loop.py

evaluator = Evaluator()
x = preprocess_img(base_path)
z = load_img(base_path,target_size=(img_nrows,img_ncols))
imsave('iteration_original.png',z)
print "Saving original image.."

for i in range(EPOCHS):
    print "Start iteration: %d" % i
    start_time = time.time()
    x,min_val,info = fmin_l_bfgs_b(evaluator.loss,x.flatten(),fprime=evaluator.grads,maxfun=20)
    print "Loss: %s" % str(min_val)
    img = deprocess_img(x.copy())
    fname = "iteration_%d.png" % i
    imsave(fname,img)
    print "Time taken: %s" % str(time.time()-start_time)