merge

mini_proj/waldo_model.py

@@ -53,6 +53,22 @@ def FCN():
 
     return model
 
+def precision(y_true, y_pred):
+    y_pred = np.round(y_pred)
+    num = np.sum(np.logical_and(y_true, y_pred))
+    den = np.sum(y_pred)
+    return np.divide(num, den)
+
+def recall(y_true, y_pred):
+    y_pred = np.round(y_pred)
+    num = np.sum(np.logical_and(y_true, y_pred))
+    den = np.sum(y_true)
+    return np.divide(num, den)
+
+def f_measure(y_true, y_pred):
+    p = precision(y_true, y_pred)
+    r = recall(y_true, y_pred)
+    return 2 * p * r / (p + r)
 
 ## Open data
 im_train = np.load('Waldo_train_data.npy')
@@ -131,4 +147,3 @@ accuracy = accuracy_score(lbl_test, pred_lbl)
 print("Accuracy: " + str(accuracy))
 print("Images generated in {} seconds".format(end - start))
 np.save('predicted_results.npy', pred_lbl)
-