Keras CNN 训练数据（三）：预测

预测代码如下所示：

from keras.models import load_model  #加载模型
import matplotlib.image as processimage  #预处理图片库
import matplotlib.pyplot as plt
import numpy as np
from PIL import Image

class Prediction(object):
    #初始化函数
    def __init__(self, ModuleFile, PredictFile, DogType, Width=100, Height=100):
        self.ModuleFile = ModuleFile
        self.PredictFile = PredictFile
        self.DogType = DogType
        self.Width = Width
        self.Height = Height
        
    #预测
    def Predict(self):
        #引入model
        model = load_model(self.ModuleFile)
        
        #处理照片格式和尺寸
        img_open = Image.open(self.PredictFile)
        conv_RGB = img_open.convert('RGB')
        new_img = conv_RGB.resize((self.Width, self.Height), Image.BILINEAR)
        new_img.save(self.PredictFile)
        
        #处理图片shape
        image = processimage.imread(self.PredictFile)
        image_to_array = np.array(image)/255.0
        image_to_array = image_to_array.reshape(-1,100,100,3)
        print('Image reshaped')
        
        #预测照片
        prediction = model.predict(image_to_array)
        Fine_Pred = [result.argmax() for result in prediction][0]
        print(prediction)
        
    #概率读取
        count = 0
        for i in prediction[0]:
            percent = '%.2f%%' % (i*100)
            print(self.DogType[count], '', percent)
            count += 1
        
DogType = ['哈士奇','德国牧羊犬']
# 实例化类
Pred = Prediction(PredictFile='Pred_img/1.jpg',
                  ModuleFile='dogfinder.h5',
                  DogType = DogType)
Pred.Predict()

运行结果如下：