def sp_batch_map_coordinates(inputs, coords):
"""Reference implementation for batch_map_coordinates"""
coords = coords.clip(0, inputs.shape[1] - 1)
mapped_vals = np.array([
sp_map_coordinates(input, coord.T, mode='nearest', order=1)
for input, coord in zip(inputs, coords)
])
return mapped_vals
def sp_batch_map_coordinates(inputs, coords):
coords = coords.clip(0, inputs.shape[1] - 1)
mapped_vals = np.array([
sp_map_coordinates(input, coord.T, mode='nearest', order=1)
for input, coord in zip(inputs, coords)
])
return mapped_vals
def sp_batch_map_coordinates(inputs, coords):
"""Reference implementation for batch_map_coordinates"""
# coords = coords.clip(0, inputs.shape[1] - 1)
assert (coords.shape[2] == 2)
height = coords[:,:,0].clip(0, inputs.shape[1] - 1)
width = coords[:,:,1].clip(0, inputs.shape[2] - 1)
np.concatenate((np.expand_dims(height, axis=2), np.expand_dims(width, axis=2)), 2)
mapped_vals = np.array([
sp_map_coordinates(input, coord.T, mode='nearest', order=1)
for input, coord in zip(inputs, coords)
])
return mapped_vals
def sp_batch_map_coordinates(inputs, coords):
"""
仅在 h = w 的情况下生效
:param inputs:
:param coords:
:return:
"""
# 将coords里面的所有数值全部都限制在(0, h^2-1)之间
coords = coords.clip(0, inputs.shape[1] - 1)
# 使用双线性差值算法 找到合适的位置
mapped_vals = np.array([
sp_map_coordinates(input, coord.T, mode='nearest', order=1)
for input, coord in zip(inputs, coords)
])
return mapped_vals
