Merge branch 's0md3v:next' into next

roop/processors/frame/core.py

@@ -1,6 +1,6 @@
 import sys
 import importlib
-import threading
+from concurrent.futures import ThreadPoolExecutor
 from typing import Any, List
 from tqdm import tqdm
 
@@ -38,24 +38,13 @@ def get_frame_processors_modules(frame_processors):
 
 
 def multi_process_frame(source_path: str, temp_frame_paths: List[str], process_frames, progress) -> None:
-    threads = []
-    frames_per_thread = len(temp_frame_paths) // roop.globals.execution_threads
-    remaining_frames = len(temp_frame_paths) % roop.globals.execution_threads
-    start_index = 0
-    # create threads by frames
-    for _ in range(roop.globals.execution_threads):
-        end_index = start_index + frames_per_thread
-        if remaining_frames > 0:
-            end_index += 1
-            remaining_frames -= 1
-        thread_paths = temp_frame_paths[start_index:end_index]
-        thread = threading.Thread(target=process_frames, args=(source_path, thread_paths, progress))
-        threads.append(thread)
-        thread.start()
-        start_index = end_index
-    # join threads
-    for thread in threads:
-        thread.join()
+    with ThreadPoolExecutor(max_workers=roop.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: Any) -> None:

roop/processors/frame/face_enhancer.py

@@ -6,7 +6,7 @@ import gfpgan
 import roop.globals
 import roop.processors.frame.core
 from roop.core import update_status
-from roop.face_analyser import get_one_face, get_many_faces
+from roop.face_analyser import get_one_face
 from roop.utilities import conditional_download, resolve_relative_path, is_image, is_video
 
 FACE_ENHANCER = None
@@ -35,53 +35,40 @@ def get_face_enhancer() -> None:
         if FACE_ENHANCER is None:
             model_path = resolve_relative_path('../models/GFPGANv1.3.pth')
             # todo: set models path https://github.com/TencentARC/GFPGAN/issues/399
-            FACE_ENHANCER = gfpgan.GFPGANer(
-                model_path=model_path,
-                channel_multiplier=2
-            )
+            FACE_ENHANCER = gfpgan.GFPGANer(model_path=model_path, upscale=1)
     return FACE_ENHANCER
 
 
-def enhance_face(source_face: Any, target_face: Any, temp_frame: Any) -> Any:
-    THREAD_SEMAPHORE.acquire()
-    if target_face:
+def enhance_face(temp_frame: Any) -> Any:
+    with THREAD_SEMAPHORE:
         _, _, temp_frame = get_face_enhancer().enhance(
             temp_frame,
             paste_back=True
         )
-    THREAD_SEMAPHORE.release()
     return temp_frame
 
 
 def process_frame(source_face: Any, temp_frame: Any) -> Any:
-    if roop.globals.many_faces:
-        many_faces = get_many_faces(temp_frame)
-        if many_faces:
-            for target_face in many_faces:
-                temp_frame = enhance_face(source_face, target_face, temp_frame)
-    else:
-        target_face = get_one_face(temp_frame)
-        if target_face:
-            temp_frame = enhance_face(source_face, target_face, temp_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=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)
-        result = process_frame(source_face, temp_frame)
+        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:
-    source_face = get_one_face(cv2.imread(source_path))
     target_frame = cv2.imread(target_path)
-    result = process_frame(source_face, target_frame)
+    result = process_frame(None, target_frame)
     cv2.imwrite(output_path, result)
 
 
 def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
-    roop.processors.frame.core.process_video(source_path, temp_frame_paths, process_frames)
+    roop.processors.frame.core.process_video(None, temp_frame_paths, process_frames)

roop/processors/frame/face_swapper.py

@@ -44,9 +44,7 @@ def get_face_swapper() -> None:
 
 
 def swap_face(source_face: Any, target_face: Any, temp_frame: Any) -> Any:
-    if target_face:
-        return get_face_swapper().get(temp_frame, target_face, source_face, paste_back=True)
-    return temp_frame
+    return get_face_swapper().get(temp_frame, target_face, source_face, paste_back=True)
 
 
 def process_frame(source_face: Any, temp_frame: Any) -> Any: