added --cpu-only mode for all stages. Upd readme. Added requirements-cpu.txt

README.md

@@ -14,6 +14,8 @@ Based on original FaceSwap repo. **Facesets** of FaceSwap or FakeApp are **not c
 
 - automatic GPU manager, chooses best gpu(s) and supports --multi-gpu (only for identical cards). Warning: dont use cards in SLI mode.
 
+- cpu mode. 8th gen Intel core CPU able to train H64 model in 2 days.
+
 - new preview window
 
 - extractor in parallel
@@ -156,9 +158,15 @@ dlib==19.10.0 from pip compiled without CUDA. Therefore you have to compile DLIB
 
 Command line example for windows: `python setup.py install -G "Visual Studio 14 2015" --yes DLIB_USE_CUDA`
 
+### **CPU only mode**
+
+CPU mode enabled by arg --cpu-only for all stages. Follow requirements-cpu.txt to install req packages.
+Do not use DLIB extractor in CPU mode, its too slow.
+Only H64 model reasonable to train on home CPU.
+
 ### Prebuilt windows app:
 
-Windows 7,8,8.1,10 zero dependency (just install/update your GeForce Drivers) prebuilt DeepFaceLab can be downloaded from 
+Windows 7,8,8.1,10 zero dependency (just install/update your GeForce Drivers) prebuilt DeepFaceLab (include GPU and CPU versions) can be downloaded from 
 1) torrent https://rutracker.org/forum/viewtopic.php?p=75318742 (magnet link inside).
 2) https://mega.nz/#F!b9MzCK4B!zEAG9txu7uaRUjXz9PtBqg
 

gpufmkmgr/gpufmkmgr.py

@@ -8,13 +8,14 @@ from .pynvml import *
 
         
 dlib_module = None
-def import_dlib(device_idx):
+def import_dlib(device_idx, cpu_only=False):
     global dlib_module
     if dlib_module is not None:
         raise Exception ('Multiple import of dlib is not allowed, reorganize your program.')
         
     import dlib
     dlib_module = dlib
+    if not cpu_only:
         dlib_module.cuda.set_device(device_idx)    
     return dlib_module
 
@@ -152,6 +153,14 @@ def finalize_keras_vggface():
     global keras_vggface_module
     keras_vggface_module = None    
 
+def hasNVML():
+    try:
+        nvmlInit()
+        nvmlShutdown()
+    except:
+        return False
+    return True    
+ 
 #returns [ (device_idx, device_name), ... ]
 def getDevicesWithAtLeastFreeMemory(freememsize):
     result = []
@@ -279,6 +288,8 @@ class GPUConfig():
                         allow_growth = True,
                         cpu_only = False,
                         **in_options):
+        if not hasNVML():
+            cpu_only = True
             
         if cpu_only:
             self.cpu_only = cpu_only

main.py

@@ -37,8 +37,10 @@ if __name__ == "__main__":
             face_type=arguments.face_type,
             detector=arguments.detector,
             multi_gpu=arguments.multi_gpu,
+            cpu_only=arguments.cpu_only,
             manual_fix=arguments.manual_fix,
-            manual_window_size=arguments.manual_window_size)
+            manual_window_size=arguments.manual_window_size
+            )
         
     extract_parser = subparsers.add_parser( "extract", help="Extract the faces from a pictures.")
     extract_parser.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input directory. A directory containing the files you wish to process.")
@@ -49,6 +51,8 @@ if __name__ == "__main__":
     extract_parser.add_argument('--multi-gpu', action="store_true", dest="multi_gpu", default=False, help="Enables multi GPU.")
     extract_parser.add_argument('--manual-fix', action="store_true", dest="manual_fix", default=False, help="Enables manual extract only frames where faces were not recognized.")
     extract_parser.add_argument('--manual-window-size', type=int, dest="manual_window_size", default=0, help="Manual fix window size. Example: 1368. Default: frame size.") 
+    extract_parser.add_argument('--cpu-only', action="store_true", dest="cpu_only", default=False, help="Extract on CPU. Forces to use MT extractor.")    
+    
     
     extract_parser.set_defaults (func=process_extract)
     
