def testFindCameraSpacePointsFour():
v = Connections()
srcPts01 = np.array([[1, 1], [8, 8], [17, 17]])
dstPts01 = np.array([[2, 2], [9, 9], [18, 18]])
v.addConnection(0, 1, None, None, srcPts01, dstPts01)
srcPts02 = np.array([[5, 5], [19, 19]])
dstPts02 = np.array([[7, 7], [20, 20]])
v.addConnection(0, 2, None, None, srcPts02, dstPts02)
srcPts03 = np.array([[8, 8], [11, 11]])
dstPts03 = np.array([[10, 10], [13, 13]])
v.addConnection(0, 3, None, None, srcPts03, dstPts03)
srcPts12 = np.array([[2, 2], [6, 6], [14, 14], [21, 21]])
dstPts12 = np.array([[3, 3], [7, 7], [15, 15], [22, 22]])
v.addConnection(1, 2, None, None, srcPts12, dstPts12)
srcPts13 = np.array([[14, 14], [23, 23]])
dstPts13 = np.array([[16, 16], [24, 24]])
v.addConnection(1, 3, None, None, srcPts13, dstPts13)
srcPts23 = np.array([[3, 3], [12, 12], [25, 25]])
dstPts23 = np.array([[4, 4], [13, 13], [26, 26]])
v.addConnection(2, 3, None, None, srcPts23, dstPts23)
# v.debugConnections()
listOfMatches = []
discovered = [dict(), dict(), dict(), dict()]
v.findMatches(listOfMatches, discovered)
[match.debugViews() for match in listOfMatches]
def Guard(): #checks were current connections are, and if not approved locations, reports it.
global locations
ip_con = Connections.Connections('ip') #find the ip connections
ip_dom = Connections.Connections('domain') #find domain connections
ip_loc = ''
for ip in ip_con: #get locations of ip connections
ip_loc = ip_loc + Locate.Locate(ip) + '\n'
dom_loc = ''
for d in ip_dom: #get locations of domain connections
dom_loc = dom_loc + Locate.Locate(DomainLookup.Domain_to_IP(d)) + '\n'
locations = ip_loc + '\n' + dom_loc
states = Locate.FindStates(locations) #finds the states of the connections
for s in states: #check to see if in approved locaitons
if (s == 'RI' or s == 'NY'):
continue
else:
return True #if there is a problem, returns true
return False #otherwise returns false
def testFindCameraSpacePointsTwo():
v = Connections()
srcPts = np.array([[1, 1], [3, 3], [5, 5]])
dstPts = np.array([[2, 2], [4, 4], [6, 6]])
v.addConnection(0, 1, None, None, srcPts, dstPts)
v.debugConnections()
listOfMatches = []
discovered = [dict(), dict()]
v.findMatches(listOfMatches, discovered)
[match.debugViews() for match in listOfMatches]
def testFindCameraSpacePointsThree():
v = Connections()
srcPts01 = np.array([[1, 1], [4, 4]])
dstPts01 = np.array([[2, 2], [5, 5]])
v.addConnection(0, 1, None, None, srcPts01, dstPts01)
srcPts02 = np.array([[8, 8]])
dstPts02 = np.array([[9, 9]])
v.addConnection(0, 2, None, None, srcPts02, dstPts02)
srcPts12 = np.array([[2, 2], [6, 6]])
dstPts12 = np.array([[3, 3], [7, 7]])
v.addConnection(1, 2, None, None, srcPts12, dstPts12)
# v.debugConnections()
listOfMatches = []
discovered = [dict(), dict(), dict()]
v.findMatches(listOfMatches, discovered)
[match.debugViews() for match in listOfMatches]
def __init__(self, layers):
"""
初始化一个全连接神经网络
:param layers: 二维数组，描述神经网络每层节点数
"""
self.connections = Connections()
self.layers = []
layer_count = len(layers)
node_count = 0
for i in range(layer_count):
self.layers.append(Layer(i, layers[i]))
for layer in range(layer_count - 1):
connections = [
Connection(upstream_node, downstream_node)
for upstream_node in self.layers[layer].nodes
for downstream_node in self.layers[layer + 1].node[:-1]
]
for conn in connections:
self.connections.add_connection(conn)
conn.downstream_node.append_upstream_connection(conn)
conn.upstream_node.append_downstream_connection(conn)
def testAddOneConnection(R01, t01):
v = Connections()
v.addConnection(0, 1, R01, t01, None, None)
v.debugConnections()
def __init__(self):
self.complete = False
self.db = Connections.Connections()
]
# convert ppm to numpy array
images = [cv2.imread(f, cv2.IMREAD_GRAYSCALE) for f in imgFiles]
# images = images[0:2]
numImages = len(images)
# load the camera matrices
matrixFiles = [open(f) for f in cameraFiles]
matrixList = [np.zeros((3, 3)) for f in cameraFiles]
for i in range(len(matrixFiles)):
for j in range(3):
row = matrixFiles[i].readline().split()
for k in range(3):
matrixList[i][j, k] = np.float(row[k])
# instantiate viewSet object
c = Connections(len(images))
# set instrinsics
c.setIntrinsics(matrixList[0])
# fill connection table
for i in range(numImages):
for j in range(i + 1, numImages):
R, t, srcPts, dstPts = estimateRelativeExtrinsics(
images[i], images[j], i, j,
c.intrinsics) # estimate time 35.433154821395874
c.addConnection(i, j, R, t, srcPts, dstPts)
# find the matches
listOfMatches = []
discovered = [dict() for i in range(numImages)]
