Upgraded to TF version 1.13.2
Removed the wait at first launch for most graphics cards. Increased speed of training by 10-20%, but you have to retrain all models from scratch. SAEHD: added option 'use float16' Experimental option. Reduces the model size by half. Increases the speed of training. Decreases the accuracy of the model. The model may collapse or not train. Model may not learn the mask in large resolutions. true_face_training option is replaced by "True face power". 0.0000 .. 1.0 Experimental option. Discriminates the result face to be more like the src face. Higher value - stronger discrimination. Comparison - https://i.imgur.com/czScS9q.png
This commit is contained in:
Colombo
@@ -10,7 +10,7 @@ from core.cv2ex import *
|
||||
|
||||
|
||||
class FacesetEnhancerSubprocessor(Subprocessor):
|
||||
|
||||
|
||||
#override
|
||||
def __init__(self, image_paths, output_dirpath, device_config):
|
||||
self.image_paths = image_paths
|
||||
@@ -18,17 +18,17 @@ class FacesetEnhancerSubprocessor(Subprocessor):
|
||||
self.result = []
|
||||
self.nn_initialize_mp_lock = multiprocessing.Lock()
|
||||
self.devices = FacesetEnhancerSubprocessor.get_devices_for_config(device_config)
|
||||
|
||||
|
||||
super().__init__('FacesetEnhancer', FacesetEnhancerSubprocessor.Cli, 600)
|
||||
|
||||
#override
|
||||
def on_clients_initialized(self):
|
||||
io.progress_bar (None, len (self.image_paths))
|
||||
|
||||
|
||||
#override
|
||||
def on_clients_finalized(self):
|
||||
io.progress_bar_close()
|
||||
|
||||
|
||||
#override
|
||||
def process_info_generator(self):
|
||||
base_dict = {'output_dirpath':self.output_dirpath,
|
||||
@@ -42,34 +42,34 @@ class FacesetEnhancerSubprocessor(Subprocessor):
|
||||
yield client_dict['device_name'], {}, client_dict
|
||||
|
||||
#override
|
||||
def get_data(self, host_dict):
|
||||
def get_data(self, host_dict):
|
||||
if len (self.image_paths) > 0:
|
||||
return self.image_paths.pop(0)
|
||||
|
||||
|
||||
#override
|
||||
def on_data_return (self, host_dict, data):
|
||||
self.image_paths.insert(0, data)
|
||||
|
||||
|
||||
#override
|
||||
def on_result (self, host_dict, data, result):
|
||||
io.progress_bar_inc(1)
|
||||
if result[0] == 1:
|
||||
self.result +=[ (result[1], result[2]) ]
|
||||
|
||||
|
||||
#override
|
||||
def get_result(self):
|
||||
return self.result
|
||||
|
||||
|
||||
@staticmethod
|
||||
def get_devices_for_config (device_config):
|
||||
def get_devices_for_config (device_config):
|
||||
devices = device_config.devices
|
||||
cpu_only = len(devices) == 0
|
||||
|
||||
if not cpu_only:
|
||||
|
||||
if not cpu_only:
|
||||
return [ (device.index, 'GPU', device.name, device.total_mem_gb) for device in devices ]
|
||||
else:
|
||||
return [ (i, 'CPU', 'CPU%d' % (i), 0 ) for i in range( min(8, multiprocessing.cpu_count() // 2) ) ]
|
||||
|
||||
|
||||
class Cli(Subprocessor.Cli):
|
||||
|
||||
#override
|
||||
@@ -85,14 +85,14 @@ class FacesetEnhancerSubprocessor(Subprocessor):
|
||||
else:
|
||||
device_config = nn.DeviceConfig.GPUIndexes ([device_idx])
|
||||
device_vram = device_config.devices[0].total_mem_gb
|
||||
|
||||
nn.initialize (device_config)
|
||||
|
||||
nn.initialize (device_config)
|
||||
|
||||
intro_str = 'Running on %s.' % (client_dict['device_name'])
|
||||
|
||||
|
||||
self.log_info (intro_str)
|
||||
|
||||
from facelib import FaceEnhancer
|
||||
from facelib import FaceEnhancer
|
||||
self.fe = FaceEnhancer( place_model_on_cpu=(device_vram<=2) )
|
||||
|
||||
#override
|
||||
@@ -103,28 +103,28 @@ class FacesetEnhancerSubprocessor(Subprocessor):
|
||||
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)
|
||||
|
||||
|
||||
def process_folder ( dirpath, cpu_only=False, force_gpu_idxs=None ):
|
||||
device_config = nn.DeviceConfig.GPUIndexes( force_gpu_idxs or nn.ask_choose_device_idxs(suggest_all_gpu=True) ) \
|
||||
if not cpu_only else nn.DeviceConfig.CPU()
|
||||
|
||||
|
||||
output_dirpath = dirpath.parent / (dirpath.name + '_enhanced')
|
||||
output_dirpath.mkdir (exist_ok=True, parents=True)
|
||||
|
||||
|
||||
dirpath_parts = '/'.join( dirpath.parts[-2:])
|
||||
output_dirpath_parts = '/'.join( output_dirpath.parts[-2:] )
|
||||
io.log_info (f"Enhancing faceset in {dirpath_parts}")
|
||||
@@ -134,19 +134,19 @@ def process_folder ( dirpath, cpu_only=False, force_gpu_idxs=None ):
|
||||
if len(output_images_paths) > 0:
|
||||
for filename in output_images_paths:
|
||||
Path(filename).unlink()
|
||||
|
||||
image_paths = [Path(x) for x in pathex.get_image_paths( dirpath )]
|
||||
|
||||
image_paths = [Path(x) for x in pathex.get_image_paths( dirpath )]
|
||||
result = FacesetEnhancerSubprocessor ( image_paths, output_dirpath, device_config=device_config).run()
|
||||
|
||||
is_merge = io.input_bool (f"\r\nMerge {output_dirpath_parts} to {dirpath_parts} ?", True)
|
||||
if is_merge:
|
||||
io.log_info (f"Copying processed files to {dirpath_parts}")
|
||||
|
||||
for (filepath, output_filepath) in result:
|
||||
try:
|
||||
|
||||
for (filepath, output_filepath) in result:
|
||||
try:
|
||||
shutil.copy (output_filepath, filepath)
|
||||
except:
|
||||
pass
|
||||
|
||||
|
||||
io.log_info (f"Removing {output_dirpath_parts}")
|
||||
shutil.rmtree(output_dirpath)
|
||||
|
||||
Reference in New Issue
Block a user