Create app.py

app.py

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+import gradio as gr
+from datasets import load_dataset
+import numpy as np
+
+# Load your dataset only once
+ds = load_dataset("Devenarya/Microsoft100", split="train")
+
+# Generator as before
+def get_image_and_mask(index):
+    # This assumes dataset alternates: image, mask, image, mask, ...
+    images = [item['image'] for item in ds]
+    img = images[2 * index].convert('RGB')
+    mask = images[2 * index + 1].convert('L')
+    return np.array(img), np.array(mask)
+
+def demo_fn(index):
+    # Output two images: the photo and its segmentation
+    return get_image_and_mask(index)
+
+demo = gr.Interface(
+    fn=demo_fn,
+    inputs=gr.Slider(0, (len(ds)//2)-1, step=1, label="Image Index"),
+    outputs=[gr.Image(label="Original Image"), gr.Image(label="Segmentation Mask")],
+    title="Microsoft100 Image & Segmentation Explorer"
+)
+
+if __name__ == "__main__":
+    demo.launch()