def superres_func(face_bgr):
if self.face_enhancer is None:
self.face_enhancer = FaceEnhancer(place_model_on_cpu=True)
return self.face_enhancer.enhance(face_bgr,
is_tanh=True,
preserve_size=False)
class Cli(Subprocessor.Cli):
#override
def on_initialize(self, client_dict):
device_idx = client_dict['device_idx']
cpu_only = client_dict['device_type'] == 'CPU'
self.output_dirpath = client_dict['output_dirpath']
nn_initialize_mp_lock = client_dict['nn_initialize_mp_lock']
if cpu_only:
device_config = nn.DeviceConfig.CPU()
device_vram = 99
else:
device_config = nn.DeviceConfig.GPUIndexes([device_idx])
device_vram = device_config.devices[0].total_mem_gb
nn.initialize(device_config)
intro_str = 'Running on %s.' % (client_dict['device_name'])
self.log_info(intro_str)
from facelib import FaceEnhancer
self.fe = FaceEnhancer(place_model_on_cpu=(device_vram <= 2
or cpu_only),
run_on_cpu=cpu_only)
#override
def process_data(self, filepath):
try:
dflimg = DFLIMG.load(filepath)
if dflimg is None or not dflimg.has_data():
self.log_err(f"{filepath.name} is not a dfl image file")
else:
dfl_dict = dflimg.get_dict()
img = cv2_imread(filepath).astype(np.float32) / 255.0
img = self.fe.enhance(img)
img = np.clip(img * 255, 0, 255).astype(np.uint8)
output_filepath = self.output_dirpath / filepath.name
cv2_imwrite(str(output_filepath), img,
[int(cv2.IMWRITE_JPEG_QUALITY), 100])
dflimg = DFLIMG.load(output_filepath)
dflimg.set_dict(dfl_dict)
dflimg.save()
return (1, filepath, output_filepath)
except:
self.log_err(
f"Exception occured while processing file {filepath}. Error: {traceback.format_exc()}"
)
return (0, filepath, None)
def on_initialize(self, client_dict):
device_idx = client_dict['device_idx']
cpu_only = client_dict['device_type'] == 'CPU'
self.output_dirpath = client_dict['output_dirpath']
device_config = nnlib.DeviceConfig(cpu_only=cpu_only,
force_gpu_idx=device_idx,
allow_growth=True)
nnlib.import_all(device_config)
device_vram = device_config.gpu_vram_gb[0]
intro_str = 'Running on %s.' % (client_dict['device_name'])
if not cpu_only and device_vram <= 2:
intro_str += " Recommended to close all programs using this device."
self.log_info(intro_str)
from facelib import FaceEnhancer
self.fe = FaceEnhancer()
def on_initialize(self, client_dict):
device_idx = client_dict['device_idx']
cpu_only = client_dict['device_type'] == 'CPU'
self.output_dirpath = client_dict['output_dirpath']
nn_initialize_mp_lock = client_dict['nn_initialize_mp_lock']
if cpu_only:
device_config = nn.DeviceConfig.CPU()
device_vram = 99
else:
device_config = nn.DeviceConfig.GPUIndexes([device_idx])
device_vram = device_config.devices[0].total_mem_gb
nn.initialize(device_config)
intro_str = 'Running on %s.' % (client_dict['device_name'])
self.log_info(intro_str)
from facelib import FaceEnhancer
self.fe = FaceEnhancer(place_model_on_cpu=(device_vram <= 2))
class Cli(Subprocessor.Cli):
#override
def on_initialize(self, client_dict):
device_idx = client_dict['device_idx']
cpu_only = client_dict['device_type'] == 'CPU'
self.output_dirpath = client_dict['output_dirpath']
device_config = nnlib.DeviceConfig(cpu_only=cpu_only,
force_gpu_idx=device_idx,
allow_growth=True)
nnlib.import_all(device_config)
device_vram = device_config.gpu_vram_gb[0]
intro_str = 'Running on %s.' % (client_dict['device_name'])
if not cpu_only and device_vram <= 2:
intro_str += " Recommended to close all programs using this device."
