1

我正在尝试用它们的概率值打印出所有已知的类。第一个值是概率最高的类别。

到目前为止，这是我的代码：

from keras.applications.vgg16 import VGG16
from keras.preprocessing.image import load_img
from keras.preprocessing.image import img_to_array
from keras.applications.vgg16 import preprocess_input
from keras.applications.vgg16 import decode_predictions

model = VGG16()

print(model.summary())


# load an image from file
image = load_img('./pictures/door.jpg', target_size=(224, 224))
image = img_to_array(image)  #output Numpy-array

#4-dimensional: samples, rows, columns, and channels.
image = image.reshape((1, image.shape[0], image.shape[1], image.shape[2]))


# prepare the image for the VGG model. 
image = preprocess_input(image)


# predict the probability across all output classes. 
yhat = model.predict(image)


# convert the probabilities to class labels
label = decode_predictions(yhat)
# retrieve the most likely result, e.g. highest probability
for i in range(0,5):
    label = label[i][i]
    print('%s (%.2f%%)' % (label[1], label[2] * 100))

我收到以下错误：

Traceback (most recent call last):
  File path, line 38, in <module>
    print('%s (%.2f%%)' % (label[1], label[2] * 100))
IndexError: string index out of range

你知道如何处理它吗？提前谢谢^^

4

1 回答 1

3

您的代码中有错误。试试这个：

labels = decode_predictions(yhat)[0]
# retrieve the most likely result, e.g. highest probability
for i in range(0,5):
    label = labels[i]
    #print('%s (%.2f%%)' % (label[1], label[2] * 100)) 
    print('%s (%.2f%%)' % (label[1], float(label[2]) * 100))
于 2017-11-23T10:18:44.027 回答