45 lines
1.7 KiB
Python
45 lines
1.7 KiB
Python
import os
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from tqdm import tqdm
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import cv2
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import insightface
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import core.globals
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from core.analyser import get_face
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FACE_SWAPPER = None
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def get_face_swapper():
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global FACE_SWAPPER
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if FACE_SWAPPER is None:
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model_path = os.path.join(os.path.abspath(os.path.dirname(__file__)), '../inswapper_128.onnx')
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FACE_SWAPPER = insightface.model_zoo.get_model(model_path, providers=core.globals.providers)
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return FACE_SWAPPER
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def process_video(source_img, frame_paths):
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source_face = get_face(cv2.imread(source_img))
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with tqdm(total=len(frame_paths), desc="Processing", unit="frame", dynamic_ncols=True, bar_format='{l_bar}{bar}| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, {rate_fmt}{postfix}]') as progress:
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for frame_path in frame_paths:
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frame = cv2.imread(frame_path)
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try:
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face = get_face(frame)
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if face:
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result = get_face_swapper().get(frame, face, source_face, paste_back=True)
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cv2.imwrite(frame_path, result)
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progress.set_postfix(status='.', refresh=True)
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else:
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progress.set_postfix(status='S', refresh=True)
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except Exception:
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progress.set_postfix(status='E', refresh=True)
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pass
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progress.update(1)
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def process_img(source_img, target_path, output_file):
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frame = cv2.imread(target_path)
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face = get_face(frame)
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source_face = get_face(cv2.imread(source_img))
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result = get_face_swapper().get(frame, face, source_face, paste_back=True)
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cv2.imwrite(output_file, result)
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print("\n\nImage saved as:", output_file, "\n\n")
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