self.log_info(intro_str)
from facelib import FaceEnhancer
self.fe = FaceEnhancer()
#override
def process_data(self, filepath):
try:
dflimg = DFLIMG.load(filepath)
if dflimg is None:
self.log_err("%s is not a dfl image file" %
(filepath.name))
else:
img = cv2_imread(filepath).astype(np.float32) / 255.0
img = self.fe.enhance(img)
img = np.clip(img * 255, 0, 255).astype(np.uint8)
output_filepath = self.output_dirpath / filepath.name
cv2_imwrite(str(output_filepath), img,
[int(cv2.IMWRITE_JPEG_QUALITY), 100])
dflimg.embed_and_set(str(output_filepath))
return (1, filepath, output_filepath)
except:
self.log_err(
f"Exception occured while processing file {filepath}. Error: {traceback.format_exc()}"
)
return (0, filepath, None)
class MergeSubprocessor(Subprocessor):
class Frame(object):
def __init__(self,
prev_temporal_frame_infos=None,
frame_info=None,
next_temporal_frame_infos=None):
self.prev_temporal_frame_infos = prev_temporal_frame_infos
self.frame_info = frame_info
self.next_temporal_frame_infos = next_temporal_frame_infos
self.output_filepath = None
self.idx = None
self.cfg = None
self.is_done = False
self.is_processing = False
self.is_shown = False
self.image = None
class ProcessingFrame(object):
def __init__(self,
idx=None,
cfg=None,
prev_temporal_frame_infos=None,
frame_info=None,
next_temporal_frame_infos=None,
output_filepath=None,
need_return_image=False):
self.idx = idx
self.cfg = cfg
self.prev_temporal_frame_infos = prev_temporal_frame_infos
self.frame_info = frame_info
self.next_temporal_frame_infos = next_temporal_frame_infos
self.output_filepath = output_filepath
self.need_return_image = need_return_image
if self.need_return_image:
self.image = None
class Cli(Subprocessor.Cli):
#override
def on_initialize(self, client_dict):
self.log_info('Running on %s.' % (client_dict['device_name']))
self.device_idx = client_dict['device_idx']
self.device_name = client_dict['device_name']
self.predictor_func = client_dict['predictor_func']
self.predictor_input_shape = client_dict['predictor_input_shape']
self.superres_func = client_dict['superres_func']
self.fanseg_input_size = client_dict['fanseg_input_size']
self.fanseg_extract_func = client_dict['fanseg_extract_func']
#transfer and set stdin in order to work code.interact in debug subprocess
stdin_fd = client_dict['stdin_fd']
if stdin_fd is not None:
sys.stdin = os.fdopen(stdin_fd)
def blursharpen_func(img,
sharpen_mode=0,
kernel_size=3,
amount=100):
if kernel_size % 2 == 0:
kernel_size += 1
if amount > 0:
if sharpen_mode == 1: #box
kernel = np.zeros((kernel_size, kernel_size),
dtype=np.float32)
kernel[kernel_size // 2, kernel_size // 2] = 1.0
box_filter = np.ones(
(kernel_size, kernel_size),
dtype=np.float32) / (kernel_size**2)
kernel = kernel + (kernel - box_filter) * amount
return cv2.filter2D(img, -1, kernel)
elif sharpen_mode == 2: #gaussian
blur = cv2.GaussianBlur(img,
(kernel_size, kernel_size), 0)
img = cv2.addWeighted(img, 1.0 + (0.5 * amount), blur,
-(0.5 * amount), 0)
return img
elif amount < 0:
n = -amount
while n > 0:
img_blur = cv2.medianBlur(img, 5)
if int(n / 10) != 0:
img = img_blur
else:
pass_power = (n % 10) / 10.0
img = img * (1.0 -
pass_power) + img_blur * pass_power
n = max(n - 10, 0)
