Python data.voc() Examples

The following are 9 code examples of data.voc(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module data , or try the search function .
Example #1
Source File: ssd.py    From SSD_resnet_pytorch with MIT License 6 votes vote down vote up 
def __init__(self, phase,model, size, base, extras, head, num_classes):
        super(SSD, self).__init__()
        self.phase = phase
        self.num_classes = num_classes
        self.cfg = (coco, voc)[num_classes == 21]
        self.priorbox = PriorBox(self.cfg)
        self.priors = Variable(self.priorbox.forward(), requires_grad=True)
        self.size = size
        self.model=model
        # SSD network
        self.base = nn.ModuleList(base)
        # Layer learns to scale the l2 normalized features from conv4_3
        self.L2Norm = L2Norm( 512, 20)
        self.extras = nn.ModuleList(extras)

        self.loc = nn.ModuleList(head[0])
        self.conf = nn.ModuleList(head[1])

        if phase == 'test':
            self.softmax = nn.Softmax(dim=-1)
            self.detect = Detect(num_classes, 0, 200, 0.01, 0.45)
Example #2
Source File: ssd.py    From repulsion_loss_ssd with MIT License 6 votes vote down vote up 
def __init__(self, phase, size, base, extras, head, num_classes):
        super(SSD, self).__init__()
        self.phase = phase
        self.num_classes = num_classes
        self.cfg = (coco, voc)[num_classes == 21]
        self.priorbox = PriorBox(self.cfg)
        self.priors = Variable(self.priorbox.forward(), volatile=True)
        self.size = size

        # SSD network
        self.vgg = nn.ModuleList(base)
        # Layer learns to scale the l2 normalized features from conv4_3
        self.L2Norm = L2Norm(512, 20)
        self.extras = nn.ModuleList(extras)

        self.loc = nn.ModuleList(head[0])
        self.conf = nn.ModuleList(head[1])

        if phase == 'test':
            self.softmax = nn.Softmax(dim=-1)
            self.detect = Detect(num_classes, 0, 200, 0.01, 0.45)
Example #3
Source File: ssd.py    From ssd.pytorch with MIT License 6 votes vote down vote up 
def __init__(self, phase, size, base, extras, head, num_classes):
        super(SSD, self).__init__()
        self.phase = phase
        self.num_classes = num_classes
        self.cfg = (coco, voc)[num_classes == 21]
        self.priorbox = PriorBox(self.cfg)
        self.priors = Variable(self.priorbox.forward(), volatile=True)
        self.size = size

        # SSD network
        self.vgg = nn.ModuleList(base)
        # Layer learns to scale the l2 normalized features from conv4_3
        self.L2Norm = L2Norm(512, 20)
        self.extras = nn.ModuleList(extras)

        self.loc = nn.ModuleList(head[0])
        self.conf = nn.ModuleList(head[1])

        if phase == 'test':
            self.softmax = nn.Softmax(dim=-1)
            self.detect = Detect(num_classes, 0, 200, 0.01, 0.45)
Example #4
Source File: detection.py    From lightDSFD with MIT License 5 votes vote down vote up 
def __init__(self, num_classes, bkg_label, top_k, conf_thresh, nms_thresh):
        self.num_classes = num_classes
        self.background_label = bkg_label
        self.top_k = top_k
        # Parameters used in nms.
        self.nms_thresh = nms_thresh
        if nms_thresh <= 0:
            raise ValueError('nms_threshold must be non negative.')
        self.conf_thresh = conf_thresh
        self.variance = cfg['variance']
Example #5
Source File: detection.py    From RefineDet.PyTorch with MIT License 5 votes vote down vote up 
def __init__(self, num_classes, size, bkg_label, top_k, conf_thresh, nms_thresh):
        self.num_classes = num_classes
        self.background_label = bkg_label
        self.top_k = top_k
        # Parameters used in nms.
        self.nms_thresh = nms_thresh
        if nms_thresh <= 0:
            raise ValueError('nms_threshold must be non negative.')
        self.conf_thresh = conf_thresh
        self.variance = cfg[str(size)]['variance']
Example #6
Source File: detection.py    From SSD_resnet_pytorch with MIT License 5 votes vote down vote up 
def __init__(self, num_classes, bkg_label, top_k, conf_thresh, nms_thresh):
        self.num_classes = num_classes
        self.background_label = bkg_label
        self.top_k = top_k
        # Parameters used in nms.
        self.nms_thresh = nms_thresh
        if nms_thresh <= 0:
            raise ValueError('nms_threshold must be non negative.')
        self.conf_thresh = conf_thresh
        self.variance = cfg['variance']
Example #7
Source File: detection.py    From repulsion_loss_ssd with MIT License 5 votes vote down vote up 
def __init__(self, num_classes, bkg_label, top_k, conf_thresh, nms_thresh):
        self.num_classes = num_classes
        self.background_label = bkg_label
        self.top_k = top_k
        # Parameters used in nms.
        self.nms_thresh = nms_thresh
        if nms_thresh <= 0:
            raise ValueError('nms_threshold must be non negative.')
        self.conf_thresh = conf_thresh
        self.variance = cfg['variance']
Example #8
Source File: detection.py    From ssd.pytorch with MIT License 5 votes vote down vote up 
def __init__(self, num_classes, bkg_label, top_k, conf_thresh, nms_thresh):
        self.num_classes = num_classes
        self.background_label = bkg_label
        self.top_k = top_k
        # Parameters used in nms.
        self.nms_thresh = nms_thresh
        if nms_thresh <= 0:
            raise ValueError('nms_threshold must be non negative.')
        self.conf_thresh = conf_thresh
        self.variance = cfg['variance']
Example #9
Source File: detection.py    From multitrident with Apache License 2.0 5 votes vote down vote up 
def __init__(self, num_classes, size, bkg_label, top_k, conf_thresh, nms_thresh):
        self.num_classes = num_classes
        self.background_label = bkg_label
        self.top_k = top_k
        # Parameters used in nms.
        self.nms_thresh = nms_thresh
        if nms_thresh <= 0:
            raise ValueError('nms_threshold must be non negative.')
        self.conf_thresh = conf_thresh
        self.variance = cfg[str(size)]['variance']