Merge pull request #91 from henryruhs/main

Introduce pre_check() and limit_resources()

README.md

@@ -24,18 +24,23 @@ Choose a face (image with desired face) and the target image/video (image/video
 Don't touch the FPS checkbox unless you know what you are doing.
 
 Additional command line arguments are given below:
+
 ```
--h, --help            show this help message and exit
+options:
--f SOURCE_IMG, --face SOURCE_IMG
+  -h, --help            show this help message and exit
+  -f SOURCE_IMG, --face SOURCE_IMG
                         use this face
--t TARGET_PATH, --target TARGET_PATH
+  -t TARGET_PATH, --target TARGET_PATH
                         replace this face
--o OUTPUT_FILE, --output OUTPUT_FILE
+  -o OUTPUT_FILE, --output OUTPUT_FILE
                         save output to this file
---keep-fps            keep original fps
+  --gpu                 use gpu
---gpu                 use gpu
+  --keep-fps            maintain original fps
---keep-frames         don't delete frames directory
+  --keep-frames         keep frames directory
---cores               number of cores to use
+  --max-memory MAX_MEMORY
+                        set max memory
+  --max-cores CORES_COUNT
+                        set max cpu cores
 ```
 
 Looking for a CLI mode? Using the -f/--face argument will make the program in cli mode.

core/config.py

@@ -1,13 +1,20 @@
 import insightface
 import core.globals
 
-face_analyser = insightface.app.FaceAnalysis(name='buffalo_l', providers=core.globals.providers)
+FACE_ANALYSER = None
-face_analyser.prepare(ctx_id=0, det_size=(640, 640))
+
+
+def get_face_analyser():
+    global FACE_ANALYSER
+    if FACE_ANALYSER is None:
+        FACE_ANALYSER = insightface.app.FaceAnalysis(name='buffalo_l', providers=core.globals.providers)
+        FACE_ANALYSER.prepare(ctx_id=0, det_size=(640, 640))
+    return FACE_ANALYSER
 
 
 def get_face(img_data):
-    analysed = face_analyser.get(img_data)
+    face = get_face_analyser().get(img_data)
     try:
-        return sorted(analysed, key=lambda x: x.bbox[0])[0]
+        return sorted(face, key=lambda x: x.bbox[0])[0]
     except IndexError:
         return None

core/processor.py

@@ -1,14 +1,19 @@
 import os
+
 import cv2
 import insightface
-import core.globals
 from core.config import get_face
 from core.utils import rreplace
 
-if os.path.isfile('inswapper_128.onnx'):
+FACE_SWAPPER = None
-    face_swapper = insightface.model_zoo.get_model('inswapper_128.onnx', providers=core.globals.providers)
+
-else:
+
-    quit('File "inswapper_128.onnx" does not exist!')
+def get_face_swapper():
+    global FACE_SWAPPER
+    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)
+    return FACE_SWAPPER
 
 
 def process_video(source_img, frame_paths):
@@ -18,7 +23,7 @@ def process_video(source_img, frame_paths):
         try:
             face = get_face(frame)
             if face:
-                result = face_swapper.get(frame, face, source_face, paste_back=True)
+                result = get_face_swapper().get(frame, face, source_face, paste_back=True)
                 cv2.imwrite(frame_path, result)
                 print('.', end='', flush=True)
             else:

run.py

@@ -1,19 +1,11 @@
 #!/usr/bin/env python3
+
+import platform
 import sys
 import time
+import torch
 import shutil
 import core.globals
-
-if not shutil.which('ffmpeg'):
-    print('ffmpeg is not installed. Read the docs: https://github.com/s0md3v/roop#installation.\n' * 10)
-    quit()
-if '--gpu' not in sys.argv:
-    core.globals.providers = ['CPUExecutionProvider']
-elif 'ROCMExecutionProvider' not in core.globals.providers:
-    import torch
-    if not torch.cuda.is_available():
-        quit("You are using --gpu flag but CUDA isn't available or properly installed on your system.")
-
 import glob
 import argparse
 import multiprocessing as mp
@@ -38,10 +30,11 @@ parser = argparse.ArgumentParser()
 parser.add_argument('-f', '--face', help='use this face', dest='source_img')
 parser.add_argument('-t', '--target', help='replace this face', dest='target_path')
 parser.add_argument('-o', '--output', help='save output to this file', dest='output_file')
-parser.add_argument('--keep-fps', help='maintain original fps', dest='keep_fps', action='store_true', default=False)
 parser.add_argument('--gpu', help='use gpu', dest='gpu', action='store_true', default=False)
+parser.add_argument('--keep-fps', help='maintain original fps', dest='keep_fps', action='store_true', default=False)
 parser.add_argument('--keep-frames', help='keep frames directory', dest='keep_frames', action='store_true', default=False)
-parser.add_argument('--cores', help='number of cores to use', dest='cores_count', type=int, default=psutil.cpu_count()-1)
+parser.add_argument('--max-memory', help='set max memory', default=16, type=int)
+parser.add_argument('--max-cores', help='number of cores to use', dest='cores_count', type=int, default=max(psutil.cpu_count() - 2, 2))
 
 for name, value in vars(parser.parse_args()).items():
     args[name] = value
@@ -51,6 +44,45 @@ if os.name == "nt":
     sep = "\\"
 
 
+def limit_resources():
+    if args['max_memory'] >= 1:
+        memory = args['max_memory'] * 1024 * 1024 * 1024
+        if str(platform.system()).lower() == 'windows':
+            import ctypes
+            kernel32 = ctypes.windll.kernel32
+            kernel32.SetProcessWorkingSetSize(-1, ctypes.c_size_t(memory), ctypes.c_size_t(memory))
+        else:
+            import resource
+            resource.setrlimit(resource.RLIMIT_DATA, (memory, memory))
+
+
+def pre_check():
+    if sys.version_info < (3, 8):
+        quit(f'Python version is not supported - please upgrade to 3.8 or higher')
+    if not shutil.which('ffmpeg'):
+        quit('ffmpeg is not installed!')
+    model_path = os.path.join(os.path.abspath(os.path.dirname(__file__)), 'inswapper_128.onnx')
+    if not os.path.isfile(model_path):
+        quit('File "inswapper_128.onnx" does not exist!')
+    if '--gpu' in sys.argv:
+        CUDA_VERSION = torch.version.cuda
+        CUDNN_VERSION = torch.backends.cudnn.version()
+
+        if 'ROCMExecutionProvider' not in core.globals.providers:
+            if not torch.cuda.is_available() or not CUDA_VERSION:
+                quit("You are using --gpu flag but CUDA isn't available or properly installed on your system.")
+            if CUDA_VERSION > '11.8':
+                quit(f"CUDA version {CUDA_VERSION} is not supported - please downgrade to 11.8.")
+            if CUDA_VERSION < '11.4':
+                quit(f"CUDA version {CUDA_VERSION} is not supported - please upgrade to 11.8")
+            if CUDNN_VERSION < 8220:
+                quit(f"CUDNN version {CUDNN_VERSION} is not supported - please upgrade to 8.9.1")
+            if CUDNN_VERSION > 8910:
+                quit(f"CUDNN version {CUDNN_VERSION} is not supported - please downgrade to 8.9.1")
+    else:
+        core.globals.providers = ['CPUExecutionProvider']
+
+
 def start_processing():
     start_time = time.time()
     if args['gpu']:
@@ -73,6 +105,7 @@ def start_processing():
     print(flush=True)
     print(f"Processing time: {end_time - start_time:.2f} seconds", flush=True)
 
+
 def preview_image(image_path):
     img = Image.open(image_path)
     img = img.resize((180, 180), Image.ANTIALIAS)
@@ -189,6 +222,10 @@ def start():
 
 if __name__ == "__main__":
     global status_label, window
+
+    pre_check()
+    limit_resources()
+
     if args['source_img']:
         args['cli_mode'] = True
         start()