import os
import numpy as np
import cv2
from pathlib import Path
from tqdm import tqdm
from PIL import Image
import shutil
import time
import subprocess
from modules import devices
from queue import Queue, Empty
import modules.scripts as scr
from .frame_interpolation import clean_folder_name
from .general_utils import duplicate_pngs_from_folder, checksum
from .video_audio_utilities import get_quick_vid_info, vid2frames, ffmpeg_stitch_video, extract_number, media_file_has_audio
from basicsr.utils.download_util import load_file_from_url
from .rich import console

from modules.shared import opts

# NCNN Upscale section START
def process_ncnn_upscale_vid_upload_logic(vid_path, in_vid_fps, in_vid_res, out_vid_res, models_path, upscale_model, upscale_factor, keep_imgs, f_location, f_crf, f_preset, current_user_os):
    print(f"Got a request to *upscale* a video using {upscale_model} at {upscale_factor}")

    folder_name = clean_folder_name(Path(vid_path.orig_name).stem)
    outdir = opts.outdir_samples or os.path.join(os.getcwd(), 'outputs')
    outdir_no_tmp = outdir + f'/frame-upscaling/{folder_name}'
    i = 1
    while os.path.exists(outdir_no_tmp):
        outdir_no_tmp = f"{outdir}/frame-upscaling/{folder_name}_{i}"
        i += 1

    outdir = os.path.join(outdir_no_tmp, 'tmp_input_frames')
    os.makedirs(outdir, exist_ok=True)
    
    vid2frames(video_path=vid_path.name, video_in_frame_path=outdir, overwrite=True, extract_from_frame=0, extract_to_frame=-1, numeric_files_output=True, out_img_format='png')
    
    process_ncnn_video_upscaling(vid_path, outdir, in_vid_fps, in_vid_res, out_vid_res, models_path, upscale_model, upscale_factor, keep_imgs, f_location, f_crf, f_preset, current_user_os)
    
def process_ncnn_video_upscaling(vid_path, outdir, in_vid_fps, in_vid_res, out_vid_res, models_path, upscale_model, upscale_factor, keep_imgs, f_location, f_crf, f_preset, current_user_os):
    # get clean number from 'x2, x3' etc
    clean_num_r_up_factor = extract_number(upscale_factor)
    # set paths
    realesrgan_ncnn_location = os.path.join(models_path, 'realesrgan_ncnn', 'realesrgan-ncnn-vulkan' + ('.exe' if current_user_os == 'Windows' else ''))
    upscaled_folder_path = os.path.join(os.path.dirname(outdir), 'Upscaled_frames')
    # create folder for upscaled imgs to live in. this folder will stay alive if keep_imgs=True, otherwise get deleted at the end
    os.makedirs(upscaled_folder_path, exist_ok=True)
    # originally we used vid_path.orig_name but gradio broke it in v 3.23 so we use a hack on vid_path.name, which might not hold forever. 2023-04-05
    out_upscaled_mp4_path = os.path.join(os.path.dirname(outdir), f"{os.path.basename(vid_path.name)}_Upscaled_{upscale_factor}.mp4")
    # download upscaling model if needed
    check_and_download_realesrgan_ncnn(models_path, current_user_os)
    # set cmd command
    cmd = [realesrgan_ncnn_location, '-i', outdir, '-o', upscaled_folder_path, '-s', str(clean_num_r_up_factor), '-n', upscale_model]
    # msg to print - need it to hide that text later on (!)
    msg_to_print = f"Upscaling raw PNGs using {upscale_model} at {upscale_factor}..."
    # blink the msg in the cli until action is done
    console.print(msg_to_print, style="blink yellow", end="") 
    start_time = time.time()
    # make call to ncnn upscaling executble
    process = subprocess.run(cmd, capture_output=True, check=True, text=True)
    print("\r" + " " * len(msg_to_print), end="", flush=True)
    print(f"\r{msg_to_print}", flush=True)
    print(f"\rUpscaling \033[0;32mdone\033[0m in {time.time() - start_time:.2f} seconds!", flush=True)
    # set custom path for ffmpeg func below
    upscaled_imgs_path_for_ffmpeg = os.path.join(upscaled_folder_path, "%09d.png")
    add_soundtrack = 'None'
    # don't pass add_soundtrack to ffmpeg if orig video doesn't contain any audio, so we won't get a message saying audio couldn't be added :)
    if media_file_has_audio(vid_path.name, f_location):
        add_soundtrack = 'File'
    # stitch video from upscaled pngs 
    ffmpeg_stitch_video(ffmpeg_location=f_location, fps=in_vid_fps, outmp4_path=out_upscaled_mp4_path, stitch_from_frame=0, stitch_to_frame=-1, imgs_path=upscaled_imgs_path_for_ffmpeg, add_soundtrack=add_soundtrack, audio_path=vid_path.name, crf=f_crf, preset=f_preset)
    # delete the raw video pngs
    shutil.rmtree(outdir)
    # delete upscaled imgs if user requested
    if not keep_imgs:
        shutil.rmtree(upscaled_folder_path)
        
