| from argparse import ArgumentParser |
| from types import ModuleType |
| from typing import List |
|
|
| import cv2 |
| import numpy |
|
|
| import facefusion.jobs.job_manager |
| import facefusion.jobs.job_store |
| from facefusion import config, content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, logger, state_manager, translator, video_manager |
| from facefusion.common_helper import get_middle |
| from facefusion.face_creator import scale_face |
| from facefusion.face_helper import warp_face_by_face_landmark_5 |
| from facefusion.face_masker import create_area_mask, create_box_mask, create_occlusion_mask, create_region_mask |
| from facefusion.face_selector import select_faces |
| from facefusion.filesystem import in_directory, is_image, is_video, same_file_extension |
| from facefusion.processors.modules.face_debugger import choices as face_debugger_choices |
| from facefusion.processors.modules.face_debugger.types import FaceDebuggerInputs |
| from facefusion.processors.types import ProcessorOutputs |
| from facefusion.program_helper import find_argument_group |
| from facefusion.types import ApplyStateItem, Args, Face, InferencePool, ProcessMode, VisionFrame |
| from facefusion.vision import read_static_image, read_static_video_frame |
|
|
|
|
| def get_inference_pool() -> InferencePool: |
| pass |
|
|
|
|
| def clear_inference_pool() -> None: |
| pass |
|
|
|
|
| def register_args(program : ArgumentParser) -> None: |
| group_processors = find_argument_group(program, 'processors') |
| if group_processors: |
| group_processors.add_argument('--face-debugger-items', help = translator.get('help.items', __package__).format(choices = ', '.join(face_debugger_choices.face_debugger_items)), default = config.get_str_list('processors', 'face_debugger_items', 'face-landmark-5/68 face-mask'), choices = face_debugger_choices.face_debugger_items, nargs = '+', metavar = 'FACE_DEBUGGER_ITEMS') |
| facefusion.jobs.job_store.register_step_keys([ 'face_debugger_items' ]) |
|
|
|
|
| def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None: |
| apply_state_item('face_debugger_items', args.get('face_debugger_items')) |
|
|
|
|
| def get_common_modules() -> List[ModuleType]: |
| return [ content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer ] |
|
|
|
|
| def pre_check() -> bool: |
| for common_module in get_common_modules(): |
| if not common_module.pre_check(): |
| return False |
| return True |
|
|
|
|
| def pre_process(mode : ProcessMode) -> bool: |
| if mode in [ 'output', 'preview' ] and not is_image(state_manager.get_item('target_path')) and not is_video(state_manager.get_item('target_path')): |
| logger.error(translator.get('choose_image_or_video_target') + translator.get('exclamation_mark'), __name__) |
| return False |
| if mode == 'output' and not in_directory(state_manager.get_item('output_path')): |
| logger.error(translator.get('specify_image_or_video_output') + translator.get('exclamation_mark'), __name__) |
| return False |
| if mode == 'output' and not same_file_extension(state_manager.get_item('target_path'), state_manager.get_item('output_path')): |
| logger.error(translator.get('match_target_and_output_extension') + translator.get('exclamation_mark'), __name__) |
| return False |
| return True |
|
|
|
|
| def post_process() -> None: |
| read_static_image.cache_clear() |
| read_static_video_frame.cache_clear() |
| video_manager.clear_video_pool() |
|
|
| if state_manager.get_item('video_memory_strategy') == 'strict': |
| for common_module in get_common_modules(): |
| common_module.clear_inference_pool() |
|
|
|
|
| def debug_face(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame: |
| face_debugger_items = state_manager.get_item('face_debugger_items') |
|
|
| if 'bounding-box' in face_debugger_items: |
| temp_vision_frame = draw_bounding_box(target_face, temp_vision_frame) |
