initial commit

rebranding everything

modules/processors/frame/core.py

@@ -0,0 +1,72 @@
+import sys
+import importlib
+from concurrent.futures import ThreadPoolExecutor
+from types import ModuleType
+from typing import Any, List, Callable
+from tqdm import tqdm
+
+import modules
+import modules.globals                   
+
+FRAME_PROCESSORS_MODULES: List[ModuleType] = []
+FRAME_PROCESSORS_INTERFACE = [
+    'pre_check',
+    'pre_start',
+    'process_frame',
+    'process_image',
+    'process_video'
+]
+
+
+def load_frame_processor_module(frame_processor: str) -> Any:
+    try:
+        frame_processor_module = importlib.import_module(f'modules.processors.frame.{frame_processor}')
+        for method_name in FRAME_PROCESSORS_INTERFACE:
+            if not hasattr(frame_processor_module, method_name):
+                sys.exit()
+    except ImportError:
+        sys.exit()
+    return frame_processor_module
+
+
+def get_frame_processors_modules(frame_processors: List[str]) -> List[ModuleType]:
+    global FRAME_PROCESSORS_MODULES
+
+    if not FRAME_PROCESSORS_MODULES:
+        for frame_processor in frame_processors:
+            frame_processor_module = load_frame_processor_module(frame_processor)
+            FRAME_PROCESSORS_MODULES.append(frame_processor_module)
+    set_frame_processors_modules_from_ui(frame_processors)
+    return FRAME_PROCESSORS_MODULES
+
+def set_frame_processors_modules_from_ui(frame_processors: List[str]) -> None:
+    global FRAME_PROCESSORS_MODULES
+    for frame_processor, state in modules.globals.fp_ui.items():
+        if state == True and frame_processor not in frame_processors:
+            frame_processor_module = load_frame_processor_module(frame_processor)
+            FRAME_PROCESSORS_MODULES.append(frame_processor_module)
+            modules.globals.frame_processors.append(frame_processor)
+        if state == False:
+            frame_processor_module = load_frame_processor_module(frame_processor)
+            try:
+                FRAME_PROCESSORS_MODULES.remove(frame_processor_module)
+                modules.globals.frame_processors.remove(frame_processor)
+            except:
+                pass
+
+def multi_process_frame(source_path: str, temp_frame_paths: List[str], process_frames: Callable[[str, List[str], Any], None], progress: Any = None) -> None:
+    with ThreadPoolExecutor(max_workers=modules.globals.execution_threads) as executor:
+        futures = []
+        for path in temp_frame_paths:
+            future = executor.submit(process_frames, source_path, [path], progress)
+            futures.append(future)
+        for future in futures:
+            future.result()
+
+
+def process_video(source_path: str, frame_paths: list[str], process_frames: Callable[[str, List[str], Any], None]) -> None:
+    progress_bar_format = '{l_bar}{bar}| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, {rate_fmt}{postfix}]'
+    total = len(frame_paths)
+    with tqdm(total=total, desc='Processing', unit='frame', dynamic_ncols=True, bar_format=progress_bar_format) as progress:
+        progress.set_postfix({'execution_providers': modules.globals.execution_providers, 'execution_threads': modules.globals.execution_threads, 'max_memory': modules.globals.max_memory})
+        multi_process_frame(source_path, frame_paths, process_frames, progress)