return img
return img
self.blursharpen_func = blursharpen_func
return None
#override
def process_data(self, pf): #pf=ProcessingFrame
cfg = pf.cfg.copy()
cfg.blursharpen_func = self.blursharpen_func
cfg.superres_func = self.superres_func
frame_info = pf.frame_info
filepath = frame_info.filepath
landmarks_list = frame_info.landmarks_list
output_filepath = pf.output_filepath
need_return_image = pf.need_return_image
if len(landmarks_list) == 0:
self.log_info('no faces found for %s, copying without faces' %
(filepath.name))
if cfg.export_mask_alpha:
img_bgr = cv2_imread(filepath)
h, w, c = img_bgr.shape
if c == 1:
img_bgr = np.repeat(img_bgr, 3, -1)
if c == 3:
img_bgr = np.concatenate([
img_bgr,
np.zeros((h, w, 1), dtype=img_bgr.dtype)
],
axis=-1)
cv2_imwrite(output_filepath, img_bgr)
else:
if filepath.suffix == '.png':
shutil.copy(str(filepath), str(output_filepath))
else:
img_bgr = cv2_imread(filepath)
cv2_imwrite(output_filepath, img_bgr)
if need_return_image:
img_bgr = cv2_imread(filepath)
pf.image = img_bgr
else:
if cfg.type == MergerConfig.TYPE_MASKED:
cfg.fanseg_input_size = self.fanseg_input_size
cfg.fanseg_extract_func = self.fanseg_extract_func
try:
final_img = MergeMasked(self.predictor_func,
self.predictor_input_shape,
cfg, frame_info)
except Exception as e:
e_str = traceback.format_exc()
if 'MemoryError' in e_str:
raise Subprocessor.SilenceException
else:
raise Exception(
f'Error while merging file [{filepath}]: {e_str}'
)
elif cfg.type == MergerConfig.TYPE_FACE_AVATAR:
final_img = MergeFaceAvatar(self.predictor_func,
self.predictor_input_shape,
cfg,
pf.prev_temporal_frame_infos,
pf.frame_info,
pf.next_temporal_frame_infos)
if output_filepath is not None and final_img is not None:
cv2_imwrite(output_filepath, final_img)
if need_return_image:
pf.image = final_img
return pf
#overridable
def get_data_name(self, pf):
#return string identificator of your data
return pf.frame_info.filepath
#override
def __init__(self, is_interactive, merger_session_filepath, predictor_func,
predictor_input_shape, merger_config, frames,
frames_root_path, output_path, model_iter):
if len(frames) == 0:
raise ValueError("len (frames) == 0")
super().__init__('Merger',
MergeSubprocessor.Cli,
86400 if MERGER_DEBUG else 60,
io_loop_sleep_time=0.001)
self.is_interactive = is_interactive
self.merger_session_filepath = Path(merger_session_filepath)
self.merger_config = merger_config
self.predictor_func_host, self.predictor_func = SubprocessFunctionCaller.make_pair(
predictor_func)
self.predictor_input_shape = predictor_input_shape
self.face_enhancer = None
def superres_func(mode, face_bgr):
if mode == 1:
if self.face_enhancer is None:
self.face_enhancer = FaceEnhancer(place_model_on_cpu=True)
return self.face_enhancer.enhance(face_bgr,
is_tanh=True,
preserve_size=False)
self.superres_host, self.superres_func = SubprocessFunctionCaller.make_pair(
superres_func)
self.fanseg_by_face_type = {}
self.fanseg_input_size = 256
def fanseg_extract_func(face_type, *args, **kwargs):
fanseg = self.fanseg_by_face_type.get(face_type, None)
if self.fanseg_by_face_type.get(face_type, None) is None:
cpu_only = len(nn.getCurrentDeviceConfig().devices) == 0
with nn.tf.device('/CPU:0' if cpu_only else '/GPU:0'):