|
|
| if 'face-mask' in face_debugger_items: |
| temp_vision_frame = draw_face_mask(target_face, temp_vision_frame) |
|
|
| if 'face-landmark-5' in face_debugger_items: |
| temp_vision_frame = draw_face_landmark_5(target_face, temp_vision_frame) |
|
|
| if 'face-landmark-5/68' in face_debugger_items: |
| temp_vision_frame = draw_face_landmark_5_68(target_face, temp_vision_frame) |
|
|
| if 'face-landmark-68' in face_debugger_items: |
| temp_vision_frame = draw_face_landmark_68(target_face, temp_vision_frame) |
|
|
| if 'face-landmark-68/5' in face_debugger_items: |
| temp_vision_frame = draw_face_landmark_68_5(target_face, temp_vision_frame) |
|
|
| return temp_vision_frame |
|
|
|
|
| def draw_bounding_box(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame: |
| temp_vision_frame = numpy.ascontiguousarray(temp_vision_frame) |
| bounding_box = target_face.bounding_box.astype(numpy.int32) |
| x1, y1, x2, y2 = bounding_box |
| box_color = 0, 0, 255 |
| border_scale = calculate_scale(temp_vision_frame) |
| border_color = 100, 100, 255 |
|
|
| cv2.rectangle(temp_vision_frame, (x1, y1), (x2, y2), box_color, border_scale) |
|
|
| if target_face.angle == 0: |
| cv2.line(temp_vision_frame, (x1, y1), (x2, y1), border_color, border_scale + 1) |
| if target_face.angle == 180: |
| cv2.line(temp_vision_frame, (x1, y2), (x2, y2), border_color, border_scale + 1) |
| if target_face.angle == 90: |
| cv2.line(temp_vision_frame, (x2, y1), (x2, y2), border_color, border_scale + 1) |
| if target_face.angle == 270: |
| cv2.line(temp_vision_frame, (x1, y1), (x1, y2), border_color, border_scale + 1) |
|
|
| return temp_vision_frame |
|
|
|
|
| def draw_face_mask(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame: |
| crop_masks = [] |
| temp_vision_frame = numpy.ascontiguousarray(temp_vision_frame) |
| face_landmark_5 = target_face.landmark_set.get('5') |
| face_landmark_68 = target_face.landmark_set.get('68') |
| face_landmark_5_68 = target_face.landmark_set.get('5/68') |
| crop_vision_frame, affine_matrix = warp_face_by_face_landmark_5(temp_vision_frame, face_landmark_5_68, 'arcface_128', (512, 512)) |
| inverse_matrix = cv2.invertAffineTransform(affine_matrix) |
| temp_size = temp_vision_frame.shape[:2][::-1] |
| mask_scale = calculate_scale(temp_vision_frame) |
| mask_color = 0, 255, 0 |
|
|
| if numpy.array_equal(face_landmark_5, face_landmark_5_68): |
| mask_color = 255, 255, 0 |
|
|
| if target_face.origin == 'refill': |
| mask_color = 0, 165, 255 |
|
|
| if 'box' in state_manager.get_item('face_mask_types'): |
| box_mask = create_box_mask(crop_vision_frame, 0, state_manager.get_item('face_mask_padding')) |
| crop_masks.append(box_mask) |
|
|
| if 'occlusion' in state_manager.get_item('face_mask_types'): |
| occlusion_mask = create_occlusion_mask(crop_vision_frame) |
| crop_masks.append(occlusion_mask) |
|
|
| if 'area' in state_manager.get_item('face_mask_types'): |
| face_landmark_68 = cv2.transform(face_landmark_68.reshape(1, -1, 2), affine_matrix).reshape(-1, 2) |
| area_mask = create_area_mask(crop_vision_frame, face_landmark_68, state_manager.get_item('face_mask_areas')) |
| crop_masks.append(area_mask) |
|
|
| if 'region' in state_manager.get_item('face_mask_types'): |
| region_mask = create_region_mask(crop_vision_frame, state_manager.get_item('face_mask_regions')) |
| crop_masks.append(region_mask) |
|
|
| crop_mask = numpy.minimum.reduce(crop_masks).clip(0, 1) |
| crop_mask = (crop_mask * 255).astype(numpy.uint8) |
| inverse_vision_frame = cv2.warpAffine(crop_mask, inverse_matrix, temp_size) |
| inverse_vision_frame = cv2.threshold(inverse_vision_frame, 100, 255, cv2.THRESH_BINARY)[1] |
| inverse_contours, _ = cv2.findContours(inverse_vision_frame, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE) |
| cv2.drawContours(temp_vision_frame, inverse_contours, -1, mask_color, mask_scale) |
|
|
