def __init__(self, classes, num_layers=101, pretrained=False, class_agnostic=False):
self.model_path = '/data/ztc/detectionModel/resnet101_caffe.pth'
self.dout_base_model = 1024
self.pretrained = pretrained
self.class_agnostic = class_agnostic
_fasterRCNN.__init__(self, classes, class_agnostic)
def __init__(self, classes, pretrained=False, class_agnostic=False):
self.model_path = './data/vgg16_caffe.pth'
self.dout_base_model = 512
self.pretrained = pretrained
self.class_agnostic = class_agnostic
_fasterRCNN.__init__(self, classes, class_agnostic)
def __init__(
self, classes, pretrained_path, pretrained=False, class_agnostic=False
):
self.model_path = pretrained_path
self.dout_base_model = 512
self.pretrained = pretrained
self.class_agnostic = class_agnostic
_fasterRCNN.__init__(self, classes, class_agnostic)
def __init__(self, classes, pretrained=False, class_agnostic=False):
# 预训练模型路径,已经改为相对路径
# self.model_path = '/data/ztc/detectionModel/vgg16_caffe.pth'
self.model_path = './data/ztc/detectionModel/vgg16_caffe.pth'
# RPN网络中使用,输入rpn的feature_map的维度
self.dout_base_model = 512
self.pretrained = pretrained
self.class_agnostic = class_agnostic
# 调用了_fasterRCNN的__init__()方法
_fasterRCNN.__init__(self, classes, class_agnostic)
def __init__(
self,
classes,
pretrained_path,
pretrained=False,
class_agnostic=False,
lc=False,
gc=False,
):
self.model_path = pretrained_path
self.dout_base_model = 512
self.pretrained = pretrained
self.class_agnostic = class_agnostic
self.lc = lc
self.gc = gc
_fasterRCNN.__init__(self, classes, class_agnostic, self.lc, self.gc)
def __init__(
self,
classes,
num_layers=101,
pretrained=False,
pretrained_path=None,
class_agnostic=False,
lc=False,
gc=False,
):
self.model_path = pretrained_path
self.dout_base_model = 1024
self.pretrained = pretrained
self.class_agnostic = class_agnostic
self.lc = lc
self.gc = gc
self.layers = num_layers
if not pretrained_path:
self.model_path = pretrained_path
_fasterRCNN.__init__(self, classes, class_agnostic, lc, gc)
