deepfuze
This commit is contained in:
vnyash
+301
@@ -0,0 +1,301 @@
|
||||
from typing import Any, List, Literal, Optional
|
||||
from argparse import ArgumentParser
|
||||
from time import sleep
|
||||
import cv2
|
||||
import numpy
|
||||
import onnxruntime
|
||||
|
||||
import deepfuze.globals
|
||||
import deepfuze.processors.frame.core as frame_processors
|
||||
from deepfuze import config, process_manager, logger, wording
|
||||
from deepfuze.face_analyser import get_many_faces, clear_face_analyser, find_similar_faces, get_one_face
|
||||
from deepfuze.face_masker import create_static_box_mask, create_occlusion_mask, clear_face_occluder
|
||||
from deepfuze.face_helper import warp_face_by_face_landmark_5, paste_back
|
||||
from deepfuze.execution import apply_execution_provider_options
|
||||
from deepfuze.content_analyser import clear_content_analyser
|
||||
from deepfuze.face_store import get_reference_faces
|
||||
from deepfuze.normalizer import normalize_output_path
|
||||
from deepfuze.thread_helper import thread_lock, thread_semaphore
|
||||
from deepfuze.typing import Face, VisionFrame, UpdateProgress, ProcessMode, ModelSet, OptionsWithModel, QueuePayload
|
||||
from deepfuze.common_helper import create_metavar
|
||||
from deepfuze.filesystem import is_file, is_image, is_video, resolve_relative_path
|
||||
from deepfuze.download import conditional_download, is_download_done
|
||||
from deepfuze.vision import read_image, read_static_image, write_image
|
||||
from deepfuze.processors.frame.typings import FaceEnhancerInputs
|
||||
from deepfuze.processors.frame import globals as frame_processors_globals
|
||||
from deepfuze.processors.frame import choices as frame_processors_choices
|
||||
|
||||
FRAME_PROCESSOR = None
|
||||
NAME = __name__.upper()
|
||||
MODELS : ModelSet =\
|
||||
{
|
||||
'codeformer':
|
||||
{
|
||||
'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models/codeformer.onnx',
|
||||
'path': resolve_relative_path('../../../models/deepfuze/codeformer.onnx'),
|
||||
'template': 'ffhq_512',
|
||||
'size': (512, 512)
|
||||
},
|
||||
'gfpgan_1.2':
|
||||
{
|
||||
'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models/gfpgan_1.2.onnx',
|
||||
'path': resolve_relative_path('../../../models/deepfuze/gfpgan_1.2.onnx'),
|
||||
'template': 'ffhq_512',
|
||||
'size': (512, 512)
|
||||
},
|
||||
'gfpgan_1.3':
|
||||
{
|
||||
'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models/gfpgan_1.3.onnx',
|
||||
'path': resolve_relative_path('../../../models/deepfuze/gfpgan_1.3.onnx'),
|
||||
'template': 'ffhq_512',
|
||||
'size': (512, 512)
|
||||
},
|
||||
'gfpgan_1.4':
|
||||
{
|
||||
'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models/gfpgan_1.4.onnx',
|
||||
'path': resolve_relative_path('../../../models/deepfuze/gfpgan_1.4.onnx'),
|
||||
'template': 'ffhq_512',
|
||||
'size': (512, 512)
|
||||
},
|
||||
'gpen_bfr_256':
|
||||
{
|
||||
'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models/gpen_bfr_256.onnx',
|
||||
'path': resolve_relative_path('../../../models/deepfuze/gpen_bfr_256.onnx'),
|
||||
'template': 'arcface_128_v2',
|
||||
'size': (256, 256)
|
||||
},
|
||||
'gpen_bfr_512':
|
||||
{
|
||||
'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models/gpen_bfr_512.onnx',
|
||||
'path': resolve_relative_path('../../../models/deepfuze/gpen_bfr_512.onnx'),
|
||||
'template': 'ffhq_512',
|
||||
'size': (512, 512)
|
||||
},
|
||||
'gpen_bfr_1024':
|
||||
{
|
||||
