added validation score after prediction

classifier.py

@@ -66,12 +66,25 @@ history = model.fit(train_generator, batch_size=32,
                     epochs=30, validation_data=valid_generator)
                     
 
-img = preprocessing.image.load_img("data/seg_test/buildings/20057.jpg")
-img_arr = preprocessing.image.img_to_array(img)
-img_arr = tf.expand_dims(img_arr, 0)
-true_labels = valid_generator.classeds
-predictions = model.predict(img_arr)
-
-
-y_pred = np.array([np.argmax(x) for x in predictions])
-print(y_pred)
+t_generator = train_datagen.flow_from_directory(
+    "../input/intel-image-classification/seg_test/seg_test", subset="validation", shuffle=False, **dataflow_kwargs)
+q = 0
+right = 0.0
+total = 0.0
+
+for q in t_generator:
+    x,y=q
+
+    z = model.predict(x, verbose=False)
+    
+    for i in z:
+        total +=1.0
+        if np.argmax(y) == np.argmax(i):
+            right+=1.0
+    if (total % 100) == 0:
+        correct = (right/total) * 100
+        print(f"{correct}%")
+    if total == 598:
+        breaK
+correct = (right/total) * 100
+print(f"Final validation: {correct}%")