app.py

import gradio as gr
import tempfile
from pathlib import Path
from wrapper import run_pipeline_on_image

def process(image):
    if image is None:
        return []
    with tempfile.TemporaryDirectory() as tmpdir:
        # Save PIL image to temp file
        img_path = Path(tmpdir) / "input.png"
        image.save(img_path)
        outputs = run_pipeline_on_image(str(img_path), tmpdir, save_artifacts=True)
        # Keep order consistent: return exactly the 7 images
        order = [
            'NDVI', 'ARI', 'GNDVI', 'LBP', 'HOG', 'Lacunarity', 'SizeAnalysis'
        ]
        return [outputs[k] for k in order if k in outputs]

with gr.Blocks() as demo:
    gr.Markdown("# 🌿 Sorghum Single-Image Demo")
    inp = gr.Image(type="pil", label="Upload Image")
    run = gr.Button("Run Pipeline", variant="primary")
    gallery = gr.Gallery(label="Outputs")
    run.click(process, inputs=inp, outputs=gallery)

if __name__ == "__main__":
    demo.launch()