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Dataset card for SVHN
The Street View House Numbers (SVHN) dataset is a real-world image dataset developed and designed for machine learning and object recognition algorithms, and is characterized by low data preprocessing and formatting requirements. Similar to MNIST, SVHN contains images of small cropped numbers, but in terms of labeled data, SVHN is an order of magnitude larger than MNIST, comprising over 600,000 digital images. Unlike MNIST, SVHN deals with a much more challenging and unsolved real-world problem - recognizing numbers and strings of numbers in natural scene images. The dataset is derived from house numbers captured in Google Street View images.
Usage
By API
from datasets import load_dataset
ds = load_dataset(
"Genius-Society/svhn",
name="default",
split="train",
cache_dir="./__pycache__",
)
for i in ds:
print(i)
Not By API
import os
import zipfile
import requests
def download_file(url, save_path):
response = requests.get(url, stream=True)
with open(save_path, 'wb') as file:
for chunk in response.iter_content(chunk_size=1024):
if chunk:
file.write(chunk)
def unzip(zip_file_path, extract_to):
with zipfile.ZipFile(zip_file_path, 'r') as zip_ref:
for member in zip_ref.infolist():
zip_ref.extract(member, extract_to)
if not os.path.exists('./data.zip'):
download_file(
'https://www.modelscope.cn/datasets/Genius-Society/svhn/resolve/master/data/svhn.zip',
'data.zip'
)
if not os.path.exists('./data'):
unzip('data.zip', './')
Maintenance
GIT_LFS_SKIP_SMUDGE=1 git clone git@hf.co:datasets/Genius-Society/svhn
cd svhn
Mirror
https://www.modelscope.cn/datasets/Genius-Society/svhn
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