def TBPP512(input_shape=(512, 512, 3), softmax=True):
"""TextBoxes++512 architecture.
# Arguments
input_shape: Shape of the input image.
# References
- [TextBoxes++: A Single-Shot Oriented Scene Text Detector](https://arxiv.org/abs/1801.02765)
"""
# SSD body
x = input_tensor = Input(shape=input_shape)
source_layers = ssd512_body(x)
num_maps = len(source_layers)
# Add multibox head for classification and regression
num_priors = [14] * num_maps
normalizations = [1] * num_maps
output_tensor = multibox_head(source_layers, num_priors, normalizations,
softmax)
model = Model(input_tensor, output_tensor)
# parameters for prior boxes
model.image_size = input_shape[:2]
model.source_layers = source_layers
model.aspect_ratios = [[1, 2, 3, 5, 1 / 2, 1 / 3, 1 / 5] * 2] * num_maps
#model.shifts = [[(0.0, 0.0)] * 7 + [(0.0, 0.5)] * 7] * num_maps
model.shifts = [[(0.0, -0.25)] * 7 + [(0.0, 0.25)] * 7] * num_maps
model.special_ssd_boxes = False
model.scale = 0.5
return model
def SL512(input_shape=(512, 512, 3), softmax=True):
"""SegLink512 architecture.
# Arguments
input_shape: Shape of the input image.
# References
https://arxiv.org/abs/1703.06520
"""
# SSD body
x = input_tensor = Input(shape=input_shape)
source_layers = ssd512_body(x)
# Add multibox head for classification and regression
num_priors = [1, 1, 1, 1, 1, 1, 1]
normalizations = [20, -1, -1, -1, -1, -1, -1]
output_tensor = multibox_head(source_layers, num_priors, normalizations, softmax)
model = Model(input_tensor, output_tensor)
# parameters for prior boxes
model.image_size = input_shape[:2]
model.source_layers = source_layers
return model