本文整理汇总了Python中model.utils.config.cfg.CROP_RESIZE_WITH_MAX_POOL属性的典型用法代码示例。如果您正苦于以下问题:Python cfg.CROP_RESIZE_WITH_MAX_POOL属性的具体用法?Python cfg.CROP_RESIZE_WITH_MAX_POOL怎么用?Python cfg.CROP_RESIZE_WITH_MAX_POOL使用的例子?那么, 这里精选的属性代码示例或许可以为您提供帮助。您也可以进一步了解该属性所在类model.utils.config.cfg
的用法示例。
在下文中一共展示了cfg.CROP_RESIZE_WITH_MAX_POOL属性的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: __init__
# 需要导入模块: from model.utils.config import cfg [as 别名]
# 或者: from model.utils.config.cfg import CROP_RESIZE_WITH_MAX_POOL [as 别名]
def __init__(self, classes, class_agnostic):
super(_fasterRCNN, self).__init__()
self.classes = classes
self.n_classes = len(classes)
self.class_agnostic = class_agnostic
# loss
self.RCNN_loss_cls = 0
self.RCNN_loss_bbox = 0
# define rpn
self.RCNN_rpn = _RPN(self.dout_base_model)
self.RCNN_proposal_target = _ProposalTargetLayer(self.n_classes)
self.RCNN_roi_pool = _RoIPooling(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.RCNN_roi_align = RoIAlignAvg(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.grid_size = cfg.POOLING_SIZE * 2 if cfg.CROP_RESIZE_WITH_MAX_POOL else cfg.POOLING_SIZE
self.RCNN_roi_crop = _RoICrop()
示例2: __init__
# 需要导入模块: from model.utils.config import cfg [as 别名]
# 或者: from model.utils.config.cfg import CROP_RESIZE_WITH_MAX_POOL [as 别名]
def __init__(self, classes, class_agnostic):
super(_fasterRCNN, self).__init__()
self.classes = classes
self.n_classes = len(classes)
self.class_agnostic = class_agnostic
# loss
self.RCNN_loss_cls = 0
self.RCNN_loss_bbox = 0
# define rpn
self.RCNN_rpn = _RPN(self.dout_base_model)
self.RCNN_proposal_target = _ProposalTargetLayer(self.n_classes)
self.RCNN_roi_pool = _RoIPooling(cfg.POOLING_SIZE, cfg.POOLING_SIZE,
1.0 / 16.0)
self.RCNN_roi_align = RoIAlignAvg(cfg.POOLING_SIZE, cfg.POOLING_SIZE,
1.0 / 16.0)
self.grid_size = cfg.POOLING_SIZE * 2 if \
cfg.CROP_RESIZE_WITH_MAX_POOL else cfg.POOLING_SIZE
self.RCNN_roi_crop = _RoICrop()
示例3: __init__
# 需要导入模块: from model.utils.config import cfg [as 别名]
# 或者: from model.utils.config.cfg import CROP_RESIZE_WITH_MAX_POOL [as 别名]
def __init__(self, classes, class_agnostic, sup=False):
super(_fasterRCNN, self).__init__()
self.classes = classes
self.n_classes = len(classes)
self.class_agnostic = class_agnostic
# loss
self.RCNN_loss_cls = 0
self.RCNN_loss_bbox = 0
# define rpn
self.RCNN_rpn = _RPN(self.dout_base_model)
self.RCNN_proposal_target = _ProposalTargetLayer(self.n_classes)
self.RCNN_roi_pool = _RoIPooling(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.RCNN_roi_align = RoIAlignAvg(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.grid_size = cfg.POOLING_SIZE * 2 if cfg.CROP_RESIZE_WITH_MAX_POOL else cfg.POOLING_SIZE
self.RCNN_roi_crop = _RoICrop()
self.sup = sup
示例4: __init__
# 需要导入模块: from model.utils.config import cfg [as 别名]
# 或者: from model.utils.config.cfg import CROP_RESIZE_WITH_MAX_POOL [as 别名]
def __init__(self, classes, class_agnostic):
super(_RFCN, self).__init__()
self.classes = classes
self.n_classes = len(classes)