modules/processors/frame/face_enhancer.py

@@ -0,0 +1,75 @@
+from typing import Any, List
+import cv2
+import threading
+import gfpgan
+
+import modules.globals
+import modules.processors.frame.core
+from modules.core import update_status
+from modules.face_analyser import get_one_face
+from modules.typing import Frame, Face
+from modules.utilities import conditional_download, resolve_relative_path, is_image, is_video
+
+FACE_ENHANCER = None
+THREAD_SEMAPHORE = threading.Semaphore()
+THREAD_LOCK = threading.Lock()
+NAME = 'DLC.FACE-ENHANCER'
+
+
+def pre_check() -> bool:
+    download_directory_path = resolve_relative_path('..\models')
+    conditional_download(download_directory_path, ['https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth'])
+    return True
+
+
+def pre_start() -> bool:
+    if not is_image(modules.globals.target_path) and not is_video(modules.globals.target_path):
+        update_status('Select an image or video for target path.', NAME)
+        return False
+    return True
+
+
+def get_face_enhancer() -> Any:
+    global FACE_ENHANCER
+
+    with THREAD_LOCK:
+        if FACE_ENHANCER is None:
+            model_path = resolve_relative_path('..\models\GFPGANv1.4.pth')
+            # todo: set models path https://github.com/TencentARC/GFPGAN/issues/399
+            FACE_ENHANCER = gfpgan.GFPGANer(model_path=model_path, upscale=1) # type: ignore[attr-defined]
+    return FACE_ENHANCER
+
+
+def enhance_face(temp_frame: Frame) -> Frame:
+    with THREAD_SEMAPHORE:
+        _, _, temp_frame = get_face_enhancer().enhance(
+            temp_frame,
+            paste_back=True
+        )
+    return temp_frame
+
+
+def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
+    target_face = get_one_face(temp_frame)
+    if target_face:
+        temp_frame = enhance_face(temp_frame)
+    return temp_frame
+
+
+def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any = None) -> None:
+    for temp_frame_path in temp_frame_paths:
+        temp_frame = cv2.imread(temp_frame_path)
+        result = process_frame(None, temp_frame)
+        cv2.imwrite(temp_frame_path, result)
+        if progress:
+            progress.update(1)
+
+
+def process_image(source_path: str, target_path: str, output_path: str) -> None:
+    target_frame = cv2.imread(target_path)
+    result = process_frame(None, target_frame)
+    cv2.imwrite(output_path, result)
+
+
+def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
+    modules.processors.frame.core.process_video(None, temp_frame_paths, process_frames)

modules/processors/frame/face_swapper.py

@@ -0,0 +1,86 @@
+from typing import Any, List
+import cv2
+import insightface
+import threading
+
+import modules.globals
+import modules.processors.frame.core
+from modules.core import update_status
+from modules.face_analyser import get_one_face, get_many_faces
+from modules.typing import Face, Frame
+from modules.utilities import conditional_download, resolve_relative_path, is_image, is_video
+
+FACE_SWAPPER = None
+THREAD_LOCK = threading.Lock()
+NAME = 'DLC.FACE-SWAPPER'
+
+
+def pre_check() -> bool:
+    download_directory_path = resolve_relative_path('../models')
+    conditional_download(download_directory_path, ['https://github.com/facefusion/facefusion-assets/releases/download/models/inswapper_128.onnx'])
+    return True
+
+
+def pre_start() -> bool:
+    if not is_image(modules.globals.source_path):
+        update_status('Select an image for source path.', NAME)
+        return False
+    elif not get_one_face(cv2.imread(modules.globals.source_path)):
+        update_status('No face in source path detected.', NAME)
+        return False
+    if not is_image(modules.globals.target_path) and not is_video(modules.globals.target_path):
+        update_status('Select an image or video for target path.', NAME)
+        return False
+    return True
+
+
+def get_face_swapper() -> Any:
+    global FACE_SWAPPER
+
+    with THREAD_LOCK:
+        if FACE_SWAPPER is None:
+            model_path = resolve_relative_path('../models/inswapper_128.onnx')
+            FACE_SWAPPER = insightface.model_zoo.get_model(model_path, providers=modules.globals.execution_providers)
+    return FACE_SWAPPER
+
+
+def swap_face(source_face: Face, target_face: Face, temp_frame: Frame) -> Frame:
+    return get_face_swapper().get(temp_frame, target_face, source_face, paste_back=True)
+
+
+def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
+    if modules.globals.many_faces:
+        many_faces = get_many_faces(temp_frame)
+        if many_faces:
+            for target_face in many_faces:
+                temp_frame = swap_face(source_face, target_face, temp_frame)
+    else:
+        target_face = get_one_face(temp_frame)
+        if target_face:
+            temp_frame = swap_face(source_face, target_face, temp_frame)
+    return temp_frame
+
+
+def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any = None) -> None:
+    source_face = get_one_face(cv2.imread(source_path))
+    for temp_frame_path in temp_frame_paths:
+        temp_frame = cv2.imread(temp_frame_path)
+        try:
+            result = process_frame(source_face, temp_frame)
+            cv2.imwrite(temp_frame_path, result)
+        except Exception as exception:
+            print(exception)
+            pass
+        if progress:
+            progress.update(1)
+
+
+def process_image(source_path: str, target_path: str, output_path: str) -> None:
+    source_face = get_one_face(cv2.imread(source_path))
+    target_frame = cv2.imread(target_path)
+    result = process_frame(source_face, target_frame)
+    cv2.imwrite(output_path, result)
+
+
+def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
+    modules.processors.frame.core.process_video(source_path, temp_frame_paths, process_frames)