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import threading |
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from typing import Any |
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import insightface |
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import roop.globals |
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from roop.typing import Frame, Face |
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import cv2 |
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import numpy as np |
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from roop.capturer import get_video_frame |
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from roop.utilities import resolve_relative_path, conditional_download |
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FACE_ANALYSER = None |
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THREAD_LOCK_ANALYSER = threading.Lock() |
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THREAD_LOCK_SWAPPER = threading.Lock() |
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FACE_SWAPPER = None |
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def get_face_analyser() -> Any: |
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global FACE_ANALYSER |
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with THREAD_LOCK_ANALYSER: |
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if FACE_ANALYSER is None: |
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if roop.globals.CFG.force_cpu: |
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print('Forcing CPU for Face Analysis') |
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FACE_ANALYSER = insightface.app.FaceAnalysis(name='buffalo_l', providers=['CPUExecutionProvider']) |
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else: |
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FACE_ANALYSER = insightface.app.FaceAnalysis(name='buffalo_l', providers=roop.globals.execution_providers) |
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FACE_ANALYSER.prepare(ctx_id=0, det_size=(640, 640) if roop.globals.default_det_size else (320,320)) |
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return FACE_ANALYSER |
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def get_first_face(frame: Frame) -> Any: |
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try: |
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faces = get_face_analyser().get(frame) |
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return min(faces, key=lambda x: x.bbox[0]) |
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except: |
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return None |
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def get_all_faces(frame: Frame) -> Any: |
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try: |
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faces = get_face_analyser().get(frame) |
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return sorted(faces, key = lambda x : x.bbox[0]) |
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except: |
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return None |
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def extract_face_images(source_filename, video_info): |
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face_data = [] |
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source_image = None |
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if video_info[0]: |
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frame = get_video_frame(source_filename, video_info[1]) |
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if frame is not None: |
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source_image = frame |
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else: |
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return face_data |
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else: |
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source_image = cv2.imread(source_filename) |
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faces = get_all_faces(source_image) |
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if faces is None: |
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return face_data |
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i = 0 |
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for face in faces: |
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(startX, startY, endX, endY) = face['bbox'].astype("int") |
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face_temp = source_image[startY:endY, startX:endX] |
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if face_temp.size < 1: |
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continue |
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i += 1 |
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face_data.append([face, face_temp]) |
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return face_data |
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def get_face_swapper() -> Any: |
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global FACE_SWAPPER |
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with THREAD_LOCK_SWAPPER: |
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if FACE_SWAPPER is None: |
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model_path = resolve_relative_path('../models/inswapper_128.onnx') |
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FACE_SWAPPER = insightface.model_zoo.get_model(model_path, providers=roop.globals.execution_providers) |
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return FACE_SWAPPER |
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def pre_check() -> bool: |
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download_directory_path = resolve_relative_path('../models') |
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conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/inswapper_128.onnx']) |
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return True |
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def swap_face(source_face: Face, target_face: Face, temp_frame: Frame) -> Frame: |
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return get_face_swapper().get(temp_frame, target_face, source_face, paste_back=True) |
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def face_offset_top(face: Face, offset): |
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smallestmin = np.min(face.landmark_2d_106, 1) |
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smallest = smallestmin[1] |
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face['bbox'][1] += offset |
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face['bbox'][3] += offset |
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lm106 = face.landmark_2d_106 |
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add = np.full_like(lm106, [0, offset]) |
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face['landmark_2d_106'] = lm106 + add |
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return face |
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