self.class_agnostic = class_agnostic
# loss
self.RCNN_loss_cls = 0
self.RCNN_loss_bbox = 0
self.box_num_classes = 1 if class_agnostic else self.n_classes
# define rpn
self.RCNN_rpn = _RPN(self.dout_base_model)
self.RCNN_proposal_target = _ProposalTargetLayer(self.n_classes)
self.RCNN_psroi_pool_cls = PSRoIPool(cfg.POOLING_SIZE, cfg.POOLING_SIZE,
spatial_scale=1/16.0, group_size=cfg.POOLING_SIZE,
output_dim=self.n_classes)
self.RCNN_psroi_pool_loc = PSRoIPool(cfg.POOLING_SIZE, cfg.POOLING_SIZE,
spatial_scale=1/16.0, group_size=cfg.POOLING_SIZE,
output_dim=self.box_num_classes * 4)
self.pooling = nn.AvgPool2d(kernel_size=cfg.POOLING_SIZE, stride=cfg.POOLING_SIZE)
self.grid_size = cfg.POOLING_SIZE * 2 if cfg.CROP_RESIZE_WITH_MAX_POOL else cfg.POOLING_SIZE
示例5: __init__
# 需要导入模块: from model.utils.config import cfg [as 别名]
# 或者: from model.utils.config.cfg import CROP_RESIZE_WITH_MAX_POOL [as 别名]
def __init__(self, classes, class_agnostic):
super(_FPN, self).__init__()
self.classes = classes
self.n_classes = len(classes)
self.class_agnostic = class_agnostic
# loss
self.RCNN_loss_cls = 0
self.RCNN_loss_bbox = 0
self.maxpool2d = nn.MaxPool2d(1, stride=2)
# define rpn
self.RCNN_rpn = _RPN_FPN(self.dout_base_model)
self.RCNN_proposal_target = _ProposalTargetLayer(self.n_classes)
# NOTE: the original paper used pool_size = 7 for cls branch, and 14 for mask branch, to save the
# computation time, we first use 14 as the pool_size, and then do stride=2 pooling for cls branch.
self.RCNN_roi_pool = _RoIPooling(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.RCNN_roi_align = RoIAlignAvg(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.grid_size = cfg.POOLING_SIZE * 2 if cfg.CROP_RESIZE_WITH_MAX_POOL else cfg.POOLING_SIZE
self.RCNN_roi_crop = _RoICrop()
示例6: __init__
# 需要导入模块: from model.utils.config import cfg [as 别名]
# 或者: from model.utils.config.cfg import CROP_RESIZE_WITH_MAX_POOL [as 别名]
def __init__(self, classes, class_agnostic):
super(_fasterRCNN, self).__init__()
self.classes = classes
self.n_classes = len(self.classes)
self.class_agnostic = class_agnostic
# loss
self.RCNN_loss_cls = 0
self.RCNN_loss_bbox = 0
# define rpn
self.RCNN_rpn = _RPN(self.dout_base_model)
self.RCNN_proposal_target = _ProposalTargetLayer(self.n_classes)
self.RCNN_roi_pool = _RoIPooling(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0 / 16.0)
self.RCNN_roi_align = RoIAlignAvg(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0 / 16.0)
self.grid_size = cfg.POOLING_SIZE * 2 if cfg.CROP_RESIZE_WITH_MAX_POOL else cfg.POOLING_SIZE
self.RCNN_roi_crop = _RoICrop()
示例7: __init__
# 需要导入模块: from model.utils.config import cfg [as 别名]
# 或者: from model.utils.config.cfg import CROP_RESIZE_WITH_MAX_POOL [as 别名]
def __init__(self, n_classes, class_agnostic):
super(_fasterRCNN, self).__init__()
self.n_classes = n_classes
self.class_agnostic = class_agnostic
# loss
self.RCNN_loss_cls = 0
self.RCNN_loss_bbox = 0
# define rpn
self.RCNN_rpn = _RPN(self.dout_base_model)