fanseg = TernausNet("FANSeg",
self.fanseg_input_size,
FaceType.toString(face_type),
place_model_on_cpu=True)
self.fanseg_by_face_type[face_type] = fanseg
return fanseg.extract(*args, **kwargs)
self.fanseg_host, self.fanseg_extract_func = SubprocessFunctionCaller.make_pair(
fanseg_extract_func)
self.frames_root_path = frames_root_path
self.output_path = output_path
self.model_iter = model_iter
self.prefetch_frame_count = self.process_count = min(
6, multiprocessing.cpu_count())
session_data = None
if self.is_interactive and self.merger_session_filepath.exists():
io.input_skip_pending()
if io.input_bool("Use saved session?", True):
try:
with open(str(self.merger_session_filepath), "rb") as f:
session_data = pickle.loads(f.read())
except Exception as e:
pass
self.frames = frames
self.frames_idxs = [*range(len(self.frames))]
self.frames_done_idxs = []
if self.is_interactive and session_data is not None:
# Loaded session data, check it
s_frames = session_data.get('frames', None)
s_frames_idxs = session_data.get('frames_idxs', None)
s_frames_done_idxs = session_data.get('frames_done_idxs', None)
s_model_iter = session_data.get('model_iter', None)
frames_equal = (s_frames is not None) and \
(s_frames_idxs is not None) and \
(s_frames_done_idxs is not None) and \
(s_model_iter is not None) and \
(len(frames) == len(s_frames)) # frames count must match
if frames_equal:
for i in range(len(frames)):
frame = frames[i]
s_frame = s_frames[i]
# frames filenames must match
if frame.frame_info.filepath.name != s_frame.frame_info.filepath.name:
frames_equal = False
if not frames_equal:
break
if frames_equal:
io.log_info('Using saved session from ' +
'/'.join(self.merger_session_filepath.parts[-2:]))
for frame in s_frames:
if frame.cfg is not None:
# recreate MergerConfig class using constructor with get_config() as dict params
# so if any new param will be added, old merger session will work properly
frame.cfg = frame.cfg.__class__(
**frame.cfg.get_config())
self.frames = s_frames
self.frames_idxs = s_frames_idxs
self.frames_done_idxs = s_frames_done_idxs
rewind_to_begin = len(
self.frames_idxs) == 0 # all frames are done?
if self.model_iter != s_model_iter:
# model was more trained, recompute all frames
rewind_to_begin = True
for frame in self.frames:
frame.is_done = False
if rewind_to_begin:
while len(self.frames_done_idxs) > 0:
prev_frame = self.frames[self.frames_done_idxs.pop()]
self.frames_idxs.insert(0, prev_frame.idx)
if len(self.frames_idxs) != 0:
cur_frame = self.frames[self.frames_idxs[0]]
cur_frame.is_shown = False
if not frames_equal:
session_data = None
if session_data is None:
for filename in pathex.get_image_paths(
self.output_path): #remove all images in output_path
Path(filename).unlink()
frames[0].cfg = self.merger_config.copy()
for i in range(len(self.frames)):
frame = self.frames[i]
frame.idx = i
frame.output_filepath = self.output_path / (
frame.frame_info.filepath.stem + '.png')
#override
def process_info_generator(self):
r = [0] if MERGER_DEBUG else range(self.process_count)
for i in r:
yield 'CPU%d' % (i), {}, {
'device_idx': i,
'device_name': 'CPU%d' % (i),
'predictor_func': self.predictor_func,
'predictor_input_shape': self.predictor_input_shape,
