depth, self.config.unet_kern_size)
return tuple((overlap if a in 'XYZT' else 0) for a in query_axes)
mean_val1 = []
for ele in self.config.means:
mean_val.append(float(ele))
mean_val1.append(float(ele))
std_val = []
std_val1 = []
for ele in self.config.stds:
std_val.append(float(ele))
std_val1.append(float(ele))
in_data_range_val = ['-inf', 'inf']
out_data_range_val = ['-inf', 'inf']
axes_val = 'b' + self.config.axes
axes_val = axes_val.lower()
val = 2**self.config.unet_n_depth
val1 = predict.tile_overlap(self.config.unet_n_depth, self.config.unet_kern_size)
min_val = [1, val, val, self.config.n_channel_in ]
step_val = [1, val, val, 0]
halo_val = [0, val1, val1, 0]
scale_val = [1, 1, 1, 1]
offset_val = [0, 0, 0, 0]
yaml = YAML(typ='rt')
with open(self.logdir/'config.json','r') as f:
tr_kwargs_val = yaml.load(f)
if (self.config.n_dim == 3):
min_val = [1, val, val, val, self.config.n_channel_in ]
step_val = [1, val, val, val, 0]
halo_val = [0, val1, val1, val1, 0]
scale_val = [1, 1, 1, 1, 1]
offset_val = [0, 0, 0, 0, 0]
def _axes_tile_overlap(self, query_axes):
query_axes = axes_check_and_normalize(query_axes)
proj = self.proj_params
unet_overlap = tile_overlap(self.config.unet_n_depth, self.config.unet_kern_size)
overlap = {
a : max(tile_overlap(proj.n_depth, a_proj_kern, a_proj_pool), unet_overlap) # approx
for a,a_proj_pool,a_proj_kern in zip(self.config.axes.replace('C',''),proj.pool,proj.kern)
if a != proj.axis
}
return tuple(overlap.get(a,0) for a in query_axes)
def _axes_tile_overlap(self, query_axes):
query_axes = axes_check_and_normalize(query_axes)
proj = self.proj_params
unet_overlap = tile_overlap(self.config.unet_n_depth, self.config.unet_kern_size)
overlap = {
a : max(tile_overlap(proj.n_depth, a_proj_kern, a_proj_pool), unet_overlap) # approx
for a,a_proj_pool,a_proj_kern in zip(self.config.axes.replace('C',''),proj.pool,proj.kern)
if a != proj.axis
}
return tuple(overlap.get(a,0) for a in query_axes)