python之在 tensorflow 中使用两种不同的模型

我正在尝试使用两种不同的移动网络模型。以下是我如何初始化模型的代码。

def initialSetup(): 
    os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
    start_time = timeit.default_timer() 
 
    # This takes 2-5 seconds to run 
    # Unpersists graph from file 
    with tf.gfile.FastGFile('age/output_graph.pb', 'rb') as f: 
        age_graph_def = tf.GraphDef() 
        age_graph_def.ParseFromString(f.read()) 
        tf.import_graph_def(age_graph_def, name='') 
 
    with tf.gfile.FastGFile('output_graph.pb', 'rb') as f: 
        gender_graph_def = tf.GraphDef() 
        gender_graph_def.ParseFromString(f.read()) 
        tf.import_graph_def(gender_graph_def, name='') 
 
    print ('Took {} seconds to unpersist the graph'.format(timeit.default_timer() - start_time)) 

由于两者是两种不同的模型，我该如何使用它进行预测？

更新

initialSetup() 
 
age_session = tf.Session(graph=age_graph_def) 
gender_session = tf.Session(graph=gender_graph_def) 
 
with tf.Session() as sess: 
    start_time = timeit.default_timer() 
 
    # Feed the image_data as input to the graph and get first prediction 
    softmax_tensor = age_session.graph.get_tensor_by_name('final_result:0') 
 
    print ('Took {} seconds to feed data to graph'.format(timeit.default_timer() - start_time)) 
 
    while True: 
        # Capture frame-by-frame 
        ret, frame = video_capture.read() 

错误

Traceback (most recent call last): File "C:/Users/Desktop/untitled/testimg/testimg/combo.py", line 48, in age_session = tf.Session(graph=age_graph_def) File "C:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1292, in init super(Session, self).init(target, graph, config=config) File "C:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 529, in init raise TypeError('graph must be a tf.Graph, but got %s' % type(graph)) TypeError: graph must be a tf.Graph, but got Exception ignored in: > Traceback (most recent call last): File "C:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 587, in del if self._session is not None: AttributeError: 'Session' object has no attribute '_session'

请您参考如下方法:

当您在同一个图中使用多个模型时，使用名称范围来为各个张量提供可预测的名称。例如，您可以重写 initial_setup() 如下:

def initialSetup(): 
    os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
    start_time = timeit.default_timer() 
 
    # This takes 2-5 seconds to run 
    # Unpersists graph from file 
    with tf.gfile.FastGFile('age/output_graph.pb', 'rb') as f: 
        age_graph_def = tf.GraphDef() 
        age_graph_def.ParseFromString(f.read()) 
        tf.import_graph_def(age_graph_def, name='age_model') 
 
    with tf.gfile.FastGFile('output_graph.pb', 'rb') as f: 
        gender_graph_def = tf.GraphDef() 
        gender_graph_def.ParseFromString(f.read()) 
        tf.import_graph_def(gender_graph_def, name='gender_model') 
 
    print ('Took {} seconds to unpersist the graph'.format(timeit.default_timer() - start_time)) 

现在 age_graph_def 中所有节点的名称都将以 "age_model/" 为前缀，而 gender_graph_def 中所有节点的名称将以前缀为前缀code> 将以 "gender_model/" 为前缀。它们都是同一默认图的一部分，因此您可以使用不带 graph 参数的单个 tf.Session 来访问任一模型。

initialSetup() 
 
with tf.Session() as sess: 
    start_time = timeit.default_timer() 
 
    # Feed the image_data as input to the graph and get first prediction 
    softmax_tensor = sess.graph.get_tensor_by_name('age_model/final_result:0') 
 
    # Alternatively, to get a tensor from the gender model: 
    # tensor = sess.graph.get_tensor_by_name('gender_model/...') 
 
    print ('Took {} seconds to feed data to graph'.format(timeit.default_timer() - start_time)) 
 
    while True: 
        # Capture frame-by-frame 
        ret, frame = video_capture.read()