self.RCNN_proposal_target = _ProposalTargetLayer(self.n_classes)
self.RCNN_roi_pool = _RoIPooling(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.RCNN_roi_align = RoIAlignAvg(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.grid_size = cfg.POOLING_SIZE * 2 if cfg.CROP_RESIZE_WITH_MAX_POOL else cfg.POOLING_SIZE
self.RCNN_roi_crop = _RoICrop()
示例8: __init__
# 需要导入模块: from model.utils.config import cfg [as 别名]
# 或者: from model.utils.config.cfg import CROP_RESIZE_WITH_MAX_POOL [as 别名]
def __init__(self, classes, class_agnostic):
super(_fasterRCNN, self).__init__()
self.classes = classes
self.n_classes = len(classes)
self.class_agnostic = class_agnostic
# loss
self.RCNN_loss_cls = 0
self.RCNN_loss_bbox = 0
# define rpn
self.RCNN_rpn = _RPN(self.dout_base_model)
self.RCNN_proposal_target = _ProposalTargetLayer(self.n_classes)
self.RCNN_roi_pool = _RoIPooling(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.RCNN_roi_align = RoIAlignAvg(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.grid_size = cfg.POOLING_SIZE * 2 if cfg.CROP_RESIZE_WITH_MAX_POOL else cfg.POOLING_SIZE
self.RCNN_roi_crop = _RoICrop()
self.Dis = Discriminator()
示例9: __init__
# 需要导入模块: from model.utils.config import cfg [as 别名]
# 或者: from model.utils.config.cfg import CROP_RESIZE_WITH_MAX_POOL [as 别名]
def __init__(self, classes, class_agnostic):
super(_da_fasterRCNN, self).__init__()
self.classes = classes
self.n_classes = len(classes)
self.class_agnostic = class_agnostic
# loss
self.RCNN_loss_cls = 0
self.RCNN_loss_bbox = 0
# define rpn
self.RCNN_rpn = _RPN(self.dout_base_model)
self.RCNN_proposal_target = _ProposalTargetLayer(self.n_classes)
self.RCNN_roi_pool = _RoIPooling(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.RCNN_roi_align = RoIAlignAvg(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.grid_size = cfg.POOLING_SIZE * 2 if cfg.CROP_RESIZE_WITH_MAX_POOL else cfg.POOLING_SIZE
self.RCNN_roi_crop = _RoICrop()
self.Dis = Discriminator()
示例10: __init__
# 需要导入模块: from model.utils.config import cfg [as 别名]
# 或者: from model.utils.config.cfg import CROP_RESIZE_WITH_MAX_POOL [as 别名]
def __init__(self, classes, class_agnostic,context):
super(_fasterRCNN, self).__init__()
self.classes = classes
self.n_classes = len(classes)
self.class_agnostic = class_agnostic
# loss
self.RCNN_loss_cls = 0
self.RCNN_loss_bbox = 0
self.context = context
# define rpn
self.RCNN_rpn = _RPN(self.dout_base_model)
self.RCNN_proposal_target = _ProposalTargetLayer(self.n_classes)
self.RCNN_roi_pool = _RoIPooling(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.RCNN_roi_align = RoIAlignAvg(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.grid_size = cfg.POOLING_SIZE * 2 if cfg.CROP_RESIZE_WITH_MAX_POOL else cfg.POOLING_SIZE
self.RCNN_roi_crop = _RoICrop()
示例11: __init__
# 需要导入模块: from model.utils.config import cfg [as 别名]
# 或者: from model.utils.config.cfg import CROP_RESIZE_WITH_MAX_POOL [as 别名]
def __init__(self, classes, class_agnostic,lc):
super(_fasterRCNN, self).__init__()
self.classes = classes
