| import os |
| import datasets |
| import urllib.request |
| import csv |
|
|
| _CITATION = """\ |
| @InProceedings{huggingface:dataset, |
| title = {diffusion train set}, |
| } |
| """ |
|
|
| _DESCRIPTION = """\ |
| This is a dataset that image data and caption txt |
| """ |
| _HOMEPAGE = "" |
|
|
| _LICENSE = "" |
|
|
| _URL = "./" |
|
|
| _URLS = { |
| "train": "/content/drive/MyDrive/", |
| "reg": "/content/drive/MyDrive/", |
| } |
|
|
|
|
| train = open("/content/drive/MyDrive/train_dataset.csv", "r") |
| train_reader = csv.DictReader(train) |
| |
| |
| for row in train_reader: |
| class_name = f"{row['Class_name']}" |
| file_name = f"{row['file_name']}" |
| url = f"{row['file_id']}" |
| path = os.path.join('./img',class_name,file_name) |
| folder = os.path.join('./img',class_name) |
| if not os.path.isdir(folder): |
| os.makedirs(folder) |
| urllib.request.urlretrieve(url, path) |
|
|
| reg = open("/content/drive/MyDrive/reg_dataset.csv", "r") |
| reg_reader = csv.DictReader(reg) |
| |
| |
| for row in reg_reader: |
| class_name = f"{row['Class_name']}" |
| file_name = f"{row['file_name']}" |
| url = f"{row['file_id']}" |
| path = os.path.join('./reg',class_name,file_name) |
| folder = os.path.join('./reg',class_name) |
| if not os.path.isdir(folder): |
| os.makedirs(folder) |
| urllib.request.urlretrieve(url, path) |