def check_and_download_realesrgan_ncnn(models_folder, current_user_os):
    import zipfile
    if current_user_os == 'Windows':
        zip_file_name = 'realesrgan-ncnn-windows.zip'
        executble_name = 'realesrgan-ncnn-vulkan.exe'
        zip_checksum_value = '1d073f520a4a3f6438a500fea88407964da6d4a87489719bedfa7445b76c019fdd95a5c39576ca190d7ac22c906b33d5250a6f48cb7eda2b6af3e86ec5f09dfc'
        download_url = 'https://github.com/hithereai/Real-ESRGAN/releases/download/real-esrgan-ncnn-windows/realesrgan-ncnn-windows.zip'
    elif current_user_os == 'Linux':
        zip_file_name = 'realesrgan-ncnn-linux.zip'
        executble_name = 'realesrgan-ncnn-vulkan'
        zip_checksum_value = 'df44c4e9a1ff66331079795f018a67fbad8ce37c4472929a56b5a38440cf96982d6e164a086b438c3d26d269025290dd6498bd50846bda8691521ecf8f0fafdf'
        download_url = 'https://github.com/hithereai/Real-ESRGAN/releases/download/real-esrgan-ncnn-linux/realesrgan-ncnn-linux.zip'
    elif current_user_os == 'Mac':
        zip_file_name = 'realesrgan-ncnn-mac.zip'
        executble_name = 'realesrgan-ncnn-vulkan'
        zip_checksum_value = '65f09472025b55b18cf6ba64149ede8cded90c20e18d35a9edb1ab60715b383a6ffbf1be90d973fc2075cf99d4cc1411fbdc459411af5c904f544b8656111469'
        download_url = 'https://github.com/hithereai/Real-ESRGAN/releases/download/real-esrgan-ncnn-mac/realesrgan-ncnn-mac.zip'
    else: # who are you then?
        raise Exception(f"No support for OS type: {current_user_os}")

    # set paths
    realesrgan_ncnn_folder = os.path.join(models_folder, 'realesrgan_ncnn')
    realesrgan_exec_path = os.path.join(realesrgan_ncnn_folder, executble_name)
    realesrgan_zip_path = os.path.join(realesrgan_ncnn_folder, zip_file_name)
    # return if exec file already exist
    if os.path.exists(realesrgan_exec_path):
        return
    try:
        os.makedirs(realesrgan_ncnn_folder, exist_ok=True)
        # download exec and model files from url
        load_file_from_url(download_url, realesrgan_ncnn_folder)
        # check downloaded zip's hash
        with open(realesrgan_zip_path, 'rb') as f:
            file_hash = checksum(realesrgan_zip_path)
        # wrong hash, file is probably broken/ download interrupted 
        if file_hash != zip_checksum_value:
            raise Exception(f"Error while downloading {realesrgan_zip_path}. Please download from: {download_url}, and extract its contents into: {models_folder}/realesrgan_ncnn")
        # hash ok, extract zip contents into our folder
        with zipfile.ZipFile(realesrgan_zip_path, 'r') as zip_ref:
            zip_ref.extractall(realesrgan_ncnn_folder)
        # delete the zip file
        os.remove(realesrgan_zip_path)
        # chmod 755 the exec if we're in a linux machine, otherwise we'd get permission errors
        if current_user_os in ('Linux', 'Mac'):
            os.chmod(realesrgan_exec_path, 0o755)
            # enable running the exec for mac users
            if current_user_os == 'Mac':
                os.system(f'xattr -d com.apple.quarantine "{realesrgan_exec_path}"')

    except Exception as e:
        raise Exception(f"Error while downloading {realesrgan_zip_path}. Please download from: {download_url}, and extract its contents into: {models_folder}/realesrgan_ncnn")

def make_upscale_v2(upscale_factor, upscale_model, keep_imgs, imgs_raw_path, imgs_batch_id, deforum_models_path, current_user_os, ffmpeg_location, ffmpeg_crf, ffmpeg_preset, fps, stitch_from_frame, stitch_to_frame, audio_path, add_soundtrack, srt_path=None):
    # get clean number from 'x2, x3' etc
    clean_num_r_up_factor = extract_number(upscale_factor)
    # set paths
    realesrgan_ncnn_location = os.path.join(deforum_models_path, 'realesrgan_ncnn', 'realesrgan-ncnn-vulkan' + ('.exe' if current_user_os == 'Windows' else ''))
    upscaled_folder_path = os.path.join(imgs_raw_path, f"{imgs_batch_id}_upscaled")
    temp_folder_to_keep_raw_ims = os.path.join(upscaled_folder_path, 'temp_raw_imgs_to_upscale')
    out_upscaled_mp4_path = os.path.join(imgs_raw_path, f"{imgs_batch_id}_Upscaled_{upscale_factor}.mp4")
    # download upscaling model if needed
    check_and_download_realesrgan_ncnn(deforum_models_path, current_user_os)
    # make a folder with only the imgs we need to duplicate so we can call the ncnn with the folder syntax (quicker!)
    duplicate_pngs_from_folder(from_folder=imgs_raw_path, to_folder=temp_folder_to_keep_raw_ims, img_batch_id=imgs_batch_id, orig_vid_name='Dummy')
    # set dynamic cmd command
    cmd = [realesrgan_ncnn_location, '-i', temp_folder_to_keep_raw_ims, '-o', upscaled_folder_path, '-s', str(clean_num_r_up_factor), '-n', upscale_model]
    # msg to print - need it to hide that text later on (!)
    msg_to_print = f"Upscaling raw output PNGs using {upscale_model} at {upscale_factor}..."
    # blink the msg in the cli until action is done
    console.print(msg_to_print, style="blink yellow", end="") 
    start_time = time.time()
    # make call to ncnn upscaling executble
    process = subprocess.run(cmd, capture_output=True, check=True, text=True, cwd=(os.path.join(deforum_models_path, 'realesrgan_ncnn') if current_user_os == 'Mac' else None))
    print("\r" + " " * len(msg_to_print), end="", flush=True)
    print(f"\r{msg_to_print}", flush=True)
    print(f"\rUpscaling \033[0;32mdone\033[0m in {time.time() - start_time:.2f} seconds!", flush=True)
    # set custom path for ffmpeg func below
    upscaled_imgs_path_for_ffmpeg = os.path.join(upscaled_folder_path, f"{imgs_batch_id}_%09d.png")
    # stitch video from upscaled pngs 
    ffmpeg_stitch_video(ffmpeg_location=ffmpeg_location, fps=fps, outmp4_path=out_upscaled_mp4_path, stitch_from_frame=stitch_from_frame, stitch_to_frame=stitch_to_frame, imgs_path=upscaled_imgs_path_for_ffmpeg, add_soundtrack=add_soundtrack, audio_path=audio_path, crf=ffmpeg_crf, preset=ffmpeg_preset, srt_path=srt_path)

    # delete the duplicated raw imgs
    shutil.rmtree(temp_folder_to_keep_raw_ims)

    if not keep_imgs:
        shutil.rmtree(upscaled_folder_path)
# NCNN Upscale section END