显示预测错误对应的图片

predict.py

@@ -25,7 +25,7 @@ model.summary()
 model.evaluate(test_images.reshape(-1, 28, 28, 1), test_labels)
 
 # 可视化预测效果
-show_num = 170
+show_num = 200
 testShow = test_labels[:show_num]
 
 pred = model.predict(test_images.reshape(-1, 28, 28, 1))
@@ -33,10 +33,25 @@ predict = []
 for item in pred:
     predict.append(np.argmax(item))
 
+# 显示折线图
 plt.figure()
 plt.title('Conv Predict')
 plt.ylabel('number')
-plt.plot(range(testShow.size), predict[:show_num], marker='^', color='coral',label='predict')
+plt.plot(range(testShow.size), predict[:show_num], marker='^', color='coral', label='predict')
-plt.plot(range(testShow.size), testShow,  marker='o',color='deepskyblue',label='result')
+plt.plot(range(testShow.size), testShow,  marker='o', color='deepskyblue', label='result')
 plt.legend()
+
+# 挑选出预测错误的图片，并显示预测值
+wrongImg = []
+wrongNum = []
+for i in range(testShow.size):
+    if (predict[i] != testShow[i]):
+        wrongImg.append(test_images[i])
+        wrongNum.append(predict[i])
+
+for i in range(len(wrongImg)):
+    plt.figure()
+    plt.title(str(wrongNum[i]))
+    plt.imshow(wrongImg[i])
+
 plt.show()