def test_fast_rcnn_10(self):
from dlpy.applications import Faster_RCNN
model = Faster_RCNN(self.s,
backbone='mobilenetv2',
width=123,
height=321)
model.print_summary()
def test_fast_rcnn_2(self):
from dlpy.applications import Faster_RCNN
anchor_num_to_sample = 64
anchor_ratio = [2312312, 2, 2]
anchor_scale = [1.2, 2.3, 3.4, 5.6]
coord_type = 'rect'
model = Faster_RCNN(self.s, model_table = 'fast', anchor_num_to_sample = anchor_num_to_sample,
anchor_ratio = anchor_ratio, anchor_scale = anchor_scale, coord_type = coord_type)
self.assertTrue(model.layers[20].config == self.sample_syntax['faster_rcnn1'])
model.print_summary()
def test_fast_rcnn_9(self):
from dlpy.applications import Faster_RCNN
model = Faster_RCNN(self.s, backbone='mobilenetv1')
model.print_summary()
def test_fast_rcnn_8(self):
from dlpy.applications import Faster_RCNN
model = Faster_RCNN(self.s, backbone='resnet34')
model.print_summary()
def test_fast_rcnn_7(self):
from dlpy.applications import Faster_RCNN
model = Faster_RCNN(self.s,
backbone='resnet18',
number_of_neurons_in_fc=[1024, 1024])
model.print_summary()
def test_fast_rcnn(self):
from dlpy.applications import Faster_RCNN
model = Faster_RCNN(self.s)
model.print_summary()