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jblitzar
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github-python

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