'superres_func': self.superres_func,
'fanseg_input_size': self.fanseg_input_size,
'fanseg_extract_func': self.fanseg_extract_func,
'stdin_fd': sys.stdin.fileno() if MERGER_DEBUG else None
}
#overridable optional
def on_clients_initialized(self):
io.progress_bar("Merging",
len(self.frames_idxs) + len(self.frames_done_idxs),
initial=len(self.frames_done_idxs))
self.process_remain_frames = not self.is_interactive
self.is_interactive_quitting = not self.is_interactive
if self.is_interactive:
help_images = {
MergerConfig.TYPE_MASKED:
cv2_imread(
str(
Path(__file__).parent / 'gfx' /
'help_merger_masked.jpg')),
MergerConfig.TYPE_FACE_AVATAR:
cv2_imread(
str(
Path(__file__).parent / 'gfx' /
'help_merger_face_avatar.jpg')),
}
self.main_screen = Screen(initial_scale_to_width=1368,
image=None,
waiting_icon=True)
self.help_screen = Screen(
initial_scale_to_height=768,
image=help_images[self.merger_config.type],
waiting_icon=False)
self.screen_manager = ScreenManager(
"Merger", [self.main_screen, self.help_screen],
capture_keys=True)
self.screen_manager.set_current(self.help_screen)
self.screen_manager.show_current()
self.masked_keys_funcs = {
'`':
lambda cfg, shift_pressed: cfg.set_mode(0),
'1':
lambda cfg, shift_pressed: cfg.set_mode(1),
'2':
lambda cfg, shift_pressed: cfg.set_mode(2),
'3':
lambda cfg, shift_pressed: cfg.set_mode(3),
'4':
lambda cfg, shift_pressed: cfg.set_mode(4),
'5':
lambda cfg, shift_pressed: cfg.set_mode(5),
'6':
lambda cfg, shift_pressed: cfg.set_mode(6),
'7':
lambda cfg, shift_pressed: cfg.set_mode(7),
'8':
lambda cfg, shift_pressed: cfg.set_mode(8),
'q':
lambda cfg, shift_pressed: cfg.add_hist_match_threshold(
1 if not shift_pressed else 5),
'a':
lambda cfg, shift_pressed: cfg.add_hist_match_threshold(
-1 if not shift_pressed else -5),
'w':
lambda cfg, shift_pressed: cfg.add_erode_mask_modifier(
1 if not shift_pressed else 5),
's':
lambda cfg, shift_pressed: cfg.add_erode_mask_modifier(
-1 if not shift_pressed else -5),
'e':
lambda cfg, shift_pressed: cfg.add_blur_mask_modifier(
1 if not shift_pressed else 5),
'd':
lambda cfg, shift_pressed: cfg.add_blur_mask_modifier(
-1 if not shift_pressed else -5),
'r':
lambda cfg, shift_pressed: cfg.add_motion_blur_power(
1 if not shift_pressed else 5),
'f':
lambda cfg, shift_pressed: cfg.add_motion_blur_power(
-1 if not shift_pressed else -5),
'y':
lambda cfg, shift_pressed: cfg.add_blursharpen_amount(
1 if not shift_pressed else 5),
'h':
lambda cfg, shift_pressed: cfg.add_blursharpen_amount(
-1 if not shift_pressed else -5),
'u':
lambda cfg, shift_pressed: cfg.add_output_face_scale(
1 if not shift_pressed else 5),
'j':
lambda cfg, shift_pressed: cfg.add_output_face_scale(
-1 if not shift_pressed else -5),
'i':
lambda cfg, shift_pressed: cfg.add_image_denoise_power(
1 if not shift_pressed else 5),
'k':
lambda cfg, shift_pressed: cfg.add_image_denoise_power(
-1 if not shift_pressed else -5),
'o':
lambda cfg, shift_pressed: cfg.add_bicubic_degrade_power(
1 if not shift_pressed else 5),
'l':
lambda cfg, shift_pressed: cfg.add_bicubic_degrade_power(
-1 if not shift_pressed else -5),
'p':
lambda cfg, shift_pressed: cfg.add_color_degrade_power(
1 if not shift_pressed else 5),
';':
lambda cfg, shift_pressed: cfg.add_color_degrade_power(-1),
