dnn_library.py

import tensorflow as tf
import tensorflow.contrib.slim as slim
from nets import inception_v1, inception_v2, inception_v3, resnet_v1, resnet_v2, vgg

model={
        'resnet_v1_50': {'shape': [1, 224, 224, 3],
						 'scope': resnet_v1.resnet_arg_scope(),
						 'net': resnet_v1.resnet_v1_50,
						 'num_classes': 1000},
		'resnet_v1_101': {'shape': [1, 224, 224, 3],
						 'scope': resnet_v1.resnet_arg_scope(),
						 'net': resnet_v1.resnet_v1_101,
						 'num_classes': 1000},
		'resnet_v1_152': {'shape': [1, 224, 224, 3],
						 'scope': resnet_v1.resnet_arg_scope(),
						 'net': resnet_v1.resnet_v1_152,
						 'num_classes': 1000},
		'resnet_v2_50': {'shape': [1, 224, 224, 3],
						 'scope': resnet_v2.resnet_arg_scope(),
						 'net': resnet_v2.resnet_v2_50,
						 'num_classes': 1000},
		'resnet_v2_101': {'shape': [1, 224, 224, 3],
						 'scope': resnet_v2.resnet_arg_scope(),
						 'net': resnet_v2.resnet_v2_101,
						 'num_classes': 1000},
		'resnet_v2_152': {'shape': [1, 224, 224, 3],
						 'scope': resnet_v2.resnet_arg_scope(),
						 'net': resnet_v2.resnet_v2_152,
						 'num_classes': 1000},
		'inception_v1':  {'shape': [1, 224, 224, 3],
						 'scope': inception_v1.inception_v1_arg_scope(),
						 'net': inception_v1.inception_v1,
						 'num_classes': 1000},
		'inception_v2':  {'shape': [1, 224, 224, 3],
						 'scope': inception_v2.inception_v2_arg_scope(),
						 'net': inception_v2.inception_v2,
						 'num_classes': 1000},
		'inception_v3':  {'shape': [1, 299, 299, 3],
						 'scope': inception_v3.inception_v3_arg_scope(),
						 'net': inception_v3.inception_v3,
						 'num_classes': 1000},
		'vgg_16':        {'shape': [1, 224, 224, 3],
						 'scope': vgg.vgg_arg_scope(),
						 'net': vgg.vgg_16,
						 'num_classes': 1000},
		'vgg_19':        {'shape': [1, 224, 224, 3],
						 'scope': vgg.vgg_arg_scope(),
						 'net': vgg.vgg_19,
						 'num_classes': 1000},
		
		
}