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import glob |
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import mimetypes |
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import os |
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import platform |
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import shutil |
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import ssl |
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import subprocess |
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import tempfile |
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import urllib |
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from pathlib import Path |
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from typing import List, Optional |
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import onnxruntime |
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from tqdm import tqdm |
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import DeepFakeAI.globals |
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from DeepFakeAI import wording |
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TEMP_DIRECTORY_PATH = os.path.join(tempfile.gettempdir(), 'DeepFakeAI') |
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TEMP_OUTPUT_NAME = 'temp.mp4' |
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if platform.system().lower() == 'darwin': |
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ssl._create_default_https_context = ssl._create_unverified_context |
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def run_ffmpeg(args : List[str]) -> bool: |
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commands = [ 'ffmpeg', '-hide_banner', '-loglevel', 'error' ] |
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commands.extend(args) |
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try: |
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subprocess.check_output(commands, stderr = subprocess.STDOUT) |
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return True |
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except subprocess.CalledProcessError: |
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return False |
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def detect_fps(target_path : str) -> Optional[float]: |
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commands = [ 'ffprobe', '-v', 'error', '-select_streams', 'v:0', '-show_entries', 'stream=r_frame_rate', '-of', 'default=noprint_wrappers = 1:nokey = 1', target_path ] |
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output = subprocess.check_output(commands).decode().strip().split('/') |
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try: |
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numerator, denominator = map(int, output) |
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return numerator / denominator |
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except (ValueError, ZeroDivisionError): |
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return None |
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def extract_frames(target_path : str, fps : float) -> bool: |
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temp_directory_path = get_temp_directory_path(target_path) |
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temp_frame_quality = round(31 - (DeepFakeAI.globals.temp_frame_quality * 0.31)) |
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trim_frame_start = DeepFakeAI.globals.trim_frame_start |
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trim_frame_end = DeepFakeAI.globals.trim_frame_end |
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commands = [ '-hwaccel', 'auto', '-i', target_path, '-q:v', str(temp_frame_quality), '-pix_fmt', 'rgb24', ] |
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if trim_frame_start is not None and trim_frame_end is not None: |
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commands.extend([ '-vf', 'trim=start_frame=' + str(trim_frame_start) + ':end_frame=' + str(trim_frame_end) + ',fps=' + str(fps) ]) |
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elif trim_frame_start is not None: |
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commands.extend([ '-vf', 'trim=start_frame=' + str(trim_frame_start) + ',fps=' + str(fps) ]) |
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elif trim_frame_end is not None: |
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commands.extend([ '-vf', 'trim=end_frame=' + str(trim_frame_end) + ',fps=' + str(fps) ]) |
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else: |
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commands.extend([ '-vf', 'fps=' + str(fps) ]) |
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commands.extend([os.path.join(temp_directory_path, '%04d.' + DeepFakeAI.globals.temp_frame_format)]) |
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return run_ffmpeg(commands) |
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def create_video(target_path : str, fps : float) -> bool: |
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temp_output_path = get_temp_output_path(target_path) |
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temp_directory_path = get_temp_directory_path(target_path) |
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output_video_quality = round(51 - (DeepFakeAI.globals.output_video_quality * 0.5)) |
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commands = [ '-hwaccel', 'auto', '-r', str(fps), '-i', os.path.join(temp_directory_path, '%04d.' + DeepFakeAI.globals.temp_frame_format), '-c:v', DeepFakeAI.globals.output_video_encoder ] |
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if DeepFakeAI.globals.output_video_encoder in [ 'libx264', 'libx265', 'libvpx' ]: |
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commands.extend([ '-crf', str(output_video_quality) ]) |
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if DeepFakeAI.globals.output_video_encoder in [ 'h264_nvenc', 'hevc_nvenc' ]: |
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commands.extend([ '-cq', str(output_video_quality) ]) |
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commands.extend([ '-pix_fmt', 'yuv420p', '-vf', 'colorspace=bt709:iall=bt601-6-625', '-y', temp_output_path ]) |
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return run_ffmpeg(commands) |
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def restore_audio(target_path : str, output_path : str) -> None: |
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fps = detect_fps(target_path) |
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trim_frame_start = DeepFakeAI.globals.trim_frame_start |
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trim_frame_end = DeepFakeAI.globals.trim_frame_end |
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temp_output_path = get_temp_output_path(target_path) |
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commands = [ '-hwaccel', 'auto', '-i', temp_output_path, '-i', target_path ] |
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if trim_frame_start is None and trim_frame_end is None: |
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commands.extend([ '-c:a', 'copy' ]) |
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else: |
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if trim_frame_start is not None: |
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start_time = trim_frame_start / fps |
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commands.extend([ '-ss', str(start_time) ]) |
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else: |
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commands.extend([ '-ss', '0' ]) |
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if trim_frame_end is not None: |
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end_time = trim_frame_end / fps |
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commands.extend([ '-to', str(end_time) ]) |
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commands.extend([ '-c:a', 'aac' ]) |
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commands.extend([ '-map', '0:v:0', '-map', '1:a:0', '-y', output_path ]) |
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done = run_ffmpeg(commands) |
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if not done: |
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move_temp(target_path, output_path) |
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def get_temp_frame_paths(target_path : str) -> List[str]: |
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temp_directory_path = get_temp_directory_path(target_path) |
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return glob.glob((os.path.join(glob.escape(temp_directory_path), '*.' + DeepFakeAI.globals.temp_frame_format))) |
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def get_temp_directory_path(target_path : str) -> str: |
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target_name, _ = os.path.splitext(os.path.basename(target_path)) |
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return os.path.join(TEMP_DIRECTORY_PATH, target_name) |
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def get_temp_output_path(target_path : str) -> str: |
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temp_directory_path = get_temp_directory_path(target_path) |
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return os.path.join(temp_directory_path, TEMP_OUTPUT_NAME) |
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def normalize_output_path(source_path : str, target_path : str, output_path : str) -> Optional[str]: |
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if source_path and target_path and output_path: |
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source_name, _ = os.path.splitext(os.path.basename(source_path)) |
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target_name, target_extension = os.path.splitext(os.path.basename(target_path)) |
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if os.path.isdir(output_path): |
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return os.path.join(output_path, source_name + '-' + target_name + target_extension) |
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return output_path |
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def create_temp(target_path : str) -> None: |
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temp_directory_path = get_temp_directory_path(target_path) |
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Path(temp_directory_path).mkdir(parents = True, exist_ok = True) |
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def move_temp(target_path : str, output_path : str) -> None: |
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temp_output_path = get_temp_output_path(target_path) |
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if os.path.isfile(temp_output_path): |
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if os.path.isfile(output_path): |
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os.remove(output_path) |
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shutil.move(temp_output_path, output_path) |
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def clear_temp(target_path : str) -> None: |
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temp_directory_path = get_temp_directory_path(target_path) |
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parent_directory_path = os.path.dirname(temp_directory_path) |
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if not DeepFakeAI.globals.keep_temp and os.path.isdir(temp_directory_path): |
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shutil.rmtree(temp_directory_path) |
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if os.path.exists(parent_directory_path) and not os.listdir(parent_directory_path): |
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os.rmdir(parent_directory_path) |
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def is_image(image_path : str) -> bool: |
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if image_path and os.path.isfile(image_path): |
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mimetype, _ = mimetypes.guess_type(image_path) |
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return bool(mimetype and mimetype.startswith('image/')) |
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return False |
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def is_video(video_path : str) -> bool: |
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if video_path and os.path.isfile(video_path): |
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mimetype, _ = mimetypes.guess_type(video_path) |
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return bool(mimetype and mimetype.startswith('video/')) |
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return False |
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def conditional_download(download_directory_path : str, urls : List[str]) -> None: |
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if not os.path.exists(download_directory_path): |
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os.makedirs(download_directory_path) |
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for url in urls: |
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download_file_path = os.path.join(download_directory_path, os.path.basename(url)) |
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if not os.path.exists(download_file_path): |
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request = urllib.request.urlopen(url) |
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total = int(request.headers.get('Content-Length', 0)) |
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with tqdm(total = total, desc = wording.get('downloading'), unit = 'B', unit_scale = True, unit_divisor = 1024) as progress: |
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urllib.request.urlretrieve(url, download_file_path, reporthook = lambda count, block_size, total_size: progress.update(block_size)) |
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def resolve_relative_path(path : str) -> str: |
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return os.path.abspath(os.path.join(os.path.dirname(__file__), path)) |
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def list_module_names(path : str) -> Optional[List[str]]: |
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if os.path.exists(path): |
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files = os.listdir(path) |
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return [Path(file).stem for file in files if not Path(file).stem.startswith('__')] |
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return None |
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def encode_execution_providers(execution_providers : List[str]) -> List[str]: |
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return [execution_provider.replace('ExecutionProvider', '').lower() for execution_provider in execution_providers] |
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def decode_execution_providers(execution_providers : List[str]) -> List[str]: |
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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)] |
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