@@ -85,6 +89,7 @@ if __name__ == "__main__":
             force_best_gpu_idx = arguments.force_best_gpu_idx,
             multi_gpu          = arguments.multi_gpu,
             force_gpu_idxs     = arguments.force_gpu_idxs,
+            cpu_only           = arguments.cpu_only
             )
         
     train_parser = subparsers.add_parser( "train", help="Trainer") 
@@ -101,6 +106,8 @@ if __name__ == "__main__":
     train_parser.add_argument('--force-best-gpu-idx', type=int, dest="force_best_gpu_idx", default=-1, help="Force to choose this GPU idx as best(worst).")
     train_parser.add_argument('--multi-gpu', action="store_true", dest="multi_gpu", default=False, help="MultiGPU option. It will select only same best(worst) GPU models.")
     train_parser.add_argument('--force-gpu-idxs', type=str, dest="force_gpu_idxs", default=None, help="Override final GPU idxs. Example: 0,1,2.")
+    train_parser.add_argument('--cpu-only', action="store_true", dest="cpu_only", default=False, help="Train on CPU.")    
+    
     train_parser.set_defaults (func=process_train)
     
     def process_convert(arguments):
@@ -197,7 +204,8 @@ if __name__ == "__main__":
             final_image_color_degrade_power = arguments.final_image_color_degrade_power,
             transfercolor = arguments.transfercolor,
             alpha = arguments.alpha,
-            force_best_gpu_idx = arguments.force_best_gpu_idx
+            force_best_gpu_idx = arguments.force_best_gpu_idx,
+            cpu_only = arguments.cpu_only
             )
         
     convert_parser = subparsers.add_parser( "convert", help="Converter") 
@@ -220,6 +228,7 @@ if __name__ == "__main__":
     convert_parser.add_argument('--alpha', action="store_true", dest="alpha", default=False, help="Embeds alpha channel of face mask to final PNG. Used in manual composing video by editors such as Sony Vegas or After Effects.")
     convert_parser.add_argument('--debug', action="store_true", dest="debug", default=False, help="Debug converter.")
     convert_parser.add_argument('--force-best-gpu-idx', type=int, dest="force_best_gpu_idx", default=-1, help="Force to choose this GPU idx as best.")
+    convert_parser.add_argument('--cpu-only', action="store_true", dest="cpu_only", default=False, help="Convert on CPU.")
     
     convert_parser.set_defaults(func=process_convert)
 

mainscripts/Extractor.py

@@ -18,13 +18,14 @@ from utils.SubprocessorBase import SubprocessorBase
 class ExtractSubprocessor(SubprocessorBase):
 
     #override
-    def __init__(self, input_data, type, image_size, face_type, debug, multi_gpu=False, manual=False, manual_window_size=0, detector=None, output_path=None ): 
+    def __init__(self, input_data, type, image_size, face_type, debug, multi_gpu=False, cpu_only=False, manual=False, manual_window_size=0, detector=None, output_path=None ): 
         self.input_data = input_data
         self.type = type
         self.image_size = image_size
         self.face_type = face_type
         self.debug = debug        
         self.multi_gpu = multi_gpu
+        self.cpu_only = cpu_only
         self.detector = detector
         self.output_path = output_path        
         self.manual = manual        
@@ -59,8 +60,10 @@ class ExtractSubprocessor(SubprocessorBase):
                     
             cv2.setMouseCallback(self.wnd_name, onMouse, self.param)
     
-    def get_devices_for_type (self, type, multi_gpu):
+    def get_devices_for_type (self, type, multi_gpu, cpu_only):
-        if (type == 'rects' or type == 'landmarks'):
+        if cpu_only:
+            devices = [ (0, 'CPU', 0 ) ]
+        elif (type == 'rects' or type == 'landmarks'):
             if not multi_gpu:            
                 devices = [gpufmkmgr.getBestDeviceIdx()]
             else:
@@ -74,9 +77,12 @@ class ExtractSubprocessor(SubprocessorBase):
         
