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https://github.com/iperov/DeepFaceLab.git
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This commit is contained in:
Colombo
parent
869c5e8dd0
commit
f1a3150ce9
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@ -67,12 +67,16 @@ DeepFaceLab is used by such popular youtube channels as
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||bitcoin:31mPd6DxPCzbpCMZk4k1koWAbErSyqkAXr||
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|Collect facesets|You can collect faceset of any celebrity that can be used in DeepFaceLab and share it [in the community](https://mrdeepfakes.com/forums/forum-celebrity-facesets)|
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</td></tr>
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<tr><td align="center" width="9999">
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## Meme zone
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<p align="center"><img src="doc/DeepFaceLab is working.png"></p>
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</td></tr>
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<tr><td align="center" width="9999">
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<sub>#deepfacelab #deepfakes #faceswap #face-swap #deep-learning #deeplearning #deep-neural-networks #deepface #deep-face-swap #fakeapp #fake-app #neural-networks #neural-nets</sub>
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</td></tr>
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@ -367,6 +367,7 @@ class InteractBase(object):
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def input_in_time (self, str, max_time_sec):
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sq = multiprocessing.Queue()
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p = multiprocessing.Process(target=self.input_process, args=( sys.stdin.fileno(), sq, str))
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p.daemon = True
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p.start()
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t = time.time()
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inp = False
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@ -380,6 +381,25 @@ class InteractBase(object):
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sys.stdin = os.fdopen( sys.stdin.fileno() )
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return inp
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def input_process_skip_pending(self, stdin_fd):
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sys.stdin = os.fdopen(stdin_fd)
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while True:
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try:
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if sys.stdin.isatty():
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sys.stdin.read()
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except:
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pass
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def input_skip_pending(self):
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"""
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skips unnecessary inputs between the dialogs
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"""
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p = multiprocessing.Process(target=self.input_process_skip_pending, args=( sys.stdin.fileno(), ))
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p.daemon = True
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p.start()
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time.sleep(0.5)
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p.terminate()
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sys.stdin = os.fdopen( sys.stdin.fileno() )
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class InteractDesktop(InteractBase):
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@ -38,7 +38,7 @@ class MergeSubprocessor(Subprocessor):
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self.prev_temporal_frame_infos = prev_temporal_frame_infos
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self.frame_info = frame_info
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self.next_temporal_frame_infos = next_temporal_frame_infos
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self.output_filename = None
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self.output_filepath = None
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self.idx = None
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self.cfg = None
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@ -53,14 +53,14 @@ class MergeSubprocessor(Subprocessor):
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prev_temporal_frame_infos=None,
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frame_info=None,
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next_temporal_frame_infos=None,
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output_filename=None,
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output_filepath=None,
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need_return_image = False):
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self.idx = idx
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self.cfg = cfg
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self.prev_temporal_frame_infos = prev_temporal_frame_infos
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self.frame_info = frame_info
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self.next_temporal_frame_infos = next_temporal_frame_infos
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self.output_filename = output_filename
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self.output_filepath = output_filepath
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self.need_return_image = need_return_image
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if self.need_return_image:
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@ -124,34 +124,33 @@ class MergeSubprocessor(Subprocessor):
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frame_info = pf.frame_info
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filename = frame_info.filename
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filepath = frame_info.filepath
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landmarks_list = frame_info.landmarks_list
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filename_path = Path(filename)
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output_filename = pf.output_filename
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output_filepath = pf.output_filepath
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need_return_image = pf.need_return_image
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if len(landmarks_list) == 0:
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self.log_info ( 'no faces found for %s, copying without faces' % (filename_path.name) )
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self.log_info ( 'no faces found for %s, copying without faces' % (filepath.name) )
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if cfg.export_mask_alpha:
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img_bgr = cv2_imread(filename)
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img_bgr = cv2_imread(filepath)
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h,w,c = img_bgr.shape
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if c == 1:
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img_bgr = np.repeat(img_bgr, 3, -1)
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if c == 3:
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img_bgr = np.concatenate ([img_bgr, np.zeros((h,w,1), dtype=img_bgr.dtype) ], axis=-1)
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cv2_imwrite (output_filename, img_bgr)
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cv2_imwrite (output_filepath, img_bgr)
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else:
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if filename_path.suffix == '.png':
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shutil.copy (filename, output_filename )
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if filepath.suffix == '.png':
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shutil.copy ( str(filepath), str(output_filepath) )
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else:
