def __call__(self, *inputs):
if not isinstance(self.interp, (tuple, list)):
interp = [self.interp] * len(inputs)
else:
interp = self.interp
outputs = []
for idx, _input in enumerate(inputs):
input_tf = th_affine2d(_input, self.tform_matrix, mode=interp[idx])
outputs.append(input_tf)
return outputs if idx > 1 else outputs[0]
def __call__(self, *inputs):
# collect all of the lazily returned tform matrices
tform_matrix = self.transforms[0](inputs[0])
for tform in self.transforms[1:]:
tform_matrix = tform_matrix.mm(tform(inputs[0]))
if not isinstance(self.interp, (tuple, list)):
interp = [self.interp] * len(inputs)
else:
interp = self.interp
outputs = []
for idx, _input in enumerate(inputs):
input_tf = th_affine2d(_input, tform_matrix, mode=interp[idx])
outputs.append(input_tf)
return outputs if idx > 1 else outputs[0]
def __call__(self, *inputs):
if not isinstance(self.interp, (tuple, list)):
interp = [self.interp] * len(inputs)
else:
interp = self.interp
zx, zy = self.value
zoom_matrix = th.FloatTensor([[zx, 0, 0], [0, zy, 0], [0, 0, 1]])
if self.lazy:
return zoom_matrix
else:
outputs = []
for idx, _input in enumerate(inputs):
input_tf = th_affine2d(_input,
zoom_matrix,
mode=interp[idx],
center=True)
outputs.append(input_tf)
return outputs if idx > 1 else outputs[0]
def __call__(self, *inputs):
if not isinstance(self.interp, (tuple, list)):
interp = [self.interp] * len(inputs)
else:
interp = self.interp
theta = (math.pi * self.value) / 180
shear_matrix = th.FloatTensor([[1, -math.sin(theta), 0],
[0, math.cos(theta), 0], [0, 0, 1]])
if self.lazy:
return shear_matrix
else:
outputs = []
for idx, _input in enumerate(inputs):
input_tf = th_affine2d(_input,
shear_matrix,
mode=interp[idx],
center=True)
outputs.append(input_tf)
return outputs if idx > 1 else outputs[0]
def __call__(self, *inputs):
if not isinstance(self.interp, (tuple, list)):
interp = [self.interp] * len(inputs)
else:
interp = self.interp
tx = self.height_range * inputs[0].size(1)
ty = self.width_range * inputs[0].size(2)
translation_matrix = th.FloatTensor([[1, 0, tx], [0, 1, ty], [0, 0,
1]])
if self.lazy:
return translation_matrix
else:
outputs = []
for idx, _input in enumerate(inputs):
input_tf = th_affine2d(_input,
translation_matrix,
mode=interp[idx],
center=True)
outputs.append(input_tf)
return outputs if idx > 1 else outputs[0]