1 /* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
2
3 Licensed under the Apache License, Version 2.0 (the "License");
4 you may not use this file except in compliance with the License.
5 You may obtain a copy of the License at
6
7 http://www.apache.org/licenses/LICENSE-2.0
8
9 Unless required by applicable law or agreed to in writing, software
10 distributed under the License is distributed on an "AS IS" BASIS,
11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 See the License for the specific language governing permissions and
13 limitations under the License.
14 ==============================================================================*/
15
16 #include "tensorflow/examples/speech_commands/accuracy_utils.h"
17
18 #include <fstream>
19 #include <iomanip>
20 #include <unordered_set>
21
22 #include "tensorflow/core/lib/io/path.h"
23 #include "tensorflow/core/lib/strings/str_util.h"
24
25 namespace tensorflow {
26
ReadGroundTruthFile(const string & file_name,std::vector<std::pair<string,int64>> * result)27 Status ReadGroundTruthFile(const string& file_name,
28 std::vector<std::pair<string, int64>>* result) {
29 std::ifstream file(file_name);
30 if (!file) {
31 return tensorflow::errors::NotFound("Ground truth file '", file_name,
32 "' not found.");
33 }
34 result->clear();
35 string line;
36 while (std::getline(file, line)) {
37 std::vector<string> pieces = tensorflow::str_util::Split(line, ',');
38 if (pieces.size() != 2) {
39 continue;
40 }
41 float timestamp;
42 if (!tensorflow::strings::safe_strtof(pieces[1].c_str(), ×tamp)) {
43 return tensorflow::errors::InvalidArgument(
44 "Wrong number format at line: ", line);
45 }
46 string label = pieces[0];
47 auto timestamp_int64 = static_cast<int64>(timestamp);
48 result->push_back({label, timestamp_int64});
49 }
50 std::sort(result->begin(), result->end(),
51 [](const std::pair<string, int64>& left,
52 const std::pair<string, int64>& right) {
53 return left.second < right.second;
54 });
55 return Status::OK();
56 }
57
CalculateAccuracyStats(const std::vector<std::pair<string,int64>> & ground_truth_list,const std::vector<std::pair<string,int64>> & found_words,int64 up_to_time_ms,int64 time_tolerance_ms,StreamingAccuracyStats * stats)58 void CalculateAccuracyStats(
59 const std::vector<std::pair<string, int64>>& ground_truth_list,
60 const std::vector<std::pair<string, int64>>& found_words,
61 int64 up_to_time_ms, int64 time_tolerance_ms,
62 StreamingAccuracyStats* stats) {
63 int64 latest_possible_time;
64 if (up_to_time_ms == -1) {
65 latest_possible_time = std::numeric_limits<int64>::max();
66 } else {
67 latest_possible_time = up_to_time_ms + time_tolerance_ms;
68 }
69 stats->how_many_ground_truth_words = 0;
70 for (const std::pair<string, int64>& ground_truth : ground_truth_list) {
71 const int64 ground_truth_time = ground_truth.second;
72 if (ground_truth_time > latest_possible_time) {
73 break;
74 }
75 ++stats->how_many_ground_truth_words;
76 }
77
78 stats->how_many_false_positives = 0;
79 stats->how_many_correct_words = 0;
80 stats->how_many_wrong_words = 0;
81 std::unordered_set<int64> has_ground_truth_been_matched;
82 for (const std::pair<string, int64>& found_word : found_words) {
83 const string& found_label = found_word.first;
84 const int64 found_time = found_word.second;
85 const int64 earliest_time = found_time - time_tolerance_ms;
86 const int64 latest_time = found_time + time_tolerance_ms;
87 bool has_match_been_found = false;
88 for (const std::pair<string, int64>& ground_truth : ground_truth_list) {
89 const int64 ground_truth_time = ground_truth.second;
90 if ((ground_truth_time > latest_time) ||
91 (ground_truth_time > latest_possible_time)) {
92 break;
93 }
94 if (ground_truth_time < earliest_time) {
95 continue;
96 }
97 const string& ground_truth_label = ground_truth.first;
98 if ((ground_truth_label == found_label) &&
99 (has_ground_truth_been_matched.count(ground_truth_time) == 0)) {
100 ++stats->how_many_correct_words;
101 } else {
102 ++stats->how_many_wrong_words;
103 }
104 has_ground_truth_been_matched.insert(ground_truth_time);
105 has_match_been_found = true;
106 break;
107 }
108 if (!has_match_been_found) {
109 ++stats->how_many_false_positives;
110 }
111 }
112 stats->how_many_ground_truth_matched = has_ground_truth_been_matched.size();
113 }
114
PrintAccuracyStats(const StreamingAccuracyStats & stats)115 void PrintAccuracyStats(const StreamingAccuracyStats& stats) {
116 if (stats.how_many_ground_truth_words == 0) {
117 LOG(INFO) << "No ground truth yet, " << stats.how_many_false_positives
118 << " false positives";
119 } else {
120 float any_match_percentage =
121 (stats.how_many_ground_truth_matched * 100.0f) /
122 stats.how_many_ground_truth_words;
123 float correct_match_percentage = (stats.how_many_correct_words * 100.0f) /
124 stats.how_many_ground_truth_words;
125 float wrong_match_percentage = (stats.how_many_wrong_words * 100.0f) /
126 stats.how_many_ground_truth_words;
127 float false_positive_percentage =
128 (stats.how_many_false_positives * 100.0f) /
129 stats.how_many_ground_truth_words;
130
131 LOG(INFO) << std::setprecision(1) << std::fixed << any_match_percentage
132 << "% matched, " << correct_match_percentage << "% correctly, "
133 << wrong_match_percentage << "% wrongly, "
134 << false_positive_percentage << "% false positives ";
135 }
136 }
137
138 } // namespace tensorflow
139