[딥러닝] 사용자 데이터로 CNN 학습하기- 6. 시험 데이터로 확인해보기

 

6. 시험 데이터로 확인해보기

 

_04_cnn_training_5.py

from _04_cnn_training_3 import *

from tensorflow.keras.models import load_model
import matplotlib.pyplot as plt

model1=load_model('model.h5')

# Model predictions for the testing dataset
y_test_predict=model1.predict(x_test)
print(y_test_predict.shape, y_test_predict[0])
y_test_predict=np.argmax(x_test_predict, axis=1)
print(y_test_predict.shape, y_test_predict[0])

# Name list
names=['_0_forward', '_1_right', '_2_left', '_3_stop']

# Display true labels and predictions
fig=plt.figure(figsize=(18,18))
for i, idx in enumerate(np.random.choice(\
        x_test.shape[0], size=16, replace=False)):
    ax=fig.add_subplot(4,4,i+1,xticks=[], yticks=[])
    ax.imshow(np.squeeze(x_test[idx]))
    pred_idx=y_test_predict[idx]
    true_idx=np.argmax(y_test[idx])
    ax.set_title("{} ({})".format(names[pred_idx], names[true_idx]),
        color=("#4876ff" if pred_idx == true_idx else "darkred"))
plt.show()