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img_bgr = cv2_imread(filename)
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cv2_imwrite (output_filename, img_bgr)
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img_bgr = cv2_imread(filepath)
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cv2_imwrite (output_filepath, img_bgr)
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if need_return_image:
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img_bgr = cv2_imread(filename)
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img_bgr = cv2_imread(filepath)
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pf.image = img_bgr
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else:
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if cfg.type == MergerConfig.TYPE_MASKED:
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@ -165,7 +164,7 @@ class MergeSubprocessor(Subprocessor):
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if 'MemoryError' in e_str:
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raise Subprocessor.SilenceException
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else:
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raise Exception( 'Error while merging file [%s]: %s' % (filename, e_str) )
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raise Exception( f'Error while merging file [{filepath}]: {e_str}' )
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elif cfg.type == MergerConfig.TYPE_FACE_AVATAR:
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final_img = MergeFaceAvatar (self.predictor_func, self.predictor_input_shape,
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@ -173,8 +172,8 @@ class MergeSubprocessor(Subprocessor):
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pf.frame_info,
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pf.next_temporal_frame_infos )
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if output_filename is not None and final_img is not None:
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cv2_imwrite (output_filename, final_img )
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if output_filepath is not None and final_img is not None:
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cv2_imwrite (output_filepath, final_img )
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if need_return_image:
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pf.image = final_img
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@ -184,10 +183,10 @@ class MergeSubprocessor(Subprocessor):
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#overridable
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def get_data_name (self, pf):
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#return string identificator of your data
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return pf.frame_info.filename
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return pf.frame_info.filepath
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#override
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def __init__(self, is_interactive, merger_session_filepath, predictor_func, predictor_input_shape, merger_config, frames, output_path, model_iter):
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def __init__(self, is_interactive, merger_session_filepath, predictor_func, predictor_input_shape, merger_config, frames, frames_root_path, output_path, model_iter):
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if len (frames) == 0:
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raise ValueError ("len (frames) == 0")
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@ -225,6 +224,7 @@ class MergeSubprocessor(Subprocessor):
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self.fanseg_host, self.fanseg_extract_func = SubprocessFunctionCaller.make_pair(fanseg_extract_func)
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self.frames_root_path = frames_root_path
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self.output_path = output_path
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self.model_iter = model_iter
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@ -232,11 +232,12 @@ class MergeSubprocessor(Subprocessor):
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session_data = None
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if self.is_interactive and self.merger_session_filepath.exists():
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io.input_skip_pending()
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if io.input_bool ("Use saved session?", True):
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try:
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with open( str(self.merger_session_filepath), "rb") as f:
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session_data = pickle.loads(f.read())
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except Exception as e:
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pass
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@ -245,6 +246,7 @@ class MergeSubprocessor(Subprocessor):
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self.frames_done_idxs = []
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if self.is_interactive and session_data is not None:
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# Loaded session data, check it
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s_frames = session_data.get('frames', None)
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s_frames_idxs = session_data.get('frames_idxs', None)
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s_frames_done_idxs = session_data.get('frames_done_idxs', None)
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@ -254,13 +256,14 @@ class MergeSubprocessor(Subprocessor):
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(s_frames_idxs is not None) and \
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(s_frames_done_idxs is not None) and \
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(s_model_iter is not None) and \
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(len(frames) == len(s_frames))
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(len(frames) == len(s_frames)) # frames count must match
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if frames_equal:
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for i in range(len(frames)):
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frame = frames[i]
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s_frame = s_frames[i]
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if frame.frame_info.filename != s_frame.frame_info.filename:
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# frames filenames must match
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if frame.frame_info.filepath.name != s_frame.frame_info.filepath.name:
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frames_equal = False
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if not frames_equal:
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break
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@ -270,25 +273,23 @@ class MergeSubprocessor(Subprocessor):
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for frame in s_frames:
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if frame.cfg is not None:
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#recreate MergerConfig class using constructor with get_config() as dict params
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#so if any new param will be added, old merger session will work properly
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# recreate MergerConfig class using constructor with get_config() as dict params
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# so if any new param will be added, old merger session will work properly
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frame.cfg = frame.cfg.__class__( **frame.cfg.get_config() )
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self.frames = s_frames
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self.frames_idxs = s_frames_idxs
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self.frames_done_idxs = s_frames_done_idxs
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if self.model_iter != s_model_iter:
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#model is more trained, recompute all frames
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rewind_to_begin = len(self.frames_idxs) == 0 # all frames are done?