     #override
     def process_info_generator(self):    
-        for (device_idx, device_name, device_total_vram_gb) in self.get_devices_for_type(self.type, self.multi_gpu): 
+        for (device_idx, device_name, device_total_vram_gb) in self.get_devices_for_type(self.type, self.multi_gpu, self.cpu_only): 
             num_processes = 1
             if not self.manual and self.type == 'rects' and self.detector == 'mt':
+                if self.cpu_only:
+                    num_processes = int ( max (1, multiprocessing.cpu_count() / 2 ) )
+                else:
                     num_processes = int ( max (1, device_total_vram_gb / 2) )
                 
             for i in range(0, num_processes ):
@@ -84,6 +90,7 @@ class ExtractSubprocessor(SubprocessorBase):
                 yield device_name_for_process, {}, {'type' : self.type, 
                                                     'device_idx' : device_idx,
                                                     'device_name' : device_name_for_process, 
+                                                    'device_type' : 'CPU' if self.cpu_only else 'GPU',
                                                     'image_size': self.image_size, 
                                                     'face_type': self.face_type, 
                                                     'debug': self.debug, 
@@ -229,6 +236,7 @@ class ExtractSubprocessor(SubprocessorBase):
         self.image_size   = client_dict['image_size']
         self.face_type    = client_dict['face_type']
         self.device_idx   = client_dict['device_idx']
+        self.cpu_only     = client_dict['device_type'] == 'CPU'
         self.output_path  = Path(client_dict['output_dir']) if 'output_dir' in client_dict.keys() else None        
         self.debug        = client_dict['debug']
         self.detector     = client_dict['detector']
@@ -242,18 +250,18 @@ class ExtractSubprocessor(SubprocessorBase):
             if self.detector is not None:
                 if self.detector == 'mt':
                 
-                    self.gpu_config = gpufmkmgr.GPUConfig ( force_best_gpu_idx=self.device_idx, allow_growth=True)                
+                    self.gpu_config = gpufmkmgr.GPUConfig ( cpu_only=self.cpu_only, force_best_gpu_idx=self.device_idx, allow_growth=True)                
                     self.tf = gpufmkmgr.import_tf ( self.gpu_config )
                     self.tf_session = gpufmkmgr.get_tf_session()
                     self.keras = gpufmkmgr.import_keras()
                     self.e = facelib.MTCExtractor(self.keras, self.tf, self.tf_session)                            
                 elif self.detector == 'dlib':
-                    self.dlib = gpufmkmgr.import_dlib( self.device_idx )
+                    self.dlib = gpufmkmgr.import_dlib( self.device_idx, cpu_only=self.cpu_only )
                     self.e = facelib.DLIBExtractor(self.dlib)
                 self.e.__enter__()
 
         elif self.type == 'landmarks':
-            self.gpu_config = gpufmkmgr.GPUConfig ( force_best_gpu_idx=self.device_idx, allow_growth=True)                
+            self.gpu_config = gpufmkmgr.GPUConfig ( cpu_only=self.cpu_only, force_best_gpu_idx=self.device_idx, allow_growth=True)                
             self.tf = gpufmkmgr.import_tf ( self.gpu_config )
             self.tf_session = gpufmkmgr.get_tf_session()
             self.keras = gpufmkmgr.import_keras()
@@ -381,7 +389,7 @@ face_type
     'full_face'
     'avatar'
 '''
-def main (input_dir, output_dir, debug, detector='mt', multi_gpu=True, manual_fix=False, manual_window_size=0, image_size=256, face_type='full_face'):
+def main (input_dir, output_dir, debug, detector='mt', multi_gpu=True, cpu_only=False, manual_fix=False, manual_window_size=0, image_size=256, face_type='full_face'):
     print ("Running extractor.\r\n")
 
