我想将jpeg图像读入批处理以进行图像识别。图像位于/ Image_p /文件中,图像名称列在label.csv文件中,其显示方式类似于14634_right。
我的问题是如何修复我的代码以便成功读取图片?
为了更具体,我不知道是否应该编写for
循环以及在何处实现它。
对于原始代码,我在tf.train.shuffle_batch()
函数
ValueError: All shapes must be fully defined: [TensorShape([Dimension(None), Dimension(None), Dimension(3)]), TensorShape([])]
我的原始代码:
# filepath
csv_filepath = r'C:\Users\Jeffy\OneDrive\Course\NMDA\retinaProject\label.csv'
# image parameter
pic_num = 100
pic_height = 64
pic_width = 64
batch_size = 10
# =============================================================================
# import library
import tensorflow as tf
import numpy as np
# =============================================================================
# read csv data
csv = np.loadtxt(open(csv_filepath,"rb"), delimiter=",", dtype='str')
pic_filename = ["" for x in range(pic_num)]
for i in range(pic_num):
pic_filename[i] = eval(csv[i,0]).decode("utf-8") +'.jpeg'
# read the data into batch
for i in range(pic_num):
# read and decode the image
image_contents = tf.read_file('Image_p/' + eval(csv[i,0]).decode("utf-8") +'.jpeg')
image = tf.image.decode_jpeg(image_contents, channels=3)
image = tf.to_float(image)
# Generate batch
batch = tf.train.shuffle_batch([image, float(eval(csv[i,1]))],
batch_size = batch_size,
num_threads = 1,
capacity = batch_size * 100,
min_after_dequeue = batch_size * 10)
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(coord=coord)
image_tensor = sess.run([batch])
print(batch)
coord.request_stop()
coord.join(threads)
另外,我还写了一个可以成功读取图像的新文件(感谢来自火星人的帮助)。 我的测试代码:
import tensorflow as tf
# read and decode the image
image_contents = tf.read_file('Image_p/11247_left.jpeg')
image = tf.image.decode_jpeg(image_contents, channels=3)
with tf.Session() as sess:
img = sess.run(image)
print(img)
答案 0 :(得分:1)
image
将具有(?, ?, 3)
形状,因为它尚未被读取,但您已在decode_jpeg()
函数中指定了该频道。请尝试打印,
with tf.Session() as sess:
img = sess.run(image)
print(img)