title: How to interpret keras " predict_generator " output?
body: <p>I am implementing image classification project .I have generated model and saved it . It was successfully trained . When i use predict_generator in keras to classify the test images then for each image i am getting multiple rows for each image in prediction numpy array.</p>
  
  <p>Prediction Code :</p>
  
  <pre><code>from keras.models import load_model
  from keras.preprocessing.image import ImageDataGenerator
  from keras.preprocessing.image import img_to_array, load_img
  import numpy as np
  
  # dimensions of our images.
  img_width, img_height = 150, 150
  batch_size = 16
  
  test_model = load_model('first_try1.h5')
  
  
  img = load_img('data/train/dogs/dog.2.jpg',False,target_size=(img_width,img_height))
  
  validation_data_dir="test1"
  
  test_datagen = ImageDataGenerator(rescale=1. / 255)
  validation_generator = test_datagen.flow_from_directory(
      validation_data_dir,
      target_size=(img_width, img_height),
      batch_size=batch_size,
      class_mode='binary')
  print(len(validation_generator.filenames))
  predictions=test_model.predict_generator(validation_generator,len(validation_generator.filenames));
  #print(predictions)
  </code></pre>
  
  <p>Output :</p>
  
  <pre><code>Found 5 images belonging to 1 classes.
  5
  [[ 0.0626688 ]
   [ 0.07796276]
   [ 0.46529126]
   [ 0.28495458]
   [ 0.07343803]
   [ 0.07343803]
   [ 0.0626688 ]
   [ 0.46529126]
   [ 0.28495458]
   [ 0.07796276]
   [ 0.0626688 ]
   [ 0.28495458]
   [ 0.07796276]
   [ 0.46529126]
   [ 0.07343803]
   [ 0.07796276]
   [ 0.46529126]
   [ 0.0626688 ]
   [ 0.07343803]
   [ 0.28495458]
   [ 0.0626688 ]
   [ 0.07796276]
   [ 0.46529126]
   [ 0.07343803]
   [ 0.28495458]]
  </code></pre>