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if error == False:
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logging.info(msg)
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else:
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logging.error(msg)
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###############################################################################
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class POINT(object):
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def __init__(self, x, y, z=0.0):
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self.x = x
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self.y = y
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self.z = z
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###############################################################################
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class RECT(object):
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def __init__(self, p1, p2):
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'''Store the top, bottom, left and right values for points
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p1 and p2 are the (corners) in either order
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'''
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self.left = min(p1.x, p2.x)
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self.right = max(p1.x, p2.x)
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self.bottom = min(p1.y, p2.y)
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self.top = max(p1.y, p2.y)
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self.minz = min(p1.z, p2.z)
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self.maxz = max(p1.z, p2.z)
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class MEMORYSTATUSEX(ctypes.Structure):
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_fields_ = [
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("dwLength", ctypes.c_ulong),
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("dwMemoryLoad", ctypes.c_ulong),
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("ullTotalPhys", ctypes.c_ulonglong),
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("ullAvailPhys", ctypes.c_ulonglong),
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("ullTotalPageFile", ctypes.c_ulonglong),
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("ullAvailPageFile", ctypes.c_ulonglong),
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("ullTotalVirtual", ctypes.c_ulonglong),
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("ullAvailVirtual", ctypes.c_ulonglong),
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("sullAvailExtendedVirtual", ctypes.c_ulonglong),
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]
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def __init__(self):
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# have to initialize this to the size of MEMORYSTATUSEX
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self.dwLength = ctypes.sizeof(self)
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super(MEMORYSTATUSEX, self).__init__()
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###################################################################################################
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if __name__ == "__main__":
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print("lashelper.py copyright GuardianGeomatics Pty Ltd")
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# <FILESEP>
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import caffe
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import numpy as np
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class DiceLoss(caffe.Layer):
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"""
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Compute energy based on dice coefficient.
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"""
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union = None
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intersection = None
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result = None
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gt = None
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def setup(self, bottom, top):
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# check input pair
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if len(bottom) != 2:
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raise Exception("Need two inputs to compute the dice. the result of the softmax and the ground truth.")
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def reshape(self, bottom, top):
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# check input dimensions match
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if bottom[0].count != 2*bottom[1].count:
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print bottom[0].data.shape
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print bottom[1].data.shape
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raise Exception("the dimension of inputs should match")
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# loss output is two scalars (mean and std)
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top[0].reshape(1)
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def forward(self, bottom, top):
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dice = np.zeros(bottom[0].data.shape[0],dtype=np.float32)
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self.union = np.zeros(bottom[0].data.shape[0],dtype=np.float32)
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self.intersection = np.zeros(bottom[0].data.shape[0],dtype=np.float32)
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self.result = np.reshape(np.squeeze(np.argmax(bottom[0].data[...],axis=1)),[bottom[0].data.shape[0],bottom[0].data.shape[2]])
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self.gt = np.reshape(np.squeeze(bottom[1].data[...]),[bottom[1].data.shape[0],bottom[1].data.shape[2]])
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self.gt = (self.gt > 0.5).astype(dtype=np.float32)
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self.result = self.result.astype(dtype=np.float32)
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for i in range(0,bottom[0].data.shape[0]):
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# compute dice
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CurrResult = (self.result[i,:]).astype(dtype=np.float32)
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CurrGT = (self.gt[i,:]).astype(dtype=np.float32)
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self.union[i]=(np.sum(CurrResult) + np.sum(CurrGT))
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self.intersection[i]=(np.sum(CurrResult * CurrGT))
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dice[i] = 2 * self.intersection[i] / (self.union[i]+0.00001)
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print dice[i]
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