app.py

import json
import os
import time
import random


import gradio as gr
import numpy as np
import requests

from PIL import Image

print ("1")
URL = "http://0.0.0.0:8188/prompt"
INPUT_DIR = "input"
OUTPUT_DIR = "output"

cached_seed = 0

def get_latest_image(folder):
    files = os.listdir(folder)
    image_files = [f for f in files if f.lower().endswith(('.png', '.jpg', '.jpeg'))]
    image_files.sort(key=lambda x: os.path.getmtime(os.path.join(folder, x)))
    latest_image = os.path.join(folder, image_files[-1]) if image_files else None
    return latest_image

print ("2")

def start_queue(prompt_workflow):
    p = {"prompt": prompt_workflow}
    data = json.dumps(p).encode('utf-8')
    requests.post(URL, data=data)

print ("3")

def generate_image(input_image):   
    with open("workflow.json", "r") as file_json:
        prompt = json.load(file_json)
    print ("4")

    prompt["3"]["inputs"]["seed"] = random.randint(1, 1500000)
    global cached_seed
    if cached_seed == prompt["3"]["inputs"]["seed"]:
        return get_latest_image(OUTPUT_DIR)
    cached_seed = prompt["3"]["inputs"]["seed"]
    print ("5")
    
    image = Image.fromarray(input_image)
    min_side = min(image.size)
    scale_factor = 512 / min_side
    new_size = (round(image.size[0] * scale_factor), round(image.size[1] * scale_factor))
    resized_image = image.resize(new_size)
    print ("6")

    resized_image.save(os.path.join(INPUT_DIR, "test_api.jpg"))

    previous_image = get_latest_image(OUTPUT_DIR)
    
    start_queue(prompt)
    print ("7")

    while True:
        print ("8")
        
        latest_image = get_latest_image(OUTPUT_DIR)
        if latest_image != previous_image:
            return latest_image
        print ("9")

        time.sleep(1)

demo = gr.Interface(fn=generate_image, inputs=["image"], outputs=["image"])
demo.launch(share=True)
print ("10")