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#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright 2023 Imperial College London (Pingchuan Ma)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import os
import cv2
import hydra
import torchvision
from pipelines.detectors.mediapipe.detector import LandmarksDetector
from pipelines.data.data_module import AVSRDataLoader
def save2vid(filename, vid, frames_per_second):
os.makedirs(os.path.dirname(filename), exist_ok=True)
torchvision.io.write_video(filename, vid, frames_per_second)
@hydra.main(version_base=None, config_path="hydra_configs", config_name="default")
def main(cfg):
if cfg.detector == "mediapipe":
from pipelines.detectors.mediapipe.detector import LandmarksDetector
landmarks_detector = LandmarksDetector()
if cfg.detector == "retinaface":
from pipelines.detectors.retinaface.detector import LandmarksDetector
landmarks_detector = LandmarksDetector()
dataloader = AVSRDataLoader(modality="video", speed_rate=1, transform=False, detector=cfg.detector, convert_gray=False)
landmarks = landmarks_detector(cfg.data_filename)
data = dataloader.load_data(cfg.data_filename, landmarks)
fps = cv2.VideoCapture(cfg.data_filename).get(cv2.CAP_PROP_FPS)
save2vid(cfg.dst_filename, data, fps)
print(f"The mouth images have been cropped and saved to {cfg.dst_filename}")
if __name__ == "__main__":
main()
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