app.py

# app.py
import gradio as gr
from datasets import load_dataset

# Load an image dataset (e.g., cifar10)
dataset = load_dataset("cifar10", split="test", trust_remote_code=True)

def get_image(index):
    index = int(index)
    # Get the image and its label
    sample = dataset[index]
    image = sample["img"] # Note: Some datasets use "image", "img", or "pixel_values"
    label = sample["label"]
    # CIFAR10 has a list of label names
    label_names = ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']
    return image, label_names[label]

with gr.Blocks() as demo:
    gr.Markdown("# 🖼️ Image Dataset Viewer")
    index_slider = gr.Slider(0, len(dataset)-1, value=0, step=1, label="Sample Index")
    image_output = gr.Image(label="Image", type="pil") # Use 'pil' for PIL Images from datasets
    label_output = gr.Label(label="Class")

    index_slider.change(fn=get_image,
                        inputs=index_slider,
                        outputs=[image_output, label_output])

demo.launch()