| return temp_vision_frame |
|
|
|
|
| def draw_face_landmark_5(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame: |
| temp_vision_frame = numpy.ascontiguousarray(temp_vision_frame) |
| face_landmark_5 = target_face.landmark_set.get('5') |
| point_scale = calculate_scale(temp_vision_frame) |
| point_color = 0, 0, 255 |
|
|
| if target_face.origin == 'refill': |
| point_color = 0, 165, 255 |
|
|
| if numpy.any(face_landmark_5): |
| face_landmark_5 = face_landmark_5.astype(numpy.int32) |
|
|
| for point in face_landmark_5: |
| cv2.circle(temp_vision_frame, tuple(point), point_scale, point_color, -1) |
|
|
| return temp_vision_frame |
|
|
|
|
| def draw_face_landmark_5_68(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame: |
| temp_vision_frame = numpy.ascontiguousarray(temp_vision_frame) |
| face_landmark_5 = target_face.landmark_set.get('5') |
| face_landmark_5_68 = target_face.landmark_set.get('5/68') |
| point_scale = calculate_scale(temp_vision_frame) |
| point_color = 0, 255, 0 |
|
|
| if numpy.array_equal(face_landmark_5, face_landmark_5_68): |
| point_color = 255, 255, 0 |
|
|
| if target_face.origin == 'refill': |
| point_color = 0, 165, 255 |
|
|
| if numpy.any(face_landmark_5_68): |
| face_landmark_5_68 = face_landmark_5_68.astype(numpy.int32) |
|
|
| for point in face_landmark_5_68: |
| cv2.circle(temp_vision_frame, tuple(point), point_scale, point_color, -1) |
|
|
| return temp_vision_frame |
|
|
|
|
| def draw_face_landmark_68(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame: |
| temp_vision_frame = numpy.ascontiguousarray(temp_vision_frame) |
| face_landmark_68 = target_face.landmark_set.get('68') |
| face_landmark_68_5 = target_face.landmark_set.get('68/5') |
| point_scale = calculate_scale(temp_vision_frame) |
| point_color = 0, 255, 0 |
|
|
| if numpy.array_equal(face_landmark_68, face_landmark_68_5): |
| point_color = 255, 255, 0 |
|
|
| if target_face.origin == 'refill': |
| point_color = 0, 165, 255 |
|
|
| if numpy.any(face_landmark_68): |
| face_landmark_68 = face_landmark_68.astype(numpy.int32) |
|
|
| for point in face_landmark_68: |
| cv2.circle(temp_vision_frame, tuple(point), point_scale, point_color, -1) |
|
|
| return temp_vision_frame |
|
|
|
|
| def draw_face_landmark_68_5(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame: |
| temp_vision_frame = numpy.ascontiguousarray(temp_vision_frame) |
| face_landmark_68_5 = target_face.landmark_set.get('68/5') |
| point_scale = calculate_scale(temp_vision_frame) |
| point_color = 255, 255, 0 |
|
|
| if target_face.origin == 'refill': |
| point_color = 0, 165, 255 |
|
|
| if numpy.any(face_landmark_68_5): |
| face_landmark_68_5 = face_landmark_68_5.astype(numpy.int32) |
|
|
| for point in face_landmark_68_5: |
| cv2.circle(temp_vision_frame, tuple(point), point_scale, point_color, -1) |
|
|
| return temp_vision_frame |
|
|
|
|
| def calculate_scale(temp_vision_frame : VisionFrame) -> int: |
| frame_height, _ = temp_vision_frame.shape[:2] |
| frame_scale = round(frame_height / 270) |
| return max(1, min(10, frame_scale)) |
|
|
|
|
| def process_frame(inputs : FaceDebuggerInputs) -> ProcessorOutputs: |
| reference_vision_frame = inputs.get('reference_vision_frame') |
| source_vision_frames = inputs.get('source_vision_frames') |
| target_vision_frames = inputs.get('target_vision_frames') |
| temp_vision_frame = inputs.get('temp_vision_frame') |
| temp_vision_mask = inputs.get('temp_vision_mask') |
|
|
| target_vision_frame = get_middle(target_vision_frames) |
| target_faces = select_faces(reference_vision_frame, source_vision_frames, target_vision_frames) |
|
|
| if target_faces: |
| for target_face in target_faces: |
| target_face = scale_face(target_face, target_vision_frame, temp_vision_frame) |
| temp_vision_frame = debug_face(target_face, temp_vision_frame) |
|
|
| return temp_vision_frame, temp_vision_mask |
|
|
