ConvertVideo.py

import sys
import os

import keras.backend as K
from networks.faceswap_gan_model import FaceswapGANModel
from converter.video_converter import VideoConverter
from detector.face_detector import MTCNNFaceDetector

def blankfx():
  sys.stdout = open(os.devnull, "w")

def conversion_fx():
    
  K.set_learning_phase(0)

  RESOLUTION = 256 # 64x64, 128x128, 256x256
  assert (RESOLUTION % 64) == 0, "RESOLUTION should be 64, 128, 256"

  # Architecture configuration
  arch_config = {}
  arch_config['IMAGE_SHAPE'] = (RESOLUTION, RESOLUTION, 3)
  arch_config['use_self_attn'] = True
  arch_config['norm'] = "instancenorm" 
  arch_config['model_capacity'] = "standard" 

  model = FaceswapGANModel(**arch_config)

  model.load_weights(path="./models1")
  mtcnn_weights_dir = "./mtcnn_weights/"

  fd = MTCNNFaceDetector(sess=K.get_session(), model_path=mtcnn_weights_dir)
  vc = VideoConverter()

  vc.set_face_detector(fd)
  vc.set_gan_model(model)

  options = {
      # ===== Fixed =====
      "use_smoothed_bbox": True,
      "use_kalman_filter": True,
      "use_auto_downscaling": False,
      "bbox_moving_avg_coef": 0.65,
      "min_face_area": 35 * 35,
      "IMAGE_SHAPE": model.IMAGE_SHAPE,
      # ===== Tunable =====
      "kf_noise_coef": 3e-3,
      "use_color_correction": "hist_match",
      "detec_threshold": 0.7,
      "roi_coverage": 0.9,
      "enhance": 0.,
      "output_type": 3,
      "direction": "AtoB",
  }

  input_fn = "testNOV12.3gpp"            # update req
  output_fn = "testNov10.mp4"
  duration = None 

  vc.convert(input_fn=input_fn, output_fn=output_fn, options=options, duration=duration)

blankfx()
conversion_fx()