input_tensors=["import/image_tensor:0"],
output_tensors=['import/detection_boxes:0', 'import/detection_scores:0',
'import/detection_classes:0', 'import/num_detections:0']
_input = [graph.get_tensor_by_name(tensor_name) for tensor_name in input_tensors]
_output_ops = [graph.get_tensor_by_name(tensor_name) for tensor_name in output_tensors]
sess = tf.Session(graph=graph, config=_config_proto)
image_expanded = np array of size specific to model (1, 512, 512, 1)
(boxes, scores, classes, num_detections) = sess.run(self._output_ops, feed_dict={_input: image_expanded})
当我运行sess.run时,我得到了一个错误
--------------------------------------------------------------------------- TypeError Traceback (most recent call last) in 3 image_np = load_image_into_numpy_array(image) 4 image_np_expanded = np.expand_dims(image_np, axis=0) ----> 5 (boxes, scores, classes, num_detections) = sess.run(_output_ops, feed_dict={_input: image_np_expanded}) 6 print(boxes) 7 break
TypeError: unhashable type: 'list'
在这种情况下_输入是一个列表。因此sess.run应该有_输入[0]
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