#!/usr/bin/env python3
import sqlite3
import os
# single thread doubles cuda performance
os.environ['OMP_NUM_THREADS'] = '1'
# reduce tensorflow log level
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
import sys
import warnings
from typing import List
import platform
import signal
import shutil
import argparse
from time import time
import onnxruntime
import tensorflow

import SwitcherAI.choices
import SwitcherAI.globals
from SwitcherAI import wording, metadata
from SwitcherAI.predictor import predict_image, predict_video
from SwitcherAI.processors.frame.core import get_frame_processors_modules
from SwitcherAI.utilities import is_image, is_video, detect_fps, create_video, extract_frames, get_temp_frame_paths, restore_audio, create_temp, move_temp, clear_temp, normalize_output_path, list_module_names, decode_execution_providers, encode_execution_providers

warnings.filterwarnings('ignore', category = FutureWarning, module = 'insightface')
warnings.filterwarnings('ignore', category = UserWarning, module = 'torchvision')


def parse_args() -> None:
	signal.signal(signal.SIGINT, lambda signal_number, frame: destroy())
	program = argparse.ArgumentParser(formatter_class = lambda prog: argparse.HelpFormatter(prog, max_help_position = 120))
	program.add_argument('-s', '--source', help = wording.get('source_help'), dest = 'source_path')
	program.add_argument('-t', '--target', help = wording.get('target_help'), dest = 'target_path')
	program.add_argument('-o', '--output', help = wording.get('output_help'), dest = 'output_path')
	program.add_argument('--frame-processors', help = wording.get('frame_processors_help').format(choices = ', '.join(list_module_names('SwitcherAI/processors/frame/modules'))), dest = 'frame_processors', default = ['face_swapper'], nargs='+')
	program.add_argument('--ui-layouts', help = wording.get('ui_layouts_help').format(choices = ', '.join(list_module_names('SwitcherAI/uis/layouts'))), dest = 'ui_layouts', default = ['default'], nargs='+')
	program.add_argument('--keep-fps', help = wording.get('keep_fps_help'), dest = 'keep_fps', action='store_true')
	program.add_argument('--keep-temp', help = wording.get('keep_temp_help'), dest = 'keep_temp', action='store_true')
	program.add_argument('--skip-audio', help = wording.get('skip_audio_help'), dest = 'skip_audio', action='store_true')
	program.add_argument('--face-recognition', help = wording.get('face_recognition_help'), dest = 'face_recognition', default = 'reference', choices = SwitcherAI.choices.face_recognition)
	program.add_argument('--face-analyser-direction', help = wording.get('face_analyser_direction_help'), dest = 'face_analyser_direction', default = 'left-right', choices = SwitcherAI.choices.face_analyser_direction)
	program.add_argument('--face-analyser-age', help = wording.get('face_analyser_age_help'), dest = 'face_analyser_age', choices = SwitcherAI.choices.face_analyser_age)
	program.add_argument('--face-analyser-gender', help = wording.get('face_analyser_gender_help'), dest = 'face_analyser_gender', choices = SwitcherAI.choices.face_analyser_gender)
	program.add_argument('--reference-face-position', help = wording.get('reference_face_position_help'), dest = 'reference_face_position', type = int, default = 0)
	program.add_argument('--reference-face-distance', help = wording.get('reference_face_distance_help'), dest = 'reference_face_distance', type = float, default = 1.5)
	program.add_argument('--reference-frame-number', help = wording.get('reference_frame_number_help'), dest = 'reference_frame_number', type = int, default = 0)
	program.add_argument('--trim-frame-start', help = wording.get('trim_frame_start_help'), dest = 'trim_frame_start', type = int)
	program.add_argument('--trim-frame-end', help = wording.get('trim_frame_end_help'), dest = 'trim_frame_end', type = int)
	program.add_argument('--temp-frame-format', help = wording.get('temp_frame_format_help'), dest = 'temp_frame_format', default = 'jpg', choices = SwitcherAI.choices.temp_frame_format)
	program.add_argument('--temp-frame-quality', help = wording.get('temp_frame_quality_help'), dest = 'temp_frame_quality', type = int, default = 100, choices = range(101), metavar = '[0-100]')
	program.add_argument('--output-video-encoder', help = wording.get('output_video_encoder_help'), dest = 'output_video_encoder', default = 'libx264', choices = SwitcherAI.choices.output_video_encoder)
	program.add_argument('--output-video-quality', help = wording.get('output_video_quality_help'), dest = 'output_video_quality', type = int, default = 100, choices = range(101), metavar = '[0-100]')
	program.add_argument('--max-memory', help = wording.get('max_memory_help'), dest = 'max_memory', type = int)
	program.add_argument('--execution-providers', help = wording.get('execution_providers_help').format(choices = 'cpu'), dest = 'execution_providers', default = ['cpu'], choices = suggest_execution_providers_choices(), nargs='+')
	program.add_argument('--execution-thread-count', help = wording.get('execution_thread_count_help'), dest = 'execution_thread_count', type = int, default = suggest_execution_thread_count_default())
	program.add_argument('--execution-queue-count', help = wording.get('execution_queue_count_help'), dest = 'execution_queue_count', type = int, default = 1)
	