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if self.model_iter != s_model_iter:
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# model was more trained, recompute all frames
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rewind_to_begin = True
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for frame in self.frames:
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frame.is_done = False
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if self.model_iter != s_model_iter or \
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len(self.frames_idxs) == 0:
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#rewind to begin if model is more trained or all frames are done
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if rewind_to_begin:
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while len(self.frames_done_idxs) > 0:
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prev_frame = self.frames[self.frames_done_idxs.pop()]
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self.frames_idxs.insert(0, prev_frame.idx)
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@ -309,9 +310,7 @@ class MergeSubprocessor(Subprocessor):
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for i in range( len(self.frames) ):
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frame = self.frames[i]
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frame.idx = i
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frame.output_filename = self.output_path / ( Path(frame.frame_info.filename).stem + '.png' )
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frame.output_filepath = self.output_path / ( frame.frame_info.filepath.stem + '.png' )
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#override
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def process_info_generator(self):
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@ -330,7 +329,7 @@ class MergeSubprocessor(Subprocessor):
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#overridable optional
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def on_clients_initialized(self):
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io.progress_bar ("Merging", len (self.frames_idxs), initial=len(self.frames_done_idxs) )
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io.progress_bar ("Merging", len(self.frames_idxs)+len(self.frames_done_idxs), initial=len(self.frames_done_idxs) )
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self.process_remain_frames = not self.is_interactive
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self.is_interactive_quitting = not self.is_interactive
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@ -393,7 +392,7 @@ class MergeSubprocessor(Subprocessor):
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self.screen_manager.finalize()
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for frame in self.frames:
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frame.output_filename = None
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frame.output_filepath = None
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frame.image = None
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session_data = {
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@ -433,10 +432,10 @@ class MergeSubprocessor(Subprocessor):
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if not cur_frame.is_shown:
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if cur_frame.is_done:
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cur_frame.is_shown = True
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io.log_info (cur_frame.cfg.to_string( cur_frame.frame_info.filename_short) )
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io.log_info (cur_frame.cfg.to_string( cur_frame.frame_info.filepath.name) )
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if cur_frame.image is None:
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cur_frame.image = cv2_imread ( cur_frame.output_filename)
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cur_frame.image = cv2_imread ( cur_frame.output_filepath)
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if cur_frame.image is None:
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# unable to read? recompute then
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cur_frame.is_done = False
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@ -474,7 +473,7 @@ class MergeSubprocessor(Subprocessor):
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self.masked_keys_funcs[chr_key](cfg, shift_pressed)
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if prev_cfg != cfg:
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io.log_info ( cfg.to_string(cur_frame.frame_info.filename_short) )
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io.log_info ( cfg.to_string(cur_frame.frame_info.filepath.name) )
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cur_frame.is_done = False
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cur_frame.is_shown = False
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else:
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@ -607,7 +606,7 @@ class MergeSubprocessor(Subprocessor):
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prev_temporal_frame_infos=frame.prev_temporal_frame_infos,
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frame_info=frame.frame_info,
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next_temporal_frame_infos=frame.next_temporal_frame_infos,
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output_filename=frame.output_filename,
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output_filepath=frame.output_filepath,
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need_return_image=True )
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return None
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@ -705,7 +704,7 @@ def main (model_class_name=None,
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if multiple_faces_detected:
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io.log_info ("Warning: multiple faces detected. Strongly recommended to process them separately.")
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frames = [ MergeSubprocessor.Frame( frame_info=FrameInfo(filename=p, landmarks_list=alignments.get(Path(p).stem, None))) for p in input_path_image_paths ]
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frames = [ MergeSubprocessor.Frame( frame_info=FrameInfo(filepath=Path(p), landmarks_list=alignments.get(Path(p).stem, None))) for p in input_path_image_paths ]
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if multiple_faces_detected:
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io.log_info ("Warning: multiple faces detected. Motion blur will not be used.")
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@ -750,9 +749,9 @@ def main (model_class_name=None,
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if dflimg is None:
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io.log_err ("%s is not a dfl image file" % (filepath.name) )
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continue
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filesdata += [ ( FrameInfo(filename=str(filepath), landmarks_list=[dflimg.get_landmarks()] ), dflimg.get_source_filename() ) ]
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filesdata += [ ( FrameInfo(filepath=filepath, landmarks_list=[dflimg.get_landmarks()] ), dflimg.get_source_filename() ) ]
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filesdata = sorted(filesdata, key=operator.itemgetter(1)) #sort by filename
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filesdata = sorted(filesdata, key=operator.itemgetter(1)) #sort by source_filename
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frames = []
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filesdata_len = len(filesdata)
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for i in range(len(filesdata)):
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@ -776,12 +775,13 @@ def main (model_class_name=None,
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io.log_info ("No frames to merge in input_dir.")
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else:
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MergeSubprocessor (
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is_interactive = is_interactive,
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is_interactive = is_interactive,
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merger_session_filepath = merger_session_filepath,
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predictor_func = predictor_func,
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predictor_input_shape = predictor_input_shape,
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merger_config = cfg,
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merger_config = cfg,
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frames = frames,
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frames_root_path = input_path,
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output_path = output_path,
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model_iter = model.get_iter()
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).run()
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@ -1,9 +1,8 @@
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from pathlib import Path
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class FrameInfo(object):
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def __init__(self, filename=None, landmarks_list=None):
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self.filename = filename
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self.filename_short = str(Path(filename).name)
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def __init__(self, filepath=None, landmarks_list=None):
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self.filepath = filepath
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self.landmarks_list = landmarks_list or []
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self.motion_deg = 0
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self.motion_power = 0
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@ -334,7 +334,7 @@ def MergeMaskedFace (predictor_func, predictor_input_shape, cfg, frame_info, img
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def MergeMasked (predictor_func, predictor_input_shape, cfg, frame_info):
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img_bgr_uint8 = cv2_imread(frame_info.filename)
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img_bgr_uint8 = cv2_imread(frame_info.filepath)
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img_bgr_uint8 = imagelib.normalize_channels (img_bgr_uint8, 3)
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img_bgr = img_bgr_uint8.astype(np.float32) / 255.0
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@ -158,6 +158,8 @@ class ModelBase(object):
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self.batch_size = self.load_or_def_option('batch_size', 1)
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#####
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io.input_skip_pending()
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self.on_initialize_options()
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if self.is_first_run():
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# save as default options only for first run model initialize
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