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processors/modules/face_debugger/choices.py

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+from typing import List, get_args
+
+from facefusion.processors.modules.face_debugger.types import FaceDebuggerItem
+
+face_debugger_items : List[FaceDebuggerItem] = list(get_args(FaceDebuggerItem))

processors/modules/face_debugger/core.py

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+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

processors/modules/face_debugger/locales.py

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+from facefusion.types import Locales
+
+LOCALES : Locales =\
+{
+	'en':
+	{
+		'help':
+		{
+			'items': 'load a single or multiple processors (choices: {choices})'
+		},
+		'uis':
+		{
+			'items_checkbox_group': 'FACE DEBUGGER ITEMS'
+		}
+	}
+}

processors/modules/face_debugger/types.py

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+from typing import List, Literal, TypedDict
+
+from facefusion.types import Mask, VisionFrame
+
+FaceDebuggerInputs = TypedDict('FaceDebuggerInputs',
+{
+	'reference_vision_frame' : VisionFrame,
+	'source_vision_frames' : List[VisionFrame],
+	'target_vision_frames' : List[VisionFrame],
+	'temp_vision_frame' : VisionFrame,
+	'temp_vision_mask' : Mask
+})
+
+FaceDebuggerItem = Literal['bounding-box', 'face-landmark-5', 'face-landmark-5/68', 'face-landmark-68', 'face-landmark-68/5', 'face-mask']