# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Bipartite matcher implementation.""" import tensorflow as tf from tensorflow.contrib.image.python.ops import image_ops from object_detection.core import matcher class GreedyBipartiteMatcher(matcher.Matcher): """Wraps a Tensorflow greedy bipartite matcher.""" def _match(self, similarity_matrix, num_valid_rows=-1): """Bipartite matches a collection rows and columns. A greedy bi-partite. TODO: Add num_valid_columns options to match only that many columns with all the rows. Args: similarity_matrix: Float tensor of shape [N, M] with pairwise similarity where higher values mean more similar. num_valid_rows: A scalar or a 1-D tensor with one element describing the number of valid rows of similarity_matrix to consider for the bipartite matching. If set to be negative, then all rows from similarity_matrix are used. Returns: match_results: int32 tensor of shape [M] with match_results[i]=-1 meaning that column i is not matched and otherwise that it is matched to row match_results[i]. """ # Convert similarity matrix to distance matrix as tf.image.bipartite tries # to find minimum distance matches. distance_matrix = -1 * similarity_matrix _, match_results = image_ops.bipartite_match( distance_matrix, num_valid_rows) match_results = tf.reshape(match_results, [-1]) match_results = tf.cast(match_results, tf.int32) return match_results