def __init__(self, inchannels):
super(FiveStr, self).__init__()
self.five_str = nn.ModuleList([
Conv_BN_Act(inchannels,
inchannels // 2,
kernel_size=1,
stride=1,
activation='leaky'),
Conv_BN_Act(inchannels // 2,
inchannels,
kernel_size=3,
stride=1,
activation='leaky'),
Conv_BN_Act(inchannels,
inchannels // 2,
kernel_size=1,
stride=1,
activation='leaky'),
Conv_BN_Act(inchannels // 2,
inchannels,
kernel_size=3,
stride=1,
activation='leaky'),
Conv_BN_Act(inchannels,
inchannels // 2,
kernel_size=1,
stride=1,
activation='leaky')
])
def __init__(self, in_channels, per_anchors, outs):
super(OUTPUT, self).__init__()
self.conv1 = Conv_BN_Act(in_channels, in_channels * 2, 3, 1, 'leaky')
self.conv2 = nn.Conv2d(in_channels * 2,
per_anchors * outs,
kernel_size=1,
stride=1)
def __init__(self, in_channels=512):
super(PANUP2, self).__init__()
self.conv1 = Conv_BN_Act(in_channels, in_channels // 2, 1, 1, 'leaky')
self.five_s = FiveStr(in_channels)
self.upsample = UPSAMPLE(in_channels // 2)
def __init__(self, in_channels=1024):
super(PANUP1, self).__init__()
self.conv1 = Conv_BN_Act(in_channels, in_channels // 2, 1, 1, 'leaky')
self.conv2 = Conv_BN_Act(in_channels // 2, in_channels, 3, 1, 'leaky')
self.spp = SPP(in_channels)
self.conv3 = Conv_BN_Act(in_channels * 2, in_channels // 2, 1, 1,
'leaky')
self.conv4 = Conv_BN_Act(in_channels // 2, in_channels, 3, 1, 'leaky')
self.conv5 = Conv_BN_Act(in_channels, in_channels // 2, 1, 1, 'leaky')
self.upsample = UPSAMPLE(in_channels // 2)
def __init__(self, in_channels):
super(DOWNSAMPLE, self).__init__()
self.down = Conv_BN_Act(in_channels,
in_channels * 2,
kernel_size=3,
stride=2,
activation='leaky')
def __init__(self, in_channels):
super(UPSAMPLE, self).__init__()
self.conv1 = Conv_BN_Act(in_channels,
in_channels // 2,
kernel_size=1,
stride=1,
activation='leaky')
def __init__(self, in_channels):
super(SPP, self).__init__()
self.spp_head = Conv_BN_Act(in_channels,
in_channels // 2,
kernel_size=1,
stride=1,
activation='leaky')
# #SPP层
self.spp_body1 = nn.MaxPool2d(kernel_size=13,
stride=1,
padding=13 // 2)
self.spp_body2 = nn.MaxPool2d(kernel_size=9, stride=1, padding=9 // 2)
self.spp_body3 = nn.MaxPool2d(kernel_size=5, stride=1, padding=5 // 2)
def __init__(self, anchors, num_bbparas, num_classes, freeze=False):
super(YOLOBODY, self).__init__()
self.darknet53 = Darknet53(freeze=freeze)
self.panup1 = PANUP1()
self.five_d32 = FiveStr(inchannels=1024)
self.outs1 = OUTPUT(in_channels=512,
per_anchors=anchors // 3,
outs=num_bbparas + 1 + num_classes)
self.panup2 = PANUP2()
self.pandown2 = PANDOWN2()
self.convd16 = Conv_BN_Act(512, 256, 1, 1, 'leaky')
self.outs2 = OUTPUT(in_channels=256,
per_anchors=anchors // 3,
outs=num_bbparas + 1 + num_classes)
self.pandown1 = PANDOWN1()
self.outs3 = OUTPUT(in_channels=128,
per_anchors=anchors // 3,
outs=num_bbparas + 1 + num_classes)
def __init__(self, in_channels=256):
super(PANDOWN1, self).__init__()
self.conv1 = Conv_BN_Act(in_channels, in_channels // 2, 1, 1, 'leaky')
self.conv2 = FiveStr(in_channels)
self.down1 = DOWNSAMPLE(in_channels=128)