def init_network(self):
self.layer1 = Pointnet_SA(npoint=512,
radius=0.2,
nsample=32,
mlp=[64, 64, 128],
group_all=False,
activation=self.activation,
bn=self.bn)
self.layer2 = Pointnet_SA(npoint=128,
radius=0.4,
nsample=64,
mlp=[128, 128, 256],
group_all=False,
activation=self.activation,
bn=self.bn)
self.layer3 = Pointnet_SA(npoint=None,
radius=None,
nsample=None,
mlp=[256, 512, 1024],
group_all=True,
activation=self.activation,
bn=self.bn)
self.dense1 = Dense(512, activation=self.activation)
self.dropout1 = Dropout(self.keep_prob)
self.dense2 = Dense(128, activation=self.activation)
self.dropout2 = Dropout(self.keep_prob)
self.dense3 = Dense(self.num_classes, activation=tf.nn.softmax)
def init_network(self):
self.sa_1 = Pointnet_SA(npoint=128,
radius=0.2,
nsample=32,
mlp=[64, 64, 128],
group_all=False,
activation=self.activation,
bn=self.bn)
self.sa_2 = Pointnet_SA(npoint=64,
radius=0.4,
nsample=32,
mlp=[256, 256, 512],
group_all=False,
activation=self.activation,
bn=self.bn)
self.fp_1 = Pointnet_FP(mlp=[256, 64],
activation=self.activation,
bn=self.bn)
self.fp_2 = Pointnet_FP(mlp=[64, 64, 64],
activation=self.activation,
bn=self.bn)
self.dense1 = Dense(128, activation=self.activation)
self.dropout1 = Dropout(self.keep_prob)
self.dense2 = Dense(self.num_classes, activation=tf.nn.softmax)
def init_network(self):
self.sa_1 = Pointnet_SA(npoint=288,
radius=0.2,
nsample=8,
mlp=[32, 32, 64],
group_all=False,
activation=self.activation,
bn=self.bn)
self.sa_2 = Pointnet_SA(npoint=14,
radius=0.4,
nsample=4,
mlp=[64, 64, 128],
group_all=False,
activation=self.activation,
bn=self.bn)
self.fp_3 = Pointnet_FP(mlp=[256, 128],
activation=self.activation,
bn=self.bn)
self.fp_4 = Pointnet_FP(mlp=[128, 128, 128],
activation=self.activation,
bn=self.bn)
self.dense1 = Dense(128, activation=self.activation)
self.dropout1 = Dropout(self.keep_prob)
self.dense2 = Dense(self.num_classes, activation=None)
def init_network(self):
self.layer1 = Pointnet_SA_MSG(npoint=1024,
radius_list=[0.1, 0.2, 0.4],
nsample_list=[16, 32, 128],
mlp=[[32, 32, 64], [64, 64, 128],
[64, 96, 128]],
activation=self.activation,
bn=self.bn)
self.layer2 = Pointnet_SA_MSG(npoint=512,
radius_list=[0.2, 0.4, 0.8],
nsample_list=[32, 64, 128],
mlp=[[64, 64, 128], [128, 128, 256],
[128, 128, 256]],
activation=self.activation,
bn=self.bn)
self.layer3 = Pointnet_SA(npoint=None,
radius=None,
nsample=None,
mlp=[256, 512, 1024],
group_all=True,
activation=self.activation,
bn=self.bn)
self.dense1 = Dense(512, activation=self.activation)
self.dropout1 = Dropout(self.keep_prob)
self.dense2 = Dense(128, activation=self.activation)
self.dropout2 = Dropout(self.keep_prob)
self.dense3 = Dense(self.num_classes, activation=tf.nn.softmax)