我在 Google Colab 中使用 Jupiter Notebook。我的训练数据集如下所示:
/data/label1/img1.jpeg
.
.
.
/data/label2/img90.jpeg
我想导入这样的数据集。我尝试过的事情
步骤1:
!pip install -U -q PyDrive
%matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
from os import walk
import os
from pydrive.auth import GoogleAuth
from pydrive.drive import GoogleDrive
from google.colab import auth
from oauth2client.client import GoogleCredentials
第2步:
# 1. Authenticate and create the PyDrive client.
auth.authenticate_user()
gauth = GoogleAuth()
gauth.credentials = GoogleCredentials.get_application_default()
drive = GoogleDrive(gauth)
步骤3
file_to_download = os.path.expanduser('./data/')
file_list = drive.ListFile(
{'q': 'id_of_the_data_directory'})
不确定下一步如何进行。文件夹
data
是驱动器中我的协作笔记本文件夹。我想阅读图像和标签。要做同样的事情,我使用代码:
filename_queue=tf.train.string_input_producer(tf.train.match_filenames_once('data/*/*.jpeg'))
image_reader=tf.WholeFileReader()
key,image_file=image_reader.read(filename_queue)
#key is the entire path to the jpeg file and we need only the subfolder as the label
S = tf.string_split([key],'\/')
length = tf.cast(S.dense_shape[1],tf.int32)
label = S.values[length-tf.constant(2,dtype=tf.int32)]
label = tf.string_to_number(label,out_type=tf.int32)
#decode the image
image=tf.image.decode_jpeg(image_file)
#then code to place labels and folders in corresponding arrays