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import multiprocessing
import shutil
from DFLIMG import *
from core.interact import interact as io
from core.joblib import Subprocessor
from core.leras import nn
from core import pathex
from core.cv2ex import *
class FacesetEnhancerSubprocessor(Subprocessor):
#override
def __init__(self, image_paths, output_dirpath, device_config):
self.image_paths = image_paths
self.output_dirpath = output_dirpath
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,
'nn_initialize_mp_lock': self.nn_initialize_mp_lock,}
for (device_idx, device_type, device_name, device_total_vram_gb) in self.devices:
client_dict = base_dict.copy()
client_dict['device_idx'] = device_idx
client_dict['device_name'] = device_name
client_dict['device_type'] = device_type
yield client_dict['device_name'], {}, client_dict
#override
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):
devices = device_config.devices
cpu_only = len(devices) == 0
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
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 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}")
io.log_info ( f"Processing to {output_dirpath_parts}")
output_images_paths = pathex.get_image_paths(output_dirpath)
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 )]
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:
shutil.copy (output_filepath, filepath)
except:
pass
io.log_info (f"Removing {output_dirpath_parts}")
shutil.rmtree(output_dirpath)
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