run_FCN.py 文件源码

def predict_batch_test_images (model, batch_size = 1, max_image = 50):
    #
    #   DESCRIPTION 
    #       Generator function batching each of the 32 mapped image from one test image 
    #       Once the image have been loaded they are predicted using the specified Keras Model 
    #       Once predicted the generator finally yields the batch to be treated in a for loop in predict_and_rebuild
    #       
    #   INPUTS 
    #       model keras model 
    #       batch_size set to 1 
    #       max_image the max number of image loaded (50 test set)
    #
    #   OUTPUTS
    #       yield predictions a np.array of [:, 400, 400, 1]
    #
    images = np.zeros(shape=[8*4, 400, 400, 3], dtype=float) 

    for i in range(1,max_image+1):
        count = 0
        for rota_count in range(8):
            for patch_count in range(4):
                images[count, :,:,:] = mpimg.imread('test_set_images/test_'+str(i)+'/Test_'+str(i)+'_rota'+str(rota_count)+'_patch'+str(patch_count)+'.png')
                count += 1

        if (count == 32):
            preds = model.predict(images, batch_size = batch_size, verbose=1)
            yield preds