app.py

import os
from pathlib import Path
import subprocess
import gradio as gr
from PIL import Image
import io

# Fixed input paths and output location
FRAME1_PATH = "demo/frame1.png"
FRAME2_PATH = "demo/frame2.png"
OUTPUT_GIF = "/tmp/output.gif"

def generate_demo_gif(exp=2, progress=gr.Progress(track_tqdm=True)):
    progress(0.1, desc="Starting inference...")

    # Delete old output if exists
    try:
        os.remove(OUTPUT_GIF)
    except FileNotFoundError:
        pass

    # Build and run command
    cmd = [
        "python", "inference_img.py",
        "--img", FRAME1_PATH, FRAME2_PATH,
        "--exp", str(exp),
        "--model", "train_log/"
    ]
    print("Running:", " ".join(cmd))
    result = subprocess.run(cmd, capture_output=True, text=True)

    print("STDOUT:", result.stdout)
    print("STDERR:", result.stderr)

    # Check and display result
    if result.returncode == 0 and os.path.exists(OUTPUT_GIF):
        with open(OUTPUT_GIF, "rb") as f:
            gif = Image.open(io.BytesIO(f.read()))
        progress(1.0, desc="GIF created!")
        return gif, "✅ Done!"
    else:
        return None, "❌ Inference failed or output missing"

# UI setup
with gr.Blocks() as demo_ui:
    gr.Markdown("## 🎞️ Demo GIF Generator — Interpolate Two Frames")

    with gr.Row():
        gr.Image(value=FRAME1_PATH, label="Frame 1", interactive=False)
        gr.Image(value=FRAME2_PATH, label="Frame 2", interactive=False)

    exp = gr.Slider(1, 4, value=2, step=1, label="Interpolation Exponent")
    run_btn = gr.Button("Generate GIF")
    out_gif = gr.Image(label="Output GIF")
    status = gr.Markdown()

    run_btn.click(fn=generate_demo_gif, inputs=[exp], outputs=[out_gif, status])

# Launch the app
demo_ui.launch()