'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models/gpen_bfr_1024.onnx',
|
||||
'path': resolve_relative_path('../../../models/deepfuze/gpen_bfr_1024.onnx'),
|
||||
'template': 'ffhq_512',
|
||||
'size': (1024, 1024)
|
||||
},
|
||||
'gpen_bfr_2048':
|
||||
{
|
||||
'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models/gpen_bfr_2048.onnx',
|
||||
'path': resolve_relative_path('../../../models/deepfuze/gpen_bfr_2048.onnx'),
|
||||
'template': 'ffhq_512',
|
||||
'size': (2048, 2048)
|
||||
},
|
||||
'restoreformer_plus_plus':
|
||||
{
|
||||
'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models/restoreformer_plus_plus.onnx',
|
||||
'path': resolve_relative_path('../../../models/deepfuze/restoreformer_plus_plus.onnx'),
|
||||
'template': 'ffhq_512',
|
||||
'size': (512, 512)
|
||||
}
|
||||
}
|
||||
OPTIONS : Optional[OptionsWithModel] = None
|
||||
|
||||
|
||||
def get_frame_processor() -> Any:
|
||||
global FRAME_PROCESSOR
|
||||
|
||||
with thread_lock():
|
||||
while process_manager.is_checking():
|
||||
sleep(0.5)
|
||||
if FRAME_PROCESSOR is None:
|
||||
model_path = get_options('model').get('path')
|
||||
FRAME_PROCESSOR = onnxruntime.InferenceSession(model_path, providers = apply_execution_provider_options(deepfuze.globals.execution_device_id, deepfuze.globals.execution_providers))
|
||||
return FRAME_PROCESSOR
|
||||
|
||||
|
||||
def clear_frame_processor() -> None:
|
||||
global FRAME_PROCESSOR
|
||||
|
||||
FRAME_PROCESSOR = None
|
||||
|
||||
|
||||
def get_options(key : Literal['model']) -> Any:
|
||||
global OPTIONS
|
||||
|
||||
if OPTIONS is None:
|
||||
OPTIONS =\
|
||||
{
|
||||
'model': MODELS[frame_processors_globals.face_enhancer_model]
|
||||
}
|
||||
return OPTIONS.get(key)
|
||||
|
||||
|
||||
def set_options(key : Literal['model'], value : Any) -> None:
|
||||
global OPTIONS
|
||||
|
||||
OPTIONS[key] = value
|
||||
|
||||
|
||||
def register_args(program : ArgumentParser) -> None:
|
||||
program.add_argument('--face-enhancer-model', help = wording.get('help.face_enhancer_model'), default = config.get_str_value('frame_processors.face_enhancer_model', 'gfpgan_1.4'), choices = frame_processors_choices.face_enhancer_models)
|
||||
program.add_argument('--face-enhancer-blend', help = wording.get('help.face_enhancer_blend'), type = int, default = config.get_int_value('frame_processors.face_enhancer_blend', '80'), choices = frame_processors_choices.face_enhancer_blend_range, metavar = create_metavar(frame_processors_choices.face_enhancer_blend_range))
|
||||
|
||||
|
||||
def apply_args(program : ArgumentParser) -> None:
|
||||
args = program.parse_args()
|
||||
frame_processors_globals.face_enhancer_model = args.face_enhancer_model
|
||||
frame_processors_globals.face_enhancer_blend = args.face_enhancer_blend
|
||||
|
||||
|
||||
def pre_check() -> bool:
|
||||
download_directory_path = resolve_relative_path('../../../models/deepfuze')
|
||||
model_url = get_options('model').get('url')
|
||||
model_path = get_options('model').get('path')
|
||||
|
||||
if not deepfuze.globals.skip_download:
|
||||
process_manager.check()
|
||||
conditional_download(download_directory_path, [ model_url ])
|
||||
process_manager.end()
|
||||
return is_file(model_path)
|
||||
|
||||
|
||||
def post_check() -> bool:
|
||||
model_url = get_options('model').get('url')
|
||||
model_path = get_options('model').get('path')
|
||||
|
||||
if not deepfuze.globals.skip_download and not is_download_done(model_url, model_path):
