import gradio as gr import numpy as np import random import multiprocessing import subprocess import sys import time import signal import json import os import requests from loguru import logger from decouple import config from pathlib import Path from PIL import Image import io URL="http://127.0.0.1" OUTPUT_DIR="Backend/output" INPUT_DIR="Backend/input" BACKEND_PATH="Backend/main.py" import torch import spaces print(f"Is CUDA available: {torch.cuda.is_available()}") print(f"CUDA device: {torch.cuda.get_device_name(torch.cuda.current_device())}") print(torch.version.cuda) device = torch.cuda.get_device_name(torch.cuda.current_device()) print(device) def read_prompt_from_file(filename): with open(filename, 'r', encoding='utf-8') as file: return json.load(file) def wait_for_image_with_prefix(folder, prefix): def is_file_ready(file_path): initial_size = os.path.getsize(file_path) time.sleep(1) return initial_size == os.path.getsize(file_path) files = os.listdir(folder) image_files = [f for f in files if f.lower().startswith(prefix.lower()) and f.lower().endswith(('.png', '.jpg', '.jpeg'))] if image_files: # Sort by modification time to get the latest file image_files.sort(key=lambda x: os.path.getmtime(os.path.join(folder, x)), reverse=True) latest_image = os.path.join(folder, image_files[0]) if is_file_ready(latest_image): # Wait a bit more to ensure the file is completely written time.sleep(3) return latest_image return None def delete_image_file(file_path): try: if os.path.exists(file_path): os.remove(file_path) logger.debug(f"file {file_path} deleted") else: logger.debug(f"file {file_path} is not exist") except Exception as e: logger.debug(f"error {file_path}: {str(e)}") def start_queue(prompt_workflow, port): p = {"prompt": prompt_workflow} data = json.dumps(p).encode('utf-8') requests.post(f"{URL}:{port}/prompt", data=data) def check_server_ready(port): try: response = requests.get(f"{URL}:{port}/history/123", timeout=5) return response.status_code == 200 except requests.RequestException: return False @spaces.GPU(duration=170) def generate_image(image): prefix_filename = str(random.randint(0, 999999)) prompt = read_prompt_from_file('good_upscaler.json') prompt = json.dumps(prompt, ensure_ascii=False).replace('OutPutImage', prefix_filename) prompt = json.loads(prompt) image = Image.fromarray(image) image.save(INPUT_DIR + '/input.png', format='PNG') process = None new_port = str(random.randint(8123, 8200)) try: process = subprocess.Popen([sys.executable, BACKEND_PATH, "--listen", "127.0.0.1", "--port", new_port]) logger.debug(f'Subprocess started with PID: {process.pid}') for _ in range(40): if check_server_ready(new_port): break time.sleep(1) else: raise TimeoutError("Server did not start in time") start_queue(prompt, new_port) timeout = 240 start_time = time.time() while time.time() - start_time < timeout: latest_image = wait_for_image_with_prefix(OUTPUT_DIR, prefix_filename) if latest_image: logger.debug(f"file is: {latest_image}") try: return Image.open(latest_image) finally: delete_image_file(latest_image) delete_image_file(INPUT_DIR + '/input.png') time.sleep(1) raise TimeoutError("New image was not generated in time") except Exception as e: logger.error(f"Error in generate_image: {e}") finally: if process and process.poll() is None: process.terminate() logger.debug("process.terminate()") try: logger.debug("process.wait(timeout=5)") process.wait(timeout=5) except subprocess.TimeoutExpired: logger.debug("process.kill()") process.kill() if __name__ == "__main__": demo = gr.Interface( fn=generate_image, inputs=[gr.Image(image_mode='RGBA', type="numpy")], outputs=[gr.Image(type="numpy", image_mode='RGBA')], title="Image Upscaler", description="This is an upscaler that increases the resolution of your image to 16 megapixels. Upload an image to get started!" ) demo.launch(debug=True) logger.debug('demo.launch()') logger.info("finish")