python - How to calculate Top N Accuracy Score with predict generator predictions

Question

I calculate the predictions using model.predict_generator() as below, but now I want to find out the top N accuracy using this result. Is there any way to find out the top n accuracy with model.predict_generator results ?

def test_gen(test_path, batch_size, img_r, img_c):
  test_datagen = ImageDataGenerator(rescale=1./255)
  test_generator = test_datagen.flow_from_directory(test_path,
                                                    target_size=(224, 224),
                                                    color_mode="rgb",
                                                    shuffle = False,
                                                    class_mode='categorical',
                                                    batch_size=32)
  filenames = test_generator.filenames
  nb_samples = len(filenames)
  return test_generator, nb_samples
  


def predict_model(model,test_batches, nb_samples): 
  predict = model.predict_generator(test_batches,steps = np.ceil(nb_samples//32), verbose=1)
  return predict
  
  
  
  
if __name__ == '__main__':
  model = keras.models.load_model('./model')
  test_batches, nb_samples = test_gen(dataset_test_path, 32, img_width, img_height)
  predict = predict_model(model,test_batches, nb_samples)

Answer 1

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