self.n_classes = len(classes)
self.class_agnostic = class_agnostic
# loss
self.RCNN_loss_cls = 0
self.RCNN_loss_bbox = 0
self.lc = lc
# define rpn
self.RCNN_rpn = _RPN(self.dout_base_model)
self.RCNN_proposal_target = _ProposalTargetLayer(self.n_classes)
self.RCNN_roi_pool = _RoIPooling(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.RCNN_roi_align = RoIAlignAvg(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.grid_size = cfg.POOLING_SIZE * 2 if cfg.CROP_RESIZE_WITH_MAX_POOL else cfg.POOLING_SIZE
self.RCNN_roi_crop = _RoICrop()
示例12: __init__
# 需要导入模块: from model.utils.config import cfg [as 别名]
# 或者: from model.utils.config.cfg import CROP_RESIZE_WITH_MAX_POOL [as 别名]
def __init__(self, classes, class_agnostic,lc,gc):
super(_fasterRCNN, self).__init__()
self.classes = classes
self.n_classes = len(classes)
self.class_agnostic = class_agnostic
# loss
self.RCNN_loss_cls = 0
self.RCNN_loss_bbox = 0
self.lc = lc
self.gc = gc
# define rpn
self.RCNN_rpn = _RPN(self.dout_base_model)
self.RCNN_proposal_target = _ProposalTargetLayer(self.n_classes)
self.RCNN_roi_pool = _RoIPooling(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.RCNN_roi_align = RoIAlignAvg(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.grid_size = cfg.POOLING_SIZE * 2 if cfg.CROP_RESIZE_WITH_MAX_POOL else cfg.POOLING_SIZE
self.RCNN_roi_crop = _RoICrop()
示例13: __init__
# 需要导入模块: from model.utils.config import cfg [as 别名]
# 或者: from model.utils.config.cfg import CROP_RESIZE_WITH_MAX_POOL [as 别名]
def __init__(self, classes, class_agnostic):
super(_RFCN, self).__init__()
self.classes = classes
self.n_classes = len(classes)
self.n_reg_classes = (1 if class_agnostic else len(classes))
self.class_agnostic = class_agnostic
self.n_bbox_reg = (4 if class_agnostic else len(classes))
# loss
self.RFCN_loss_cls = 0
self.RFCN_loss_bbox = 0
# define rpn
self.RFCN_rpn = _RPN(self.dout_base_model)
self.RFCN_proposal_target = _ProposalTargetLayer(self.n_classes)
self.RFCN_tracking_proposal_target = _TrackingProposalTargetLayer(self.n_classes)
#self.RFCN_roi_pool = _RoIPooling(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.RFCN_psroi_cls_pool = _PSRoIPooling(cfg.POOLING_SIZE, cfg.POOLING_SIZE,
spatial_scale=1.0/16.0, group_size=7, output_dim=self.n_classes)
self.RFCN_psroi_loc_pool = _PSRoIPooling(cfg.POOLING_SIZE, cfg.POOLING_SIZE,
spatial_scale=1.0/16.0, group_size=7, output_dim=4*self.n_reg_classes)
#self.RFCN_roi_align = RoIAlignAvg(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.grid_size = cfg.POOLING_SIZE * 2 if cfg.CROP_RESIZE_WITH_MAX_POOL else cfg.POOLING_SIZE
#self.RFCN_roi_crop = _RoICrop()
self.RFCN_cls_net = nn.Conv2d(512,self.n_classes*7*7, [1,1], padding=0, stride=1)
nn.init.normal(self.RFCN_cls_net.weight.data, 0.0, 0.01)
self.RFCN_bbox_net = nn.Conv2d(512, 4*self.n_reg_classes*7*7, [1,1], padding=0, stride=1)
nn.init.normal(self.RFCN_bbox_net.weight.data, 0.0, 0.01)
#self.corr_bbox_net = nn.Conv2d(1051, 4*self.n_reg_classes*7*7, [1,1], padding=0, stride=1)
