def make_model(network, input_shape): if network == 'resnet101_softmax': return resnet101_fpn(input_shape, channels=3, activation="softmax") elif network == 'resnet152_2': return resnet152_fpn(input_shape, channels=2, activation="sigmoid") elif network == 'resnet101_2': return resnet101_fpn(input_shape, channels=2, activation="sigmoid") elif network == 'resnet50_2': return resnet50_fpn(input_shape, channels=2, activation="sigmoid") elif network == 'resnetv2': return inception_resnet_v2_fpn(input_shape, channels=2, activation="sigmoid") elif network == 'resnetv2_3': return inception_resnet_v2_fpn(input_shape, channels=3, activation="sigmoid") elif network == 'densenet169': return densenet_fpn(input_shape, channels=2, activation="sigmoid") elif network == 'densenet169_softmax': return densenet_fpn(input_shape, channels=3, activation="softmax") elif network == 'resnet101_unet_2': return resnet101_fpn(input_shape, channels=2, activation="sigmoid") elif network == 'xception_fpn': return xception_fpn(input_shape, channels=2, activation="sigmoid") elif network == 'resnet50_2': return resnet50_fpn(input_shape, channels=2, activation="sigmoid") else: raise ValueError('unknown network ' + network)
def make_model(network, black_detect=False): input_shape = (None, None, 3) if network == "xception_fpn": return xception_fpn(input_shape, channels=1, activation="sigmoid", black_detect=black_detect) elif network == "resnet152": return resnet152_fpn(input_shape, channels=1, activation="sigmoid", black_detect=black_detect) elif network == "inception_resnet_v2": return inception_resnet_v2_fpn(input_shape, channels=1, activation="sigmoid", black_detect=black_detect) elif network == "densenet169": return densenet_fpn(input_shape, channels=1, activation="sigmoid", black_detect=black_detect) elif network == "testnet": return testnet(input_shape, channels=1, activation="sigmoid", black_detect=black_detect) else: raise NotImplementedError("Network {} not implement.".format(network))