app.py

import gradio as gr
import json, os, sys, glob, shutil, subprocess
from PIL import Image

if not os.path.isdir('/tmp/HorizonNet'):
    os.system("git clone https://github.com/sunset1995/HorizonNet.git /tmp/HorizonNet")
sys.path.insert(0, "/tmp/HorizonNet")

from huggingface_hub import hf_hub_download

CKPT = hf_hub_download(repo_id="gum-tech/horizonnet-resnet50-rnn", filename="resnet50_rnn__st3d.pth")
print("Model checkpoint at:", CKPT)

def run(cmd, cwd="/tmp/HorizonNet"):
    result = subprocess.run(
        cmd, cwd=cwd, shell=False,
        stdout=subprocess.PIPE, stderr=subprocess.STDOUT
    )
    log = result.stdout.decode("utf-8", errors="replace")
    print(f"=== {cmd[0]} (exit {result.returncode}) ===\n{log}\n===")
    return result.returncode, log

def predict(image):
    try:
        for d in ["/tmp/hn_input", "/tmp/hn_pre", "/tmp/hn_out"]:
            shutil.rmtree(d, ignore_errors=True)
            os.makedirs(d)

        img_path = "/tmp/hn_input/room.png"
        image.convert("RGB").resize((1024, 512)).save(img_path)
        print("Image saved to", img_path)

        # Step 1: preprocess
        code, log = run([
            "python", "preprocess.py",
            "--img_glob", img_path,
            "--output_dir", "/tmp/hn_pre"
        ])

        aligned = glob.glob("/tmp/hn_pre/*_aligned_rgb.png")
        if not aligned:
            return json.dumps({"error": "Preprocessing failed", "code": code, "log": log[-1000:]})

        aligned_path = aligned[0]
        print("Aligned image:", aligned_path)

        # Step 2: inference
        code, log = run([
            "python", "inference.py",
            "--pth", CKPT,
            "--img_glob", aligned_path,
            "--output_dir", "/tmp/hn_out",
            "--no_cuda"
        ])

        out_jsons = glob.glob("/tmp/hn_out/*.json")
        if not out_jsons:
            return json.dumps({"error": "Inference failed", "code": code, "log": log[-1000:]})

        with open(out_jsons[0]) as f:
            result = json.load(f)

        print("Result:", result)
        return json.dumps(result)

    except Exception as e:
        import traceback
        tb = traceback.format_exc()
        print("=== EXCEPTION ===\n", tb)
        return json.dumps({"error": str(e), "traceback": tb})

demo = gr.Interface(
    fn=predict,
    inputs=gr.Image(type="pil"),
    outputs=gr.Text(),
    title="HorizonNet API",
    description="Upload an equirectangular panorama to extract room layout corners."
)

demo.launch()