小编Ami*_*mit的帖子

``我正在尝试使用TensorFlow中的图像数据增强方法，例如旋转，随机亮度，随机饱和度等各种方法。我观察到的是tf.image.random_brightness的输出不一致-有时会产生负值。我了解随机性，但是产生负值是否正确？当我尝试使用matplotlib.pyplot绘制图像时，它无法显示ValueError：浮点图像RGB值必须在0..1范围内。下面是一些代码示例：'

# Function which reads file and converts to image array
def read_images_from_file (input_queue):
    label = input_queue[1]

    file_content = tf.read_file(input_queue[0])
    image = tf.image.decode_jpeg(file_content, channels=NUM_CHANNELS)
    image = tf.image.convert_image_dtype(image, dtype=tf.float32, saturate=True)
    image = tf.image.resize_images(image, [IMAGE_HEIGHT, IMAGE_WIDTH])

.....
    #inside a function which applies various augmentations - code shown only for brightness

    X_init = tf.placeholder(tf.float32, shape=images.shape)
    X = tf.Variable(X_init)

    sess.run(tf.variables_initializer([X]), feed_dict={X_init: images})
    aug_images, aug_labels = (sess.run(tf.map_fn(lambda params: (tf.image.random_brightness(params[0], 0.8, 1), params[1]), (X, labels))))

    #inside a loop after calling above function - output of function …