def __init__(self, configer):
super(Vgg16SSD512, self).__init__()
self.configer = configer
self.backbone = vgg_backbone(configer).named_modules()
cnt = 0
self.sub_backbone_1 = nn.ModuleList()
self.sub_backbone_2 = nn.ModuleList()
for key, module in self.backbone:
if len(key.split('.')) < 2:
continue
if cnt < 23:
self.sub_backbone_1.append(module)
else:
self.sub_backbone_2.append(module)
cnt += 1
self.norm4 = L2Norm(512, 20)
self.ssd_head = SSDHead(configer)
self.ssd_detection_layer = SSDDetectionLayer(configer)
self.ssd_target_generator = SSDTargetGenerator(configer)
self.valid_loss_dict = configer.get('loss', 'loss_weights', configer.get('loss.loss_type'))
def __init__(self, configer):
super(LFFDv2, self).__init__()
self.configer = configer
# conv block 1 ---------------------------------------------------------------------------------------
self.conv1 = nn.Conv2d(3, num_filters_list[1], kernel_size=3, stride=(2, 2), padding=(0, 0))
self.relu1 = nn.ReLU()
# conv block 2 ----------------------------------------------------------------------------------------
self.conv2 = nn.Conv2d(num_filters_list[1], num_filters_list[1], kernel_size=3, stride=(2, 2), padding=(0, 0))
self.relu2 = nn.ReLU()
# conv block 3 ----------------------------------------------------------------------------------------
self.conv3 = nn.Conv2d(num_filters_list[1], num_filters_list[1], kernel_size=3, stride=(1, 1), padding=(1, 1))
self.relu3 = nn.ReLU()
# conv block 4 ----------------------------------------------------------------------------------------
self.conv4 = nn.Conv2d(num_filters_list[1], num_filters_list[1], kernel_size=3, stride=(1, 1), padding=(1, 1))
self.relu4 = nn.ReLU()
# conv block 5 ----------------------------------------------------------------------------------------
self.conv5 = nn.Conv2d(num_filters_list[1], num_filters_list[1], kernel_size=3, stride=(1, 1), padding=(1, 1))
self.relu5 = nn.ReLU()
# conv block 6 ----------------------------------------------------------------------------------------
self.conv6 = nn.Conv2d(num_filters_list[1], num_filters_list[1], kernel_size=3, stride=(1, 1), padding=(1, 1))
self.relu6 = nn.ReLU()
# conv block 7 ----------------------------------------------------------------------------------------
self.conv7 = nn.Conv2d(num_filters_list[1], num_filters_list[1], kernel_size=3, stride=(1, 1), padding=(1, 1))
self.relu7 = nn.ReLU()
# conv block 8 ----------------------------------------------------------------------------------------
self.conv8 = nn.Conv2d(num_filters_list[1], num_filters_list[1], kernel_size=3, stride=(1, 1), padding=(1, 1))
self.relu8 = nn.ReLU()
# conv block 9 ----------------------------------------------------------------------------------------
self.conv9 = nn.Conv2d(num_filters_list[1], num_filters_list[1], kernel_size=3, stride=(2, 2), padding=(0, 0))
self.relu9 = nn.ReLU()
# conv block 10 ----------------------------------------------------------------------------------------
self.conv10 = nn.Conv2d(num_filters_list[1], num_filters_list[1], kernel_size=3, stride=(1, 1), padding=(1, 1))
self.relu10 = nn.ReLU()
# conv block 11 ----------------------------------------------------------------------------------------
self.conv11 = nn.Conv2d(num_filters_list[1], num_filters_list[1], kernel_size=3, stride=(1, 1), padding=(1, 1))
self.relu11 = nn.ReLU()
# conv block 12 ----------------------------------------------------------------------------------------
self.conv12 = nn.Conv2d(num_filters_list[1], num_filters_list[1], kernel_size=3, stride=(2, 2), padding=(0, 0))
self.relu12 = nn.ReLU()
# conv block 13 ----------------------------------------------------------------------------------------
self.conv13 = nn.Conv2d(num_filters_list[1], num_filters_list[1], kernel_size=3, stride=(1, 1), padding=(1, 1))
self.relu13 = nn.ReLU()
# conv block 14 ----------------------------------------------------------------------------------------
self.conv14 = nn.Conv2d(num_filters_list[1], num_filters_list[1], kernel_size=3, stride=(1, 1), padding=(1, 1))
self.relu14 = nn.ReLU()
# conv block 15 ----------------------------------------------------------------------------------------
self.conv15 = nn.Conv2d(num_filters_list[1], num_filters_list[2], kernel_size=3, stride=(2, 2), padding=(0, 0))
self.relu15 = nn.ReLU()
# conv block 16 ----------------------------------------------------------------------------------------
self.conv16 = nn.Conv2d(num_filters_list[2], num_filters_list[2], kernel_size=3, stride=(1, 1), padding=(1, 1))
self.relu16 = nn.ReLU()
# conv block 17 ----------------------------------------------------------------------------------------
self.conv17 = nn.Conv2d(num_filters_list[2], num_filters_list[2], kernel_size=3, stride=(1, 1), padding=(1, 1))
self.relu17 = nn.ReLU()
# conv block 18 ----------------------------num_nonzero--------------------------------------------------------
self.conv18 = nn.Conv2d(num_filters_list[2], num_filters_list[2], kernel_size=3, stride=(2, 2), padding=(0, 0))
self.relu18 = nn.ReLU()
# conv block 19 ----------------------------------------------------------------------------------------
self.conv19 = nn.Conv2d(num_filters_list[2], num_filters_list[2], kernel_size=3, stride=(1, 1), padding=(1, 1))
self.relu19 = nn.ReLU()
# conv block 20 ----------------------------------------------------------------------------------------
self.conv20 = nn.Conv2d(num_filters_list[2], num_filters_list[2], kernel_size=3, stride=(1, 1), padding=(1, 1))
self.relu20 = nn.ReLU()
self.ssd_detection_layer = DetectionLayer(configer)
self.ssd_target_generator = SSDTargetGenerator(configer)
self.valid_loss_dict = configer.get('loss', 'loss_weights', configer.get('loss.loss_type'))
def __init__(self, configer):
super(MultiBoxLoss, self).__init__()
self.num_classes = configer.get('data', 'num_classes')
self.ssd_target_generator = SSDTargetGenerator(configer)