':':
lambda cfg, shift_pressed: cfg.add_color_degrade_power(-5),
'z':
lambda cfg, shift_pressed: cfg.toggle_masked_hist_match(),
'x':
lambda cfg, shift_pressed: cfg.toggle_mask_mode(),
'c':
lambda cfg, shift_pressed: cfg.toggle_color_transfer_mode(),
'v':
lambda cfg, shift_pressed: cfg.toggle_super_resolution_mode(),
'b':
lambda cfg, shift_pressed: cfg.toggle_export_mask_alpha(),
'n':
lambda cfg, shift_pressed: cfg.toggle_sharpen_mode(),
}
self.masked_keys = list(self.masked_keys_funcs.keys())
#overridable optional
def on_clients_finalized(self):
io.progress_bar_close()
if self.is_interactive:
self.screen_manager.finalize()
for frame in self.frames:
frame.output_filepath = None
frame.image = None
session_data = {
'frames': self.frames,
'frames_idxs': self.frames_idxs,
'frames_done_idxs': self.frames_done_idxs,
'model_iter': self.model_iter,
}
self.merger_session_filepath.write_bytes(
pickle.dumps(session_data))
io.log_info("Session is saved to " +
'/'.join(self.merger_session_filepath.parts[-2:]))
#override
def on_tick(self):
self.predictor_func_host.process_messages()
self.superres_host.process_messages()
self.fanseg_host.process_messages()
go_prev_frame = False
go_first_frame = False
go_prev_frame_overriding_cfg = False
go_first_frame_overriding_cfg = False
go_next_frame = self.process_remain_frames
go_next_frame_overriding_cfg = False
go_last_frame_overriding_cfg = False
cur_frame = None
if len(self.frames_idxs) != 0:
cur_frame = self.frames[self.frames_idxs[0]]
if self.is_interactive:
self.main_screen.set_waiting_icon(False)
if not self.is_interactive_quitting and not self.process_remain_frames:
if cur_frame is not None:
if not cur_frame.is_shown:
if cur_frame.is_done:
cur_frame.is_shown = True
io.log_info(
cur_frame.cfg.to_string(
cur_frame.frame_info.filepath.name))
if cur_frame.image is None:
cur_frame.image = cv2_imread(
cur_frame.output_filepath)
if cur_frame.image is None:
# unable to read? recompute then
cur_frame.is_done = False
cur_frame.is_shown = False
self.main_screen.set_image(cur_frame.image)
else:
self.main_screen.set_waiting_icon(True)
else:
self.main_screen.set_image(None)
else:
self.main_screen.set_image(None)
self.main_screen.set_waiting_icon(True)
self.screen_manager.show_current()
key_events = self.screen_manager.get_key_events()
key, chr_key, ctrl_pressed, alt_pressed, shift_pressed = key_events[
-1] if len(key_events) > 0 else (0, 0, False, False, False)
if key == 9: #tab
self.screen_manager.switch_screens()
else:
if key == 27: #esc
self.is_interactive_quitting = True
elif self.screen_manager.get_current() is self.main_screen:
if self.merger_config.type == MergerConfig.TYPE_MASKED and chr_key in self.masked_keys:
self.process_remain_frames = False
if cur_frame is not None:
cfg = cur_frame.cfg
prev_cfg = cfg.copy()
if cfg.type == MergerConfig.TYPE_MASKED:
self.masked_keys_funcs[chr_key](cfg,
shift_pressed)
if prev_cfg != cfg:
io.log_info(
cfg.to_string(
cur_frame.frame_info.filepath.name))
cur_frame.is_done = False
cur_frame.is_shown = False
else:
if chr_key == ',' or chr_key == 'm':
self.process_remain_frames = False
go_prev_frame = True
if chr_key == ',':
if shift_pressed:
go_first_frame = True
elif chr_key == 'm':
