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from pathlib import Path
import os
import gradio as gr
from gradio.components.gallery import GalleryImageType
import datasets
from datasets import load_dataset
from huggingface_hub import HfApi, HfFileSystem, login
from dotenv import load_dotenv
load_dotenv()
HF_TOKEN = os.getenv('HF_TOKEN')
login(token=HF_TOKEN, add_to_git_credential=True)
def stream_dataset_from_hub(split):
dataset = load_dataset_builder('mcarthuradal/arm-unicef')
data = dataset.as_streaming_dataset(split).iter(200)
yield next(data)
stream = stream_dataset_from_hub('train')
def get_images(split: str):
n = 50
batch = stream['image'][:n]
return batch
iface = gr.Interface(fn=get_images,
inputs='text',
outputs='gallery',
title='Aerial Images Gallery',
description='A gallery of the train and test data to be used without annotations',
analytics_enabled=False,
allow_flagging='never', )
gr.Gallery(columns=5,
rows=10,
min_width=500,
allow_preview=True,
show_download_button=False,
show_share_button=False)
iface.launch(debug=True)
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