|
||||
logger.error(wording.get('model_download_not_done') + wording.get('exclamation_mark'), NAME)
|
||||
return False
|
||||
if not is_file(model_path):
|
||||
logger.error(wording.get('model_file_not_present') + wording.get('exclamation_mark'), NAME)
|
||||
return False
|
||||
return True
|
||||
|
||||
|
||||
def pre_process(mode : ProcessMode) -> bool:
|
||||
if mode in [ 'output', 'preview' ] and not is_image(deepfuze.globals.target_path) and not is_video(deepfuze.globals.target_path):
|
||||
logger.error(wording.get('select_image_or_video_target') + wording.get('exclamation_mark'), NAME)
|
||||
return False
|
||||
if mode == 'output' and not normalize_output_path(deepfuze.globals.target_path, deepfuze.globals.output_path):
|
||||
logger.error(wording.get('select_file_or_directory_output') + wording.get('exclamation_mark'), NAME)
|
||||
return False
|
||||
return True
|
||||
|
||||
|
||||
def post_process() -> None:
|
||||
read_static_image.cache_clear()
|
||||
if deepfuze.globals.video_memory_strategy == 'strict' or deepfuze.globals.video_memory_strategy == 'moderate':
|
||||
clear_frame_processor()
|
||||
if deepfuze.globals.video_memory_strategy == 'strict':
|
||||
clear_face_analyser()
|
||||
clear_content_analyser()
|
||||
clear_face_occluder()
|
||||
|
||||
|
||||
def enhance_face(target_face: Face, temp_vision_frame : VisionFrame) -> VisionFrame:
|
||||
model_template = get_options('model').get('template')
|
||||
model_size = get_options('model').get('size')
|
||||
crop_vision_frame, affine_matrix = warp_face_by_face_landmark_5(temp_vision_frame, target_face.landmarks.get('5/68'), model_template, model_size)
|
||||
box_mask = create_static_box_mask(crop_vision_frame.shape[:2][::-1], deepfuze.globals.face_mask_blur, (0, 0, 0, 0))
|
||||
crop_mask_list =\
|
||||
[
|
||||
box_mask
|
||||
]
|
||||
|
||||
if 'occlusion' in deepfuze.globals.face_mask_types:
|
||||
occlusion_mask = create_occlusion_mask(crop_vision_frame)
|
||||
crop_mask_list.append(occlusion_mask)
|
||||
crop_vision_frame = prepare_crop_frame(crop_vision_frame)
|
||||
crop_vision_frame = apply_enhance(crop_vision_frame)
|
||||
crop_vision_frame = normalize_crop_frame(crop_vision_frame)
|
||||
crop_mask = numpy.minimum.reduce(crop_mask_list).clip(0, 1)
|
||||
paste_vision_frame = paste_back(temp_vision_frame, crop_vision_frame, crop_mask, affine_matrix)
|
||||
temp_vision_frame = blend_frame(temp_vision_frame, paste_vision_frame)
|
||||
return temp_vision_frame
|
||||
|
||||
|
||||
def apply_enhance(crop_vision_frame : VisionFrame) -> VisionFrame:
|
||||
frame_processor = get_frame_processor()
|
||||
frame_processor_inputs = {}
|
||||
|
||||
for frame_processor_input in frame_processor.get_inputs():
|
||||
if frame_processor_input.name == 'input':
|
||||
frame_processor_inputs[frame_processor_input.name] = crop_vision_frame
|
||||
if frame_processor_input.name == 'weight':
|
||||
weight = numpy.array([ 1 ]).astype(numpy.double)
|
||||
frame_processor_inputs[frame_processor_input.name] = weight
|
||||
with thread_semaphore():
|
||||
crop_vision_frame = frame_processor.run(None, frame_processor_inputs)[0][0]
|
||||
return crop_vision_frame
|
||||
|
||||
|
||||
def prepare_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame:
|
||||
crop_vision_frame = crop_vision_frame[:, :, ::-1] / 255.0
|
||||
crop_vision_frame = (crop_vision_frame - 0.5) / 0.5
|
||||
crop_vision_frame = numpy.expand_dims(crop_vision_frame.transpose(2, 0, 1), axis = 0).astype(numpy.float32)
