小编Smu*_*ain的帖子

我尝试使用此代码预测 10 个类

#Predicting the Test set rules
y_pred = model.predict(traindata)
y_pred = np.argmax(y_pred, axis=1) 
y_true = np.argmax(testdata, axis=1) 

target_names = ["akLembut","akMundur","akTajam","caMenaik", "caMenurun", "coretanTengah", "garisAtas", "garisBawah", "garisBawahBanyak", "ttdCangkang"]
print("\n"+ classification_report(y_true, y_pred, target_names=target_names))

但后来我收到了这样的错误消息

AxisError                                 Traceback (most recent call last)
<ipython-input-13-a2b02b251547> in <module>()
      2 y_pred = model.predict(traindata)
      3 y_pred = np.argmax(y_pred, axis=1)
----> 4 y_true = np.argmax(testdata, axis=1)
      5 
      6 target_names = ["akLembut","akMundur","akTajam","caMenaik", "caMenurun", "coretanTengah", "garisAtas", "garisBawah", "garisBawahBanyak", "ttdCangkang"]

<__array_function__ internals> in argmax(*args, **kwargs)

2 frames
/usr/local/lib/python3.6/dist-packages/numpy/core/fromnumeric.py in _wrapit(obj, method, *args, …

我尝试用 100,100,1 绘制图像，但出现这样的错误

TypeError: Invalid shape (100, 100, 1) for image data

这是代码

sample_training_images, _ = next(traindata)
def plotImages(images_arr):
    fig, axes = plt.subplots(1, 5, figsize=(20,20))
    axes = axes.flatten()
    for img, ax in zip( images_arr, axes):
        ax.imshow(img)
        ax.axis('off')
    plt.tight_layout()
    plt.plot(images_arr)
    plt.show()

plotImages(sample_training_images[:5])