holiday similarity update

1 files changed, 24 insertions, 0 deletions

diff --git a/cv/holiday_similarity/eval_utils.py b/cv/holiday_similarity/eval_utils.py
new file mode 100644
index 0000000..b83125e
--- /dev/null
+++ b/cv/holiday_similarity/eval_utils.py
@@ -0,0 +1,24 @@
+import numpy as np
+from sklearn.metrics import accuracy_score, confusion_matrix, classification_report
+
+
+def evaluate_model(model, test_gen, test_triples, batch_size):
+    # model_name = os.path.basename(model_file)
+    # model = load_model(model_file)
+    # print("=== Evaluating model: {:s} ===".format(model_name))
+    print("=== Evaluating model")
+    ytrue, ypred = [], []
+    num_test_steps = len(test_triples) // batch_size
+    for i in range(num_test_steps):
+        # (X1, X2), Y = test_gen.next()
+        (X1, X2), Y = next(test_gen)
+        Y_ = model.predict([X1, X2])
+        ytrue.extend(np.argmax(Y, axis=1).tolist())
+        ypred.extend(np.argmax(Y_, axis=1).tolist())
+    accuracy = accuracy_score(ytrue, ypred)
+    print("\nAccuracy: {:.3f}".format(accuracy))
+    print("\nConfusion Matrix")
+    print(confusion_matrix(ytrue, ypred))
+    print("\nClassification Report")
+    print(classification_report(ytrue, ypred))
+    return accuracy