v3

test.py

@@ -0,0 +1,34 @@
+import prepare
+import keras
+import pickle
+import numpy as np
+
+mxlen = 32
+
+token_file = open('tokenizer', 'rb')
+prepare.tokenizer = pickle.load(token_file)
+
+train_json = 'nlvr\\train\\train.json'
+train_img_folder = 'nlvr\\train\\images'
+test_json = 'nlvr\\test\\test.json'
+test_img_folder = 'nlvr\\test\\images'
+
+data = prepare.load_data(train_json)
+data = prepare.tokenize_data(data, mxlen)
+imgs, ws, labels = prepare.load_images(train_img_folder, data)
+data.clear()
+
+model = keras.models.load_model('model')
+
+
+test_data = prepare.load_data(test_json)
+test_data = prepare.tokenize_data(test_data, mxlen)
+test_imgs, test_ws, test_labels = prepare.load_images(test_img_folder, test_data)
+test_data.clear()
+
+imgs_mean = np.mean(imgs)
+imgs_std = np.std(imgs - imgs_mean)
+
+test_imgs = (test_imgs - imgs_mean) / imgs_std
+
+print(model.evaluate([test_imgs, test_ws], test_labels, batch_size=128))