|
||||
return crop_vision_frame
|
||||
|
||||
|
||||
def normalize_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame:
|
||||
crop_vision_frame = numpy.clip(crop_vision_frame, -1, 1)
|
||||
crop_vision_frame = (crop_vision_frame + 1) / 2
|
||||
crop_vision_frame = crop_vision_frame.transpose(1, 2, 0)
|
||||
crop_vision_frame = (crop_vision_frame * 255.0).round()
|
||||
crop_vision_frame = crop_vision_frame.astype(numpy.uint8)[:, :, ::-1]
|
||||
return crop_vision_frame
|
||||
|
||||
|
||||
def blend_frame(temp_vision_frame : VisionFrame, paste_vision_frame : VisionFrame) -> VisionFrame:
|
||||
face_enhancer_blend = 1 - (frame_processors_globals.face_enhancer_blend / 100)
|
||||
temp_vision_frame = cv2.addWeighted(temp_vision_frame, face_enhancer_blend, paste_vision_frame, 1 - face_enhancer_blend, 0)
|
||||
return temp_vision_frame
|
||||
|
||||
|
||||
def get_reference_frame(source_face : Face, target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame:
|
||||
return enhance_face(target_face, temp_vision_frame)
|
||||
|
||||
|
||||
def process_frame(inputs : FaceEnhancerInputs) -> VisionFrame:
|
||||
reference_faces = inputs.get('reference_faces')
|
||||
target_vision_frame = inputs.get('target_vision_frame')
|
||||
|
||||
if deepfuze.globals.face_selector_mode == 'many':
|
||||
many_faces = get_many_faces(target_vision_frame)
|
||||
if many_faces:
|
||||
for target_face in many_faces:
|
||||
target_vision_frame = enhance_face(target_face, target_vision_frame)
|
||||
if deepfuze.globals.face_selector_mode == 'one':
|
||||
target_face = get_one_face(target_vision_frame)
|
||||
if target_face:
|
||||
target_vision_frame = enhance_face(target_face, target_vision_frame)
|
||||
if deepfuze.globals.face_selector_mode == 'reference':
|
||||
similar_faces = find_similar_faces(reference_faces, target_vision_frame, deepfuze.globals.reference_face_distance)
|
||||
if similar_faces:
|
||||
for similar_face in similar_faces:
|
||||
target_vision_frame = enhance_face(similar_face, target_vision_frame)
|
||||
return target_vision_frame
|
||||
|
||||
|
||||
def process_frames(source_path : List[str], queue_payloads : List[QueuePayload], update_progress : UpdateProgress) -> None:
|
||||
reference_faces = get_reference_faces() if 'reference' in deepfuze.globals.face_selector_mode else None
|
||||
|
||||
for queue_payload in process_manager.manage(queue_payloads):
|
||||
target_vision_path = queue_payload['frame_path']
|
||||
target_vision_frame = read_image(target_vision_path)
|
||||
output_vision_frame = process_frame(
|
||||
{
|
||||
'reference_faces': reference_faces,
|
||||
'target_vision_frame': target_vision_frame
|
||||
})
|
||||
write_image(target_vision_path, output_vision_frame)
|
||||
update_progress(1)
|
||||
|
||||
|
||||
def process_image(source_path : str, target_path : str, output_path : str) -> None:
|
||||
reference_faces = get_reference_faces() if 'reference' in deepfuze.globals.face_selector_mode else None
|
||||
target_vision_frame = read_static_image(target_path)
|
||||
output_vision_frame = process_frame(
|
||||
{
|
||||
'reference_faces': reference_faces,
|
||||
'target_vision_frame': target_vision_frame
|
||||
})
|
||||
write_image(output_path, output_vision_frame)
|
||||
|
||||
|
||||
def process_video(source_paths : List[str], temp_frame_paths : List[str]) -> None:
|
||||
frame_processors.multi_process_frames(None, temp_frame_paths, process_frames)
|
||||
Reference in New Issue
Block a user