NiftyNet 數據預處理

NiftyNet項目介紹

使用NiftyNet時，咱們須要先將圖像數據和標籤進行一次簡單的處理，獲得對應的.csv文件。
對應文件格式爲：
img.csv

image	path
img_name	img_path

label.csv

label	path
img_label	img_path

在此給出一個二分類的生成該文件的demo。首先，已經將兩個類別的圖片分別存儲在兩個文件夾中
demo

import pandas as pd
import os


# 生成 img.csv
list_img = []
list_path = []

img_path = 'C:\\Users\\fan\\Desktop\\demo\\train\\ad'
img_name = os.listdir(img_path)

for i, item in enumerate(img_name):
    list_img.append(item)
    list_path.append(img_path + "\\" + item)

img_path = "C:\\Users\\fan\\Desktop\\demo\\train\\cn"
img_name = os.listdir(img_path)
for i, item in enumerate(img_name):
    list_img.append(item)
    list_path.append(img_path + "\\" + item)

data_frame = pd.DataFrame({'image': list_img, 'path': list_path})
data_frame.to_csv('C:\\Users\\fan\\Desktop\\demo\\train\\img_path.csv', index=False)

# 生成label.csv

list_label_name = []
list_label_path = []

label_path = 'C:\\Users\\fan\\Desktop\\demo\\train\\ad'
label_name = os.listdir(label_path)

for j, elem in enumerate(label_name):
    list_label_name.append(elem[0:2])
    list_label_path.append(label_path + '\\' + elem)

label_path = 'C:\\Users\\fan\\Desktop\\demo\\train\\cn'
label_name = os.listdir(label_path)

for j, elem in enumerate(label_name):
    list_label_name.append(elem[0:2])
    list_label_path.append(label_path + '\\' + elem)
print(list_label_name)

label_dataframe = pd.DataFrame({'label': list_label_name, 'path': list_label_path})
label_dataframe.to_csv('C:\\Users\\fan\\Desktop\\demo\\train\\label.csv', index=False)

NiftyNet平臺配置介紹