#nn.init.normal(self.corr_bbox_net.weight.data, 0.0, 0.01)
self.conv3_corr_layer = Correlation(pad_size=8, kernel_size=1, max_displacement=8, stride1=2, stride2=2)
self.conv4_corr_layer = Correlation(pad_size=8, kernel_size=1, max_displacement=8, stride1=1, stride2=1)
self.conv5_corr_layer = Correlation(pad_size=8, kernel_size=1, max_displacement=8, stride1=1, stride2=1)
self.RFCN_cls_score = nn.AvgPool2d((7,7), stride=(7,7))
self.RFCN_bbox_pred = nn.AvgPool2d((7,7), stride=(7,7))
self.RFCN_tracking_pred = nn.AvgPool2d((7,7), stride=(7,7))
示例14: __init__
# 需要导入模块: from model.utils.config import cfg [as 别名]
# 或者: from model.utils.config.cfg import CROP_RESIZE_WITH_MAX_POOL [as 别名]
def __init__(self, classes, class_agnostic):
super(CoupleNet, self).__init__()
self.classes = classes
self.n_classes = len(classes)
self.class_agnostic = class_agnostic
# loss
self.RCNN_loss_cls = 0
self.RCNN_loss_bbox = 0
self.box_num_classes = 1 if class_agnostic else self.n_classes
# define rpn
self.RCNN_rpn = _RPN(self.dout_base_model)
self.RCNN_proposal_target = _ProposalTargetLayer(self.n_classes)
self.RCNN_roi_pool = _RoIPooling(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0 / 16.0)
self.RCNN_roi_align = RoIAlignAvg(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0 / 16.0)
self.RCNN_roi_crop = _RoICrop()
self.RCNN_psroi_pool_cls = PSRoIPool(cfg.POOLING_SIZE, cfg.POOLING_SIZE,
spatial_scale=1/16.0, group_size=cfg.POOLING_SIZE,
output_dim=self.n_classes)
self.RCNN_psroi_pool_loc = PSRoIPool(cfg.POOLING_SIZE, cfg.POOLING_SIZE,
spatial_scale=1/16.0, group_size=cfg.POOLING_SIZE,
output_dim=self.box_num_classes * 4)
self.avg_pooling = nn.AvgPool2d(kernel_size=cfg.POOLING_SIZE, stride=cfg.POOLING_SIZE)
self.grid_size = cfg.POOLING_SIZE * 2 if cfg.CROP_RESIZE_WITH_MAX_POOL else cfg.POOLING_SIZE
示例15: __init__
# 需要导入模块: from model.utils.config import cfg [as 别名]
# 或者: from model.utils.config.cfg import CROP_RESIZE_WITH_MAX_POOL [as 别名]
def __init__(self, classes, class_agnostic, lighthead=False, compact_mode=False):
super(_fasterRCNN, self).__init__()
self.classes = classes
self.n_classes = len(classes)
self.class_agnostic = class_agnostic
self.lighthead = lighthead
# loss
self.RCNN_loss_cls = 0
self.RCNN_loss_bbox = 0
# define Large Separable Convolution Layer
if self.lighthead:
self.lh_mode = 'S' if compact_mode else 'L'
self.lsconv = LargeSeparableConv2d(
self.dout_lh_base_model, bias=False, bn=False, setting=self.lh_mode)
self.lh_relu = nn.ReLU(inplace=True)
# define rpn
self.RCNN_rpn = _RPN(self.dout_base_model)
self.RCNN_proposal_target = _ProposalTargetLayer(self.n_classes)
self.RCNN_roi_pool = _RoIPooling(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.RCNN_roi_align = RoIAlignAvg(cfg.POOLING_SIZE, cfg.POOLING_SIZE, 1.0/16.0)
self.grid_size = cfg.POOLING_SIZE * 2 if cfg.CROP_RESIZE_WITH_MAX_POOL else cfg.POOLING_SIZE
self.RCNN_roi_crop = _RoICrop()
self.rpn_time = None
self.pre_roi_time = None
self.roi_pooling_time = None
self.subnet_time = None