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Upgraded to TF version 1.13.2

Browse source 
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 2020-01-25 21:58:19 +04:00
parent a3dfcb91b9
commit 76ca79216e
49 changed files with 1320 additions and 1297 deletions
Download patch file Download diff file Expand all files Collapse all files

62
mainscripts/FacesetEnhancer.py
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@ -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)