Merge branch 'master' of skozl.com:e4-pattern

1 files changed, 4 insertions, 4 deletions

diff --git a/evaluate.py b/evaluate.py
index 251e952..54a6a9d 100755
--- a/evaluate.py
+++ b/evaluate.py
@@ -42,7 +42,7 @@ parser.add_argument("-k", "--kmean", help="Perform Kmeans", action='store_true',
 parser.add_argument("-m", "--mahalanobis", help="Perform Mahalanobis Distance metric", action='store_true', default=0)
 parser.add_argument("-e", "--euclidean", help="Standard euclidean", action='store_true', default=0)
 parser.add_argument("-r", "--rerank", help="Use k-reciprocal rernaking", action='store_true')
-parser.add_argument("-p", "--reranka", help="Parameter 1 for Rerank", type=int, default = 11)
+parser.add_argument("-p", "--reranka", help="Parameter 1 for Rerank", type=int, default = 9)
 parser.add_argument("-q", "--rerankb", help="Parameter 2 for rerank", type=int, default = 3)
 parser.add_argument("-l", "--rerankl", help="Coefficient to combine distances", type=float, default = 0.3)
 parser.add_argument("-n", "--neighbors", help="Number of neighbors", type=int, default = 1)
@@ -250,9 +250,9 @@ def main():
         plt.plot(test_table[:(args.multrank)], 100*accuracy[0])
         if(args.comparison!=1):
             plt.plot(test_table[:(args.multrank)], 100*accuracy[1])
-            plt.legend(['Baseline kNN', 'Improved metric'], loc='upper left')
-        plt.xlabel('k rank')
-        plt.ylabel('Recognition Accuracy (%)')
+            plt.legend(['Baseline NN', 'NN+Reranking'], loc='upper left')
+        plt.xlabel('Top k')
+        plt.ylabel('Identification Accuracy (%)')
         plt.grid(True)
         plt.show()