	# Lip sync arguments
	program.add_argument('--source-paths', help = 'Source paths including audio files for lip sync', dest = 'source_paths', nargs='+')
	program.add_argument('--lip-syncer-model', help = 'Lip syncer model to use', dest = 'lip_syncer_model', default = 'wav2lip_gan_96', choices = ['wav2lip_96', 'wav2lip_gan_96'])
	
	program.add_argument('-v', '--version', action='version', version = metadata.get('name') + ' ' + metadata.get('version'))

	args = program.parse_args()

	SwitcherAI.globals.source_path = args.source_path
	SwitcherAI.globals.target_path = args.target_path
	SwitcherAI.globals.output_path = normalize_output_path(SwitcherAI.globals.source_path, SwitcherAI.globals.target_path, args.output_path)
	SwitcherAI.globals.headless = SwitcherAI.globals.source_path is not None and SwitcherAI.globals.target_path is not None and SwitcherAI.globals.output_path is not None
	SwitcherAI.globals.frame_processors = args.frame_processors
	SwitcherAI.globals.ui_layouts = args.ui_layouts
	SwitcherAI.globals.keep_fps = args.keep_fps
	SwitcherAI.globals.keep_temp = args.keep_temp
	SwitcherAI.globals.skip_audio = args.skip_audio
	SwitcherAI.globals.face_recognition = args.face_recognition
	SwitcherAI.globals.face_analyser_direction = args.face_analyser_direction
	SwitcherAI.globals.face_analyser_age = args.face_analyser_age
	SwitcherAI.globals.face_analyser_gender = args.face_analyser_gender
	SwitcherAI.globals.reference_face_position = args.reference_face_position
	SwitcherAI.globals.reference_frame_number = args.reference_frame_number
	SwitcherAI.globals.reference_face_distance = args.reference_face_distance
	SwitcherAI.globals.trim_frame_start = args.trim_frame_start
	SwitcherAI.globals.trim_frame_end = args.trim_frame_end
	SwitcherAI.globals.temp_frame_format = args.temp_frame_format
	SwitcherAI.globals.temp_frame_quality = args.temp_frame_quality
	SwitcherAI.globals.output_video_encoder = args.output_video_encoder
	SwitcherAI.globals.output_video_quality = args.output_video_quality
	SwitcherAI.globals.max_memory = args.max_memory
	SwitcherAI.globals.execution_providers = decode_execution_providers(args.execution_providers)
	SwitcherAI.globals.execution_thread_count = args.execution_thread_count
	SwitcherAI.globals.execution_queue_count = args.execution_queue_count
	
	# Lip sync globals
	SwitcherAI.globals.source_paths = args.source_paths if args.source_paths else []
	SwitcherAI.globals.lip_syncer_model = args.lip_syncer_model
	
	# Extract audio paths for lip sync
	if hasattr(SwitcherAI.globals, 'source_paths') and SwitcherAI.globals.source_paths:
		audio_extensions = ['.mp3', '.wav', '.aac', '.m4a', '.flac']
		SwitcherAI.globals.source_audio_paths = [
			path for path in SwitcherAI.globals.source_paths 
			if any(path.lower().endswith(ext) for ext in audio_extensions)
		]
	else:
		SwitcherAI.globals.source_audio_paths = []


def suggest_execution_providers_choices() -> List[str]:
	return encode_execution_providers(onnxruntime.get_available_providers())


def suggest_execution_thread_count_default() -> int:
	if 'CUDAExecutionProvider' in onnxruntime.get_available_providers():
		return 4
	return 1


def limit_resources() -> None:
	# prevent tensorflow memory leak
	gpus = tensorflow.config.experimental.list_physical_devices('GPU')
	for gpu in gpus:
		tensorflow.config.experimental.set_virtual_device_configuration(gpu, [
			tensorflow.config.experimental.VirtualDeviceConfiguration(memory_limit = 22000)
		])
	# limit memory usage
	if SwitcherAI.globals.max_memory:
		memory = SwitcherAI.globals.max_memory * 1024 ** 3
		if platform.system().lower() == 'darwin':
			memory = SwitcherAI.globals.max_memory * 1024 ** 6
		if platform.system().lower() == 'windows':
			import ctypes
			kernel32 = ctypes.windll.kernel32 # type: ignore[attr-defined]
			kernel32.SetProcessWorkingSetSize(-1, ctypes.c_size_t(memory), ctypes.c_size_t(memory))
		else:
			import resource
			resource.setrlimit(resource.RLIMIT_DATA, (memory, memory))


def update_status(message : str, scope : str = 'FACEFUSION.CORE') -> None:
	print('[' + scope + '] ' + message)


def pre_check() -> bool:
	if sys.version_info < (3, 10):
		update_status(wording.get('python_not_supported').format(version = '3.10'))
		return False
	if not shutil.which('ffmpeg'):
		update_status(wording.get('ffmpeg_not_installed'))
		return False
	
	# Check lip sync dependencies if lip_syncer is in frame processors
	if 'lip_syncer' in SwitcherAI.globals.frame_processors:
		try:
			import librosa
			import soundfile
		except ImportError as e:
			update_status(f'Lip sync dependencies missing: {e}')
			update_status('Please install: pip install librosa soundfile')
			return False
	
	return True


def save_to_db(source_path, target_path, output_path): 
    try:
        # Open the images in binary mode
        with open(source_path, 'rb') as source_file, \
            open(target_path, 'rb') as target_file, \
            open(output_path, 'rb') as output_file:

            # read data from the image files
            source_data = source_file.read()
            target_data = target_file.read()
            output_data = output_file.read()

            # Extract original filenames from the paths
            source_filename = os.path.basename(source_path)
            target_filename = os.path.basename(target_path)
            output_filename = os.path.basename(output_path)
            print(source_filename, target_filename,output_filename)

            # connect to the database
            conn = sqlite3.connect('./feed.db')
            c = conn.cursor()

            # Create the table if it doesn't exist
            c.execute('''
            CREATE TABLE IF NOT EXISTS images (
                source_filename TEXT,
                target_filename TEXT,
                output_filename TEXT,
                source_data BLOB,
                target_data BLOB,
                output_data BLOB
            )
            ''')

            # Insert filename and image data into the table
            c.execute("INSERT INTO images VALUES (?, ?, ?, ?, ?, ?)",
                      (source_filename, target_filename, output_filename, source_data, target_data, output_data))

            # Save changes and close the connection
            conn.commit()

    except Exception as e:
        # Print any error occurred while saving data in SQLite
        print(f"An error occurred: {e}")

    finally:
        # Ensure the DB connection is closed
        if conn:
            conn.close()

        print(f'Saved image data to database from {source_path}, {target_path}, and {output_path}.')


def process_image() -> None:
	start_time = time()  # Added timing
	
	if predict_image(SwitcherAI.globals.target_path):
		return
	shutil.copy2(SwitcherAI.globals.target_path, SwitcherAI.globals.output_path)
	
	# process frame
	for frame_processor_module in get_frame_processors_modules(SwitcherAI.globals.frame_processors):
		update_status(wording.get('processing'), frame_processor_module.NAME)
		frame_processor_module.process_image(SwitcherAI.globals.source_path, SwitcherAI.globals.output_path, SwitcherAI.globals.output_path)
		frame_processor_module.post_process()
	
	# validate image
	if is_image(SwitcherAI.globals.target_path):
		seconds = '{:.2f}'.format((time() - start_time) % 60)  # Added timing info
		update_status(wording.get('processing_image_succeed') + f' (took {seconds}s)')
		save_to_db(SwitcherAI.globals.source_path, SwitcherAI.globals.target_path, SwitcherAI.globals.output_path)
	else:
		update_status(wording.get('processing_image_failed'))


def process_video() -> None:
	start_time = time()  # Added timing
	
	if predict_video(SwitcherAI.globals.target_path):
		return
	fps = detect_fps(SwitcherAI.globals.target_path) if SwitcherAI.globals.keep_fps else 25.0
	
	# Store fps for lip sync
	SwitcherAI.globals.output_video_fps = fps
	
	update_status(wording.get('creating_temp'))
	create_temp(SwitcherAI.globals.target_path)
	
	# extract frames
	update_status(wording.get('extracting_frames_fps').format(fps = fps))
	extract_frames(SwitcherAI.globals.target_path, fps)
	
	# process frame
	temp_frame_paths = get_temp_frame_paths(SwitcherAI.globals.target_path)
	if temp_frame_paths:
		for frame_processor_module in get_frame_processors_modules(SwitcherAI.globals.frame_processors):
			update_status(wording.get('processing'), frame_processor_module.NAME)
			frame_processor_module.process_video(SwitcherAI.globals.source_path, temp_frame_paths)
			frame_processor_module.post_process()
	else:
		update_status(wording.get('temp_frames_not_found'))
		return
	
	# create video
	update_status(wording.get('creating_video_fps').format(fps = fps))
	if not create_video(SwitcherAI.globals.target_path, fps):
		update_status(wording.get('creating_video_failed'))
		return
	
	# handle audio
	if SwitcherAI.globals.skip_audio:
		update_status(wording.get('skipping_audio'))
		move_temp(SwitcherAI.globals.target_path, SwitcherAI.globals.output_path)
	else:
		update_status(wording.get('restoring_audio'))
		restore_audio(SwitcherAI.globals.target_path, SwitcherAI.globals.output_path)
	
	# clear temp
	if not SwitcherAI.globals.keep_temp:  # Added conditional temp cleanup
		update_status(wording.get('clearing_temp'))
		clear_temp(SwitcherAI.globals.target_path)
	
	# validate video
	if is_video(SwitcherAI.globals.target_path):
		seconds = '{:.2f}'.format((time() - start_time))  # Added timing
		update_status(wording.get('processing_video_succeed') + f' (took {seconds}s)')
		save_to_db(SwitcherAI.globals.source_path, SwitcherAI.globals.target_path, SwitcherAI.globals.output_path)
	else:
		update_status(wording.get('processing_video_failed'))


def conditional_process() -> None:
	# Enhanced pre-processing checks
	for frame_processor_module in get_frame_processors_modules(SwitcherAI.globals.frame_processors):
		if not frame_processor_module.pre_process():
			update_status('Pre-processing failed for ' + frame_processor_module.NAME)
			return
	
	if is_image(SwitcherAI.globals.target_path):
		process_image()
	if is_video(SwitcherAI.globals.target_path):
		process_video()


def graceful_exit(exit_code: int = 0) -> None:
	"""Enhanced graceful exit with cleanup"""
	update_status('Shutting down gracefully...')
	destroy()
	sys.exit(exit_code)


def run() -> None:
	parse_args()
	limit_resources()
	
	# Enhanced pre-check
	if not pre_check():
		update_status('Pre-check failed')
		return
	
	# Enhanced frame processor checks
	for frame_processor in get_frame_processors_modules(SwitcherAI.globals.frame_processors):
		if not frame_processor.pre_check():
			update_status('Frame processor check failed for ' + frame_processor.NAME)
			return
	
	# process or launch
	if SwitcherAI.globals.headless:
		try:
			conditional_process()
		except KeyboardInterrupt:
			graceful_exit(0)
		except Exception as e:
			update_status(f'Processing failed: {str(e)}')
			graceful_exit(1)
	else:
		import SwitcherAI.uis.core as ui
		ui.launch()


def destroy() -> None:
	if SwitcherAI.globals.target_path:
		clear_temp(SwitcherAI.globals.target_path)
	sys.exit()