from typing import Any, List, Callable
import cv2
import threading
import gfpgan
import os
import logging

import roop.globals
import roop.processors.frame.core
from roop.core import update_status
from roop.face_analyser import get_one_face
from roop.typing import Frame, Face
from roop.utilities import conditional_download, resolve_relative_path, is_image, is_video

FACE_ENHANCER = None
THREAD_SEMAPHORE = threading.Semaphore()
THREAD_LOCK = threading.Lock()
NAME = 'ROOP.FACE-ENHANCER'

# Configure logging
logging.basicConfig(level=logging.INFO)

def get_face_enhancer() -> Any:
    global FACE_ENHANCER

    with THREAD_LOCK:
        if FACE_ENHANCER is None:
            model_path = resolve_relative_path('../models/GFPGANv1.4.pth')
            try:
                FACE_ENHANCER = gfpgan.GFPGANer(model_path=model_path, upscale=5)  # type: ignore[attr-defined]
                logging.info(f"Loaded face enhancer model from {model_path}")
            except Exception as e:
                logging.error(f"Failed to load face enhancer model: {e}")
                FACE_ENHANCER = None
    return FACE_ENHANCER

def pre_check() -> bool:
    download_directory_path = resolve_relative_path('../models')
    try:
        conditional_download(download_directory_path, ['https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth'])
        logging.info("Pre-check completed successfully.")
        return True
    except Exception as e:
        logging.error(f"Pre-check failed: {e}")
        return False

def pre_start() -> bool:
    try:
        if not is_image(roop.globals.target_path) and not is_video(roop.globals.target_path):
            update_status('Select an image or video for target path.', NAME)
            return False
        logging.info("Pre-start checks passed.")
        return True
    except Exception as e:
        logging.error(f"Pre-start check failed: {e}")
        return False

def post_process() -> None:
    global FACE_ENHANCER

    FACE_ENHANCER = None
    logging.info("Post-process cleanup done.")

def enhance_face(temp_frame: Frame) -> Frame:
    try:
        with THREAD_SEMAPHORE:
            _, _, temp_frame = get_face_enhancer().enhance(
                temp_frame,
                paste_back=True
            )
        return temp_frame
    except Exception as e:
        logging.error(f"Error enhancing face: {e}")
        return temp_frame  # Return the unmodified frame in case of error

def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
    try:
        target_face = get_one_face(temp_frame)
        if target_face:
            temp_frame = enhance_face(temp_frame)
        return temp_frame
    except Exception as e:
        logging.error(f"Error processing frame: {e}")
        return temp_frame  # Return the unmodified frame in case of error

def process_frames(source_path: str, temp_frame_paths: List[str], update: Callable[[], None]) -> None:
    try:
        for temp_frame_path in temp_frame_paths:
            temp_frame = cv2.imread(temp_frame_path)
            if temp_frame is None:
                raise ValueError(f"Failed to read frame from path: {temp_frame_path}")
            
            result = process_frame(None, temp_frame)
            cv2.imwrite(temp_frame_path, result)
            if update:
                update()
        logging.info("Frames processed successfully.")
    except Exception as e:
        logging.error(f"Error processing frames: {e}")

def process_image(source_path: str, target_path: str, output_path: str) -> None:
    try:
        target_frame = cv2.imread(target_path)
        if target_frame is None:
            raise ValueError("Failed to read target frame.")
        
        result = process_frame(None, target_frame)
        cv2.imwrite(output_path, result)
        logging.info(f"Image processed and saved to {output_path}.")
    except Exception as e:
        logging.error(f"Error processing image: {e}")

def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
    try:
        roop.processors.frame.core.process_video(None, temp_frame_paths, process_frames)
        logging.info("Video processing completed.")
    except Exception as e:
        logging.error(f"Error processing video: {e}")