264 lines
17 KiB
Python
264 lines
17 KiB
Python
import os
|
|
import numpy as np
|
|
import cv2
|
|
from pathlib import Path
|
|
from tqdm import tqdm
|
|
from PIL import Image
|
|
from modules.scripts_postprocessing import PostprocessedImage
|
|
from modules import devices
|
|
import shutil
|
|
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
|
|
# TODO: move some funcs to this file?
|
|
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
|
|
import time
|
|
import subprocess
|
|
|
|
def process_upscale_vid_upload_logic(file, selected_tab, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, vid_file_name, keep_imgs, f_location, f_crf, f_preset):
|
|
print("Got a request to *upscale* an existing video.")
|
|
|
|
in_vid_fps, _, _ = get_quick_vid_info(file.name)
|
|
folder_name = clean_folder_name(Path(vid_file_name).stem)
|
|
outdir_no_tmp = os.path.join(os.getcwd(), 'outputs', 'frame-upscaling', folder_name)
|
|
i = 1
|
|
while os.path.exists(outdir_no_tmp):
|
|
outdir_no_tmp = os.path.join(os.getcwd(), 'outputs', 'frame-upscaling', folder_name + '_' + str(i))
|
|
i += 1
|
|
|
|
outdir = os.path.join(outdir_no_tmp, 'tmp_input_frames')
|
|
os.makedirs(outdir, exist_ok=True)
|
|
|
|
vid2frames(video_path=file.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_video_upscaling(selected_tab, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, orig_vid_fps=in_vid_fps, real_audio_track=file.name, raw_output_imgs_path=outdir, img_batch_id=None, ffmpeg_location=f_location, ffmpeg_crf=f_crf, ffmpeg_preset=f_preset, keep_upscale_imgs=keep_imgs, orig_vid_name=folder_name)
|
|
|
|
def process_video_upscaling(resize_mode, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, orig_vid_fps, real_audio_track, raw_output_imgs_path, img_batch_id, ffmpeg_location, ffmpeg_crf, ffmpeg_preset, keep_upscale_imgs, orig_vid_name):
|
|
devices.torch_gc()
|
|
|
|
print("Upscaling progress (it's OK if it finishes before 100%):")
|
|
|
|
upscaled_path = os.path.join(raw_output_imgs_path, 'upscaled_frames')
|
|
if orig_vid_name is not None: # upscaling a video (deforum or unrelated)
|
|
custom_upscale_path = "{}_{}".format(upscaled_path, orig_vid_name)
|
|
else: # upscaling after a deforum run:
|
|
custom_upscale_path = "{}_{}".format(upscaled_path, img_batch_id)
|
|
|
|
temp_convert_raw_png_path = os.path.join(raw_output_imgs_path, "tmp_upscale_folder")
|
|
duplicate_pngs_from_folder(raw_output_imgs_path, temp_convert_raw_png_path, img_batch_id, orig_vid_name)
|
|
|
|
videogen = []
|
|
for f in os.listdir(temp_convert_raw_png_path):
|
|
# double check for old _depth_ files, not really needed probably but keeping it for now
|
|
if '_depth_' not in f:
|
|
videogen.append(f)
|
|
|
|
videogen.sort(key= lambda x:int(x.split('.')[0]))
|
|
vid_out = None
|
|
|
|
if not os.path.exists(custom_upscale_path):
|
|
os.mkdir(custom_upscale_path)
|
|
|
|
# Upscaling is a slow and demanding operation, so we don't need as much parallelization here
|
|
for i in tqdm(range(len(videogen)), desc="Upscaling"):
|
|
lastframe = videogen[i]
|
|
img_path = os.path.join(temp_convert_raw_png_path, lastframe)
|
|
image = process_frame(resize_mode, Image.open(img_path).convert("RGB"), upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility)
|
|
filename = '{}/{:0>7d}.png'.format(custom_upscale_path, i)
|
|
image.save(filename)
|
|
|
|
shutil.rmtree(temp_convert_raw_png_path)
|
|
# stitch video from upscaled frames, and add audio if needed
|
|
try:
|
|
print (f"*Passing upsc frames to ffmpeg...*")
|
|
