def process_images(label_file, one_hot=False, num_classes=10):
if file.getFileName(label_file) == 'train.txt':
images = numpy.empty((60000, 784))
labels = numpy.empty(60000)
if file.getFileName(label_file) == 'test.txt':
images = numpy.empty((10000, 784))
labels = numpy.empty(10000)
lines = readLines(label_file)
label_record = map(lines)
file_name_length = len(file.getFileName(label_file))
image_dir = label_file[:-1 * file_name_length]
print len(label_record)
index = 0
for name in label_record:
# print label_record[name]
image = Image.open(image_dir + str(label_record[name]) + '/' + name)
print "processing %d: " % index + image_dir + str(
label_record[name]) + '/' + name
img_ndarray = numpy.asarray(image, dtype='float32')
images[index] = numpy.ndarray.flatten(img_ndarray)
labels[index] = numpy.int(label_record[name])
index = index + 1
print index
num_images = index
rows = 28
cols = 28
# print train_images.reshape(num_images, rows, cols, 1)numpy.fromarrays(train_labels,)
# print numpy.array(train_labels, dtype=numpy.uint8)
if one_hot:
return images.reshape(num_images, rows, cols, 1), dense_to_one_hot(
numpy.array(labels, dtype=numpy.uint8), num_classes)
return images.reshape(num_images, rows, cols,
1), numpy.array(labels, dtype=numpy.uint8)
def recordsCreater(label_file, dst_records):
writer = tf.python_io.TFRecordWriter(dst_records)
lines = readLines(label_file)
label_record = map(lines)
file_name_length = len(file.getFileName(label_file))
images_dir = label_file[:-1 * file_name_length]
index = 0
for name in label_record:
index = index + 1
image_file = images_dir + str(label_record[name]) + '/' + name
img = Image.open(image_file)
img = img.resize((imageSZ['rows'], imageSZ['cols']))
bytesImg = img.tobytes()
example = tf.train.Example(features=tf.train.Features(
feature={
"label":
tf.train.Feature(int64_list=tf.train.Int64List(
value=[int(label_record[name])])),
'bytesImg':
tf.train.Feature(bytes_list=tf.train.BytesList(
value=[bytesImg]))
}))
if index % 100 == 0:
print("processing %d:" % index + images_dir + name)
writer.write(example.SerializeToString())
print("done!")
writer.close()
import utils.fileUtil as file label_file = "./MNIST_data/mnist_train/train.txt" lenth = file.getFileName(label_file) print len(lenth) print label_file[:-1 * len(lenth)]