if not shift_pressed:
go_prev_frame_overriding_cfg = True
else:
go_first_frame_overriding_cfg = True
elif chr_key == '.' or chr_key == '/':
self.process_remain_frames = False
go_next_frame = True
if chr_key == '.':
if shift_pressed:
self.process_remain_frames = not self.process_remain_frames
elif chr_key == '/':
if not shift_pressed:
go_next_frame_overriding_cfg = True
else:
go_last_frame_overriding_cfg = True
elif chr_key == '-':
self.screen_manager.get_current().diff_scale(-0.1)
elif chr_key == '=':
self.screen_manager.get_current().diff_scale(0.1)
if go_prev_frame:
if cur_frame is None or cur_frame.is_done:
if cur_frame is not None:
cur_frame.image = None
while True:
if len(self.frames_done_idxs) > 0:
prev_frame = self.frames[self.frames_done_idxs.pop()]
self.frames_idxs.insert(0, prev_frame.idx)
prev_frame.is_shown = False
io.progress_bar_inc(-1)
if cur_frame is not None and (
go_prev_frame_overriding_cfg
or go_first_frame_overriding_cfg):
if prev_frame.cfg != cur_frame.cfg:
prev_frame.cfg = cur_frame.cfg.copy()
prev_frame.is_done = False
cur_frame = prev_frame
if go_first_frame_overriding_cfg or go_first_frame:
if len(self.frames_done_idxs) > 0:
continue
break
elif go_next_frame:
if cur_frame is not None and cur_frame.is_done:
cur_frame.image = None
cur_frame.is_shown = True
self.frames_done_idxs.append(cur_frame.idx)
self.frames_idxs.pop(0)
io.progress_bar_inc(1)
f = self.frames
if len(self.frames_idxs) != 0:
next_frame = f[self.frames_idxs[0]]
next_frame.is_shown = False
if go_next_frame_overriding_cfg or go_last_frame_overriding_cfg:
if go_next_frame_overriding_cfg:
to_frames = next_frame.idx + 1
else:
to_frames = len(f)
for i in range(next_frame.idx, to_frames):
f[i].cfg = None
for i in range(
min(len(self.frames_idxs),
self.prefetch_frame_count)):
frame = f[self.frames_idxs[i]]
if frame.cfg is None:
if i == 0:
frame.cfg = cur_frame.cfg.copy()
else:
frame.cfg = f[self.frames_idxs[i -
1]].cfg.copy()
frame.is_done = False #initiate solve again
frame.is_shown = False
if len(self.frames_idxs) == 0:
self.process_remain_frames = False
return (self.is_interactive and self.is_interactive_quitting) or \
(not self.is_interactive and self.process_remain_frames == False)
#override
def on_data_return(self, host_dict, pf):
frame = self.frames[pf.idx]
frame.is_done = False
frame.is_processing = False
#override
def on_result(self, host_dict, pf_sent, pf_result):
frame = self.frames[pf_result.idx]
frame.is_processing = False
if frame.cfg == pf_result.cfg:
frame.is_done = True
frame.image = pf_result.image
#override
def get_data(self, host_dict):
if self.is_interactive and self.is_interactive_quitting:
return None
for i in range(min(len(self.frames_idxs), self.prefetch_frame_count)):
frame = self.frames[self.frames_idxs[i]]
if not frame.is_done and not frame.is_processing and frame.cfg is not None:
frame.is_processing = True
return MergeSubprocessor.ProcessingFrame(
idx=frame.idx,
cfg=frame.cfg.copy(),
prev_temporal_frame_infos=frame.prev_temporal_frame_infos,
frame_info=frame.frame_info,
next_temporal_frame_infos=frame.next_temporal_frame_infos,
output_filepath=frame.output_filepath,
need_return_image=True)
return None
#override
def get_result(self):
return 0