vid_out_path = stitch_video(img_batch_id, orig_vid_fps, custom_upscale_path, real_audio_track, ffmpeg_location, resize_mode, upscaling_resize, upscaling_resize_w, upscaling_resize_h, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, ffmpeg_crf, ffmpeg_preset, keep_upscale_imgs, orig_vid_name)
|
|
# remove folder with raw (non-upscaled) vid input frames in case of input VID and not PNGs
|
|
if orig_vid_name is not None:
|
|
shutil.rmtree(raw_output_imgs_path)
|
|
except Exception as e:
|
|
print(f'Video stitching gone wrong. *Upscaled frames were saved to HD as backup!*. Actual error: {e}')
|
|
|
|
devices.torch_gc()
|
|
|
|
def process_frame(resize_mode, image, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility):
|
|
pp = PostprocessedImage(image)
|
|
postproc = scr.scripts_postproc
|
|
upscaler_script = next(s for s in postproc.scripts if s.name == "Upscale")
|
|
upscaler_script.process(pp, resize_mode, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility)
|
|
return pp.image
|
|
|
|
def stitch_video(img_batch_id, fps, img_folder_path, audio_path, ffmpeg_location, resize_mode, upscaling_resize, upscaling_resize_w, upscaling_resize_h, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, f_crf, f_preset, keep_imgs, orig_vid_name):
|
|
parent_folder = os.path.dirname(img_folder_path)
|
|
grandparent_folder = os.path.dirname(parent_folder)
|
|
if orig_vid_name is not None:
|
|
mp4_path = os.path.join(grandparent_folder, str(orig_vid_name) +'_upscaled_' + (('by_' + str(upscaling_resize).replace('.', '-')) if resize_mode == 0 else f"to_{upscaling_resize_w}_{upscaling_resize_h}")) + f"_with_{extras_upscaler_1}" + (f"_then_{extras_upscaler_2}" if extras_upscaler_2_visibility > 0 else "")
|
|
else:
|
|
mp4_path = os.path.join(parent_folder, str(img_batch_id) +'_upscaled_' + (('by_' + str(upscaling_resize).replace('.', '-')) if resize_mode == 0 else f"to_{upscaling_resize_w}_{upscaling_resize_h}")) + f"_with_{extras_upscaler_1}_then_{extras_upscaler_2}"
|
|
|
|
mp4_path = mp4_path + '.mp4'
|
|
|
|
t = os.path.join(img_folder_path, "%07d.png")
|
|
add_soundtrack = 'None'
|
|
if not audio_path is None:
|
|
add_soundtrack = 'File'
|
|
|
|
exception_raised = False
|
|
try:
|
|
ffmpeg_stitch_video(ffmpeg_location=ffmpeg_location, fps=fps, outmp4_path=mp4_path, stitch_from_frame=0, stitch_to_frame=1000000, imgs_path=t, add_soundtrack=add_soundtrack, audio_path=audio_path, crf=f_crf, preset=f_preset)
|
|
except Exception as e:
|
|
exception_raised = True
|
|
print(f"An error occurred while stitching the video: {e}")
|
|
|
|
if not exception_raised and not keep_imgs:
|
|
shutil.rmtree(img_folder_path)
|
|
|
|
if (keep_imgs and orig_vid_name is not None) or (orig_vid_name is not None and exception_raised is True):
|
|
shutil.move(img_folder_path, grandparent_folder)
|
|
|
|
return mp4_path
|
|
|
|
# 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_no_tmp = os.path.join(os.getcwd(), 'outputs', 'frame-upscaling', folder_name)
|
|
i = 1
|
|
while os.path.exists(outdir_no_tmp):
|
|
outdir_no_tmp = os.path.join(os.getcwd(), 'outputs', 'frame-upscaling', folder_name + '_' + str(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)
|
|
out_upscaled_mp4_path = os.path.join(os.path.dirname(outdir), f"{vid_path.orig_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, "%05d.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):
|
|
# 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}_%05d.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)
|
|
|
|
# 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 |