Python 无法在tensorflow中成功读取图像
我想将jpeg图像读取到批处理中以进行图像重签名。图像在/Image\u p/文件中,图像名称在label.csv文件中列出,如14634\u right所示 我的问题是如何修复我的代码以成功地将图像读取到批处理中? 更具体地说,我不知道是否应该为循环编写Python 无法在tensorflow中成功读取图像,python,image,machine-learning,tensorflow,computer-vision,Python,Image,Machine Learning,Tensorflow,Computer Vision,我想将jpeg图像读取到批处理中以进行图像重签名。图像在/Image\u p/文件中,图像名称在label.csv文件中列出,如14634\u right所示 我的问题是如何修复我的代码以成功地将图像读取到批处理中? 更具体地说,我不知道是否应该为循环编写,以及在哪里实现它 对于原始代码,我在tf.train.shuffle\u batch()函数上得到了错误消息: ValueError: All shapes must be fully defined: [TensorShape([Dimen
,以及在哪里实现它
对于原始代码,我在tf.train.shuffle\u batch()
函数上得到了错误消息:
ValueError: All shapes must be fully defined: [TensorShape([Dimension(None), Dimension(None), Dimension(3)]), TensorShape([])]
我的来源代码:
# 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,我还编写了一个新文件,可以成功读取图像(感谢martianwars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)
图像
将具有(?,?,3)
形状,因为它尚未被读取,但您已在解码jpeg()函数中指定了通道。试着把这个打印出来
with tf.Session() as sess:
img = sess.run(image)
print(img)
非常感谢你。你能帮我修一下第一个原产地代码吗?坦率地说,我不知道是否应该在哪里编写for循环和tf.train.shuffle\u batch()
。我是ML的初学者,非常感谢!在您完成sess.run(image)
之后,是否可以尝试运行tf.train.shuffle\u batch()
?谢谢!它似乎有效,但在匹配图像和标签=(答案对你@Jeffy有帮助吗?