     input_path = Path(input_dir)
@@ -412,13 +420,13 @@ def main (input_dir, output_dir, debug, detector='mt', multi_gpu=True, manual_fi
     if images_found != 0:    
         if detector == 'manual':
             print ('Performing manual extract...')
-            extracted_faces = ExtractSubprocessor ([ (filename,[]) for filename in input_path_image_paths ], 'landmarks', image_size, face_type, debug, manual=True, manual_window_size=manual_window_size).process()
+            extracted_faces = ExtractSubprocessor ([ (filename,[]) for filename in input_path_image_paths ], 'landmarks', image_size, face_type, debug, cpu_only=cpu_only, manual=True, manual_window_size=manual_window_size).process()
         else:
             print ('Performing 1st pass...')
-            extracted_rects = ExtractSubprocessor ([ (x,) for x in input_path_image_paths ], 'rects', image_size, face_type, debug, multi_gpu=multi_gpu, manual=False, detector=detector).process()
+            extracted_rects = ExtractSubprocessor ([ (x,) for x in input_path_image_paths ], 'rects', image_size, face_type, debug, multi_gpu=multi_gpu, cpu_only=cpu_only, manual=False, detector=detector).process()
                 
             print ('Performing 2nd pass...')
-            extracted_faces = ExtractSubprocessor (extracted_rects, 'landmarks', image_size, face_type, debug, multi_gpu=multi_gpu, manual=False).process()
+            extracted_faces = ExtractSubprocessor (extracted_rects, 'landmarks', image_size, face_type, debug, multi_gpu=multi_gpu, cpu_only=cpu_only, manual=False).process()
                 
             if manual_fix:
                 print ('Performing manual fix...')
@@ -430,7 +438,7 @@ def main (input_dir, output_dir, debug, detector='mt', multi_gpu=True, manual_fi
 
         if len(extracted_faces) > 0:
             print ('Performing 3rd pass...')
-            final_imgs_paths = ExtractSubprocessor (extracted_faces, 'final', image_size, face_type, debug, multi_gpu=multi_gpu, manual=False, output_path=output_path).process()
+            final_imgs_paths = ExtractSubprocessor (extracted_faces, 'final', image_size, face_type, debug, multi_gpu=multi_gpu, cpu_only=cpu_only, manual=False, output_path=output_path).process()
             faces_detected = len(final_imgs_paths)
             
     print('-------------------------')

models/ModelBase.py

@@ -118,10 +118,13 @@ class ModelBase(object):
             print ("== |== %s : %s" % (key, self.options[key]) )        
         
         print ("== Running on:")
+        if self.gpu_config.cpu_only:
+            print ("== |== [CPU]")
+        else:
             for idx in self.gpu_config.gpu_idxs:
                 print ("== |== [%d : %s]" % (idx, gpufmkmgr.getDeviceName(idx)) )
  
-        if self.gpu_total_vram_gb == 2:
+        if not self.gpu_config.cpu_only and self.gpu_total_vram_gb == 2:
             print ("==")
             print ("== WARNING: You are using 2GB GPU. Result quality may be significantly decreased.")
             print ("== If training does not start, close all programs and try again.")
@@ -264,6 +267,9 @@ class ModelBase(object):
         self.epoch += 1
         
         #............."Saving... 
+        if epoch_time >= 10000:
+            loss_string = "Training [#{0:06d}][{1:03d}s]".format ( self.epoch, epoch_time / 1000 )
+        else:
             loss_string = "Training [#{0:06d}][{1:04d}ms]".format ( self.epoch, int(epoch_time*1000) % 10000 )
         for (loss_name, loss_value) in losses:
             loss_string += " %s:%.3f" % (loss_name, loss_value)
@@ -301,6 +307,10 @@ class ModelBase(object):
         #example d = {2:2,3:4,4:8,5:16,6:32,7:32,8:32,9:48} 
         keys = [x for x in d.keys()]
         
+        if self.gpu_config.cpu_only:
+            if self.batch_size == 0:
+                self.batch_size = 2
+        else:
             if self.gpu_total_vram_gb < keys[0]:
                 raise Exception ('Sorry, this model works only on %dGB+ GPU' % ( keys[0] ) )
 

requirements-cpu.txt

@@ -0,0 +1,10 @@
+pathlib==1.0.1
+scandir==1.6
+h5py==2.7.1
+Keras==2.2.4
+opencv-python==3.4.0.12
+tensorflow==1.11.0
+scikit-image
+dlib==19.10.0
+tqdm
+git+https://www.github.com/keras-team/keras-contrib.git