From d05368c361629be7e4b542cc019520a9a8cc17f6 Mon Sep 17 00:00:00 2001
From: Somdev Sangwan <s0md3v@gmail.com>
Date: Sun, 4 Jun 2023 17:17:19 +0530
Subject: [PATCH] revert changes

---
 roop/swapper.py | 71 +++++++++++++++++--------------------------------
 1 file changed, 25 insertions(+), 46 deletions(-)

diff --git a/roop/swapper.py b/roop/swapper.py
index 3e3eca8..9f25b46 100644
--- a/roop/swapper.py
+++ b/roop/swapper.py
@@ -4,20 +4,24 @@ import torch
 import onnxruntime
 import cv2
 import insightface
-import threading
+
 import roop.globals
 from roop.analyser import get_face_single, get_face_many
-from roop.globals import gpu_vendor
 
 FACE_SWAPPER = None
-lock = threading.Lock()
+
 
 def get_face_swapper():
     global FACE_SWAPPER
-    with lock:
-        if FACE_SWAPPER is None:
-            model_path = os.path.join(os.path.abspath(os.path.dirname(__file__)), '../inswapper_128.onnx')
-            FACE_SWAPPER = insightface.model_zoo.get_model(model_path, providers=roop.globals.providers)
+    if FACE_SWAPPER is None:
+        session_options = onnxruntime.SessionOptions()
+        if roop.globals.gpu_vendor is not None:
+            session_options.intra_op_num_threads = roop.globals.gpu_threads
+        else:
+            session_options.intra_op_num_threads = roop.globals.cpu_threads
+        session_options.execution_mode = onnxruntime.ExecutionMode.ORT_PARALLEL
+        model_path = os.path.join(os.path.abspath(os.path.dirname(__file__)), '../inswapper_128.onnx')
+        FACE_SWAPPER = insightface.model_zoo.get_model(model_path, providers=roop.globals.providers, session_options=session_options)
     return FACE_SWAPPER
 
 
@@ -27,20 +31,7 @@ def swap_face_in_frame(source_face, target_face, frame):
     return frame
 
 
-def process_frames(source_img, frame_paths, progress=None):
-    source_face = get_face_single(cv2.imread(source_img))
-    for frame_path in frame_paths:
-        frame = cv2.imread(frame_path)
-        try:
-            result = process_faces(source_face, frame)
-            cv2.imwrite(frame_path, result)
-        except Exception as e:
-            print(">>>>", e)
-            pass
-        if progress:
-            progress.update(1)
-
-def process_faces(source_face, target_frame):
+def process_faces(source_face, target_frame, progress):
     if roop.globals.all_faces:
         many_faces = get_face_many(target_frame)
         if many_faces:
@@ -54,34 +45,22 @@ def process_faces(source_face, target_frame):
 
 
 def process_video(source_img, frame_paths, preview_callback):
+    source_face = get_face_single(cv2.imread(source_img))
     progress_bar_format = '{l_bar}{bar}| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, {rate_fmt}{postfix}]'
 
     with tqdm(total=len(frame_paths), desc="Processing", unit="frame", dynamic_ncols=True, bar_format=progress_bar_format) as progress:
-        # nvidia multi-threading
-        if roop.globals.gpu_vendor == 'nvidia':
-            #progress.set_postfix(cuda_utilization="{:02d}%".format(torch.cuda.utilization()), cuda_memory="{:02d}GB".format(torch.cuda.memory_usage()))
-            # caculate the number of frames each threads processed
-            num_threads = roop.globals.gpu_threads
-            num_frames_per_thread = len(frame_paths) // num_threads
-            remaining_frames = len(frame_paths) % num_threads
-            # create thread list
-            threads = []
-            start_index = 0
-            # create thread and launch
-            for _ in range(num_threads):
-                end_index = start_index + num_frames_per_thread
-                if remaining_frames > 0:
-                    end_index += 1
-                    remaining_frames -= 1
-                thread_frame_paths = frame_paths[start_index:end_index]
-                thread = threading.Thread(target=process_frames, args=(source_img, thread_frame_paths, progress))
-                threads.append(thread)
-                thread.start()
-                start_index = end_index
-            for thread in threads:
-                thread.join()
-        else:
-            process_frames(source_img, frame_paths, progress)
+        for frame_path in frame_paths:
+            if roop.globals.gpu_vendor == 'nvidia':
+                progress.set_postfix(cuda_utilization="{:02d}%".format(torch.cuda.utilization()), cuda_memory="{:02d}GB".format(torch.cuda.memory_usage()))
+            frame = cv2.imread(frame_path)
+            try:
+                result = process_faces(source_face, frame, progress)
+                cv2.imwrite(frame_path, result)
+                if preview_callback:
+                    preview_callback(cv2.cvtColor(result, cv2.COLOR_BGR2RGB))                
+            except Exception:
+                pass
+            progress.update(1)
 
 
 def process_img(source_img, target_path, output_file):