merge_faces.py

import argparse
import cv2
import json
import numpy
from pathlib import Path
from tqdm import tqdm

from model import autoencoder_A
from model import autoencoder_B
from model import encoder, decoder_A, decoder_B

encoder  .load_weights( "models/encoder.h5"   )
decoder_A.load_weights( "models/decoder_A.h5" )
decoder_B.load_weights( "models/decoder_B.h5" )

def convert_one_image( autoencoder, image, mat ):
    size = 64
    image_size = image.shape[1], image.shape[0]

    face = cv2.warpAffine( image, mat * size, (size,size) )
    face = numpy.expand_dims( face, 0 )
    new_face = autoencoder.predict( face / 255.0 )[0]
    new_face = numpy.clip( