def get_crop(e, center_location, window_size, freqs=[18, 38, 120, 200]):
"""
Returns a crop of data around the pixels specified in the center_location.
"""
# Get grid sampled around center_location
grid = getGrid(window_size) + np.expand_dims(
np.expand_dims(center_location, 1), 1)
channels = []
for f in freqs:
# Interpolate data onto grid
memmap = e.data_memmaps(f)[0]
data = linear_interpolation(memmap,
grid,
boundary_val=0,
out_shape=window_size)
del memmap
# Set non-finite values (nan, positive inf, negative inf) to zero
if np.any(np.invert(np.isfinite(data))):
data[np.invert(np.isfinite(data))] = 0
channels.append(np.expand_dims(data, 0))
channels = np.concatenate(channels, 0)
labels = nearest_interpolation(e.label_memmap(),
grid,
boundary_val=-100,
out_shape=window_size)
return channels, labels
def get_sample(self):
"""
:return: [(int) y-coordinate, (int) x-coordinate], (Echogram) selected echogram
"""
#Random echogram
ei = np.random.randint(len(self.echograms))
#Random x-loc with y-location of seabed
x = np.random.randint(
self.window_size[1] // 2,
self.echograms[ei].shape[1] - (self.window_size[1] // 2))
y = self.echograms[ei].get_seabed()[x]
#Check if there is any fish-labels in crop
grid = getGrid(self.window_size) + np.expand_dims(
np.expand_dims([y, x], 1), 1)
labels = nearest_interpolation(self.echograms[ei].label_memmap(),
grid,
boundary_val=0,
out_shape=self.window_size)
if np.any(labels != 0):
return self.get_sample() #Draw new sample
return [y, x], self.echograms[ei]
def get_full(echogram, freqs):
channels = []
shape = echogram.shape
grid = getGrid(shape)
for f in freqs:
# Interpolate data onto grid
memmap = echogram.data_memmaps(f)[0]
data = linear_interpolation(memmap, grid, boundary_val=0, out_shape=shape)
# Set non-finite values (nan, positive inf, negative inf) to zero
if np.any(np.invert(np.isfinite(data))):
data[np.invert(np.isfinite(data))] = 0
channels.append(np.expand_dims(data, 0))
channels = np.concatenate(channels, 0)
labels = nearest_interpolation(echogram.label_memmap(), grid, boundary_val=-100, out_shape=shape)
return channels, labels