#!/usr/bin/env python3

import os
import sys
import shutil
import argparse
import warnings
from typing import List
import platform
import signal
import torch
import onnxruntime
import pathlib
from time import time
import roop.globals
import roop.metadata
import roop.utilities as util
import roop.util_ffmpeg as ffmpeg
from settings import Settings
from roop.face_util import extract_face_images
from roop.ProcessEntry import ProcessEntry
from roop.ProcessMgr import ProcessMgr
from roop.ProcessOptions import ProcessOptions
from roop.capturer import get_video_frame_total
from roop.FaceSet import FaceSet

process_mgr = None

if 'ROCMExecutionProvider' in roop.globals.execution_providers:
    del torch

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


def parse_args():
    parser = argparse.ArgumentParser(description="Run Roop from the command line")
    parser.add_argument('--source_path', type=str, required=True, help="Path to the source file")
    parser.add_argument('--target_path', type=str, required=True, help="Path to the target file")
    parser.add_argument('--output_path', type=str, required=True, help="Path to save the output file")
    parser.add_argument('--execution_provider', type=str, default='CPUExecutionProvider', help="Execution provider for ONNX runtime")
    parser.add_argument('--max_memory', type=int, default=None, help="Max memory to use (in GB)")
    parser.add_argument('--distance_threshold', type=float, default=0.6, help="Distance threshold for face matching")
    parser.add_argument('--blend_ratio', type=float, default=0.5, help="Blend ratio for face swapping")
    parser.add_argument('--face_swap_mode', type=str, default='replace', help="Face swap mode")
    parser.add_argument('--output_image_format', type=str, default='png', help="Output image format")
    parser.add_argument('--output_video_format', type=str, default='mp4', help="Output video format")
    parser.add_argument('--execution_threads', type=int, default=8, help="Number of threads to use for execution")
    parser.add_argument('--skip_audio', action='store_true', help="Skip audio when processing video")
    return parser.parse_args()


def encode_execution_providers(execution_providers: List[str]) -> List[str]:
    return [execution_provider.replace('ExecutionProvider', '').lower() for execution_provider in execution_providers]


def decode_execution_providers(execution_providers: List[str]) -> List[str]:
    return [provider for provider, encoded_execution_provider in zip(onnxruntime.get_available_providers(), encode_execution_providers(onnxruntime.get_available_providers()))
            if any(execution_provider in encoded_execution_provider for execution_provider in execution_providers)]


def suggest_max_memory() -> int:
    if platform.system().lower() == 'darwin':
        return 4
    return 16


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


def suggest_execution_threads() -> int:
    if 'DmlExecutionProvider' in roop.globals.execution_providers:
        return 1
    if 'ROCMExecutionProvider' in roop.globals.execution_providers:
        return 1
    return 8


def limit_resources() -> None:
    # limit memory usage
    if roop.globals.max_memory:
        memory = roop.globals.max_memory * 1024 ** 3
        if platform.system().lower() == 'darwin':
            memory = roop.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 release_resources() -> None:
    import gc
    global process_mgr

    if process_mgr is not None:
        process_mgr.release_resources()
        process_mgr = None

    gc.collect()


def pre_check() -> bool:
    if sys.version_info < (3, 9):
        update_status('Python version is not supported - please upgrade to 3.9 or higher.')
        return False
    
    download_directory_path = util.resolve_relative_path('../models')
    util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/inswapper_128.onnx'])
    util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/GFPGANv1.4.onnx'])
    util.conditional_download(download_directory_path, ['https://github.com/csxmli2016/DMDNet/releases/download/v1/DMDNet.pth'])
    util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/GPEN-BFR-512.onnx'])
    util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/restoreformer_plus_plus.onnx'])
    util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/xseg.onnx'])
    download_directory_path = util.resolve_relative_path('../models/CLIP')
    util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/rd64-uni-refined.pth'])
    download_directory_path = util.resolve_relative_path('../models/CodeFormer')
    util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/CodeFormerv0.1.onnx'])
    download_directory_path = util.resolve_relative_path('../models/Frame')
    util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/deoldify_artistic.onnx'])
    util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/deoldify_stable.onnx'])
    util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/isnet-general-use.onnx'])
    util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/real_esrgan_x4.onnx'])
    util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/real_esrgan_x2.onnx'])
    util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/lsdir_x4.onnx'])

    if not shutil.which('ffmpeg'):
        update_status('ffmpeg is not installed.')
    return True


def update_status(message: str) -> None:
    print(message)


def get_processing_plugins(masking_engine):
    processors = {"faceswap": {}}
    if masking_engine is not None:
        processors.update({masking_engine: {}})
    
    if roop.globals.selected_enhancer == 'GFPGAN':
        processors.update({"gfpgan": {}})
    elif roop.globals.selected_enhancer == 'Codeformer':
        processors.update({"codeformer": {}})
    elif roop.globals.selected_enhancer == 'DMDNet':
        processors.update({"dmdnet": {}})
    elif roop.globals.selected_enhancer == 'GPEN':
        processors.update({"gpen": {}})
    elif roop.globals.selected_enhancer == 'Restoreformer++':
        processors.update({"restoreformer++": {}})
    return processors


def live_swap(frame, options):
    global process_mgr

    if frame is None:
        return frame

    if process_mgr is None:
        process_mgr = ProcessMgr(None)
    
    process_mgr.initialize(roop.globals.INPUT_FACESETS, roop.globals.TARGET_FACES, options)
    newframe = process_mgr.process_frame(frame)
    if newframe is None:
        return frame
    return newframe


def batch_process_regular(files: List[ProcessEntry], masking_engine: str, new_clip_text: str, use_new_method, imagemask, num_swap_steps, progress, selected_index=0) -> None:
    global process_mgr

    release_resources()
    limit_resources()
    if process_mgr is None:
        process_mgr = ProcessMgr(progress)
    mask = imagemask["layers"][0] if imagemask is not None else None
    if len(roop.globals.INPUT_FACESETS) <= selected_index:
        selected_index = 0
    options = ProcessOptions(get_processing_plugins(masking_engine), roop.globals.distance_threshold, roop.globals.blend_ratio, roop.globals.face_swap_mode, selected_index, new_clip_text, mask, num_swap_steps, False)
    process_mgr.initialize(roop.globals.INPUT_FACESETS, roop.globals.TARGET_FACES, options)
    batch_process(files, use_new_method)
    return


def batch_process_with_options(files: List[ProcessEntry], options, progress):
    global process_mgr

    release_resources()
    limit_resources()
    if process_mgr is None:
        process_mgr = ProcessMgr(progress)
    process_mgr.initialize(roop.globals.INPUT_FACESETS, roop.globals.TARGET_FACES, options)
    roop.globals.keep_frames = False
    roop.globals.wait_after_extraction = False
    roop.globals.skip_audio = False
    batch_process(files, True)


def batch_process(files: List[ProcessEntry], use_new_method) -> None:
    global process_mgr

    roop.globals.processing = True

    max_threads = suggest_execution_threads()
    if max_threads == 1:
        roop.globals.execution_threads = 1

    imagefiles: List[ProcessEntry] = []
    videofiles: List[ProcessEntry] = []
           
    update_status('Sorting videos/images')

    for index, f in enumerate(files):
        fullname = f.filename
        if util.has_image_extension(fullname):
            destination = util.get_destfilename_from_path(fullname, roop.globals.output_path, f'.{roop.globals.CFG.output_image_format}')
            destination = util.replace_template(destination, index=index)
            pathlib.Path(os.path.dirname(destination)).mkdir(parents=True, exist_ok=True)
            f.finalname = destination
            imagefiles.append(f)

        elif util.is_video(fullname) or util.has_extension(fullname, ['gif']):
            destination = util.get_destfilename_from_path(fullname, roop.globals.output_path, f'__temp.{roop.globals.CFG.output_video_format}')
            f.finalname = destination
            videofiles.append(f)

    if len(imagefiles) > 0:
        update_status('Processing image(s)')
        origimages = []
        fakeimages = []
        for f in imagefiles:
            origimages.append(f.filename)
            fakeimages.append(f.finalname)

        process_mgr.run_batch(origimages, fakeimages, roop.globals.execution_threads)
        origimages.clear()
        fakeimages.clear()

    if len(videofiles) > 0:
        for index, v in enumerate(videofiles):
            if not roop.globals.processing:
                end_processing('Processing stopped!')
                return
            fps = v.fps if v.fps > 0 else util.detect_fps(v.filename)
            if v.endframe == 0:
                v.endframe = get_video_frame_total(v.filename)

            update_status(f'Creating {os.path.basename(v.finalname)} with {fps} FPS...')
            start_processing = time()
            if roop.globals.keep_frames or not use_new_method:
                util.create_temp(v.filename)
                update_status('Extracting frames...')
                ffmpeg.extract_frames(v.filename, v.startframe, v.endframe, fps)
                if not roop.globals.processing:
                    end_processing('Processing stopped!')
                    return

                temp_frame_paths = util.get_temp_frame_paths(v.filename)
                process_mgr.run_batch(temp_frame_paths, temp_frame_paths, roop.globals.execution_threads)
                if not roop.globals.processing:
                    end_processing('Processing stopped!')
                    return
                if roop.globals.wait_after_extraction:
                    extract_path = os.path.dirname(temp_frame_paths[0])
                    util.open_folder(extract_path)
                    input("Press any key to continue...")
                    print("Resorting frames to create video")
                    util.sort_rename_frames(extract_path)                                    
                
                ffmpeg.create_video(v.filename, v.finalname, fps)
                if not roop.globals.keep_frames:
                    util.delete_temp_frames(temp_frame_paths[0])
            else:
                if util.has_extension(v.filename, ['gif']):
                    skip_audio = True
                else:
                    skip_audio = roop.globals.skip_audio
                process_mgr.run_batch_inmem(v.filename, v.finalname, v.startframe, v.endframe, fps, roop.globals.execution_threads, skip_audio)
                
            if not roop.globals.processing:
                end_processing('Processing stopped!')
                return
            
            video_file_name = v.finalname
            if os.path.isfile(video_file_name):
                destination = ''
                if util.has_extension(v.filename, ['gif']):
                    gifname = util.get_destfilename_from_path(v.filename, roop.globals.output_path, '.gif')
                    destination = util.replace_template(gifname, index=index)
                    pathlib.Path(os.path.dirname(destination)).mkdir(parents=True, exist_ok=True)

                    update_status('Creating final GIF')
                    ffmpeg.create_gif_from_video(video_file_name, destination)
                    if os.path.isfile(destination):
                        os.remove(video_file_name)
                else:
                    skip_audio = roop.globals.skip_audio
                    destination = util.replace_template(video_file_name, index=index)
                    pathlib.Path(os.path.dirname(destination)).mkdir(parents=True, exist_ok=True)

                    if not skip_audio:
                        ffmpeg.restore_audio(video_file_name, v.filename, v.startframe, v.endframe, destination)
                        if os.path.isfile(destination):
                            os.remove(video_file_name)
                    else:
                        shutil.move(video_file_name, destination)
                update_status(f'\nProcessing {os.path.basename(destination)} took {time() - start_processing} secs')

            else:
                update_status(f'Failed processing {os.path.basename(v.finalname)}!')
    end_processing('Finished')


def end_processing(msg: str):
    update_status(msg)
    roop.globals.target_folder_path = None
    release_resources()


def destroy() -> None:
    if roop.globals.target_path:
        util.clean_temp(roop.globals.target_path)
    release_resources()
    sys.exit()


def run() -> None:
    args = parse_args()

    roop.globals.source_path = args.source_path
    roop.globals.target_path = args.target_path
    roop.globals.output_path = args.output_path
    roop.globals.execution_providers = decode_execution_providers([args.execution_provider])
    roop.globals.max_memory = args.max_memory
    roop.globals.distance_threshold = args.distance_threshold
    roop.globals.blend_ratio = args.blend_ratio
    roop.globals.face_swap_mode = args.face_swap_mode
    roop.globals.CFG = Settings('config.yaml')
    roop.globals.execution_threads = args.execution_threads
    roop.globals.output_image_format = args.output_image_format
    roop.globals.output_video_format = args.output_video_format
    roop.globals.skip_audio = args.skip_audio
    roop.globals.face_swap_mode == 'selected'
    # Ensure these values are set
    if not roop.globals.video_encoder:
        roop.globals.video_encoder = 'libx264'  # or another suitable default value
    if not roop.globals.video_quality:
        roop.globals.video_quality = 23  # or another suitable default value

    signal.signal(signal.SIGINT, lambda signal_number, frame: destroy())

    if not pre_check():
        return

    # Extract faces from the source and target files and create FaceSet objects
    source_faces = extract_face_images(args.source_path, (False, 0))
    target_faces = extract_face_images(args.target_path, (False, util.has_image_extension(args.target_path)))
    print("Number of targets faces is ", target_faces.count)

    if source_faces:
        source_face_set = FaceSet()
        for face_data in source_faces:
            face = face_data[0]
            face.mask_offsets = (0, 0, 0, 0, 1, 20)
            source_face_set.faces.append(face)
        if len(source_face_set.faces) > 1:
            source_face_set.AverageEmbeddings()
        roop.globals.INPUT_FACESETS.append(source_face_set)

    if target_faces:
        target_face_set = FaceSet()
        for face_data in target_faces:
            face = face_data[0]
            face.mask_offsets = (0, 0, 0, 0, 1, 20)
            target_face_set.faces.append(face)
        if len(target_face_set.faces) > 1:
            target_face_set.AverageEmbeddings()
        roop.globals.TARGET_FACES.append(target_face_set.faces[0])  # Assuming using the first face for target

    # Detect fps and endframe values for the source and target videos
    source_fps = util.detect_fps(args.source_path)
    source_endframe = get_video_frame_total(args.source_path)
    target_fps = util.detect_fps(args.target_path)
    target_endframe = get_video_frame_total(args.target_path)

    # Initialize ProcessEntry objects using detected values
    source_entry = ProcessEntry(
        filename=args.source_path,
        start=0,
        end=source_endframe,
        fps=source_fps
    )

    target_entry = ProcessEntry(
        filename=args.target_path,
        start=0,
        end=target_endframe,
        fps=target_fps
    )

    files = [source_entry, target_entry]
    batch_process_regular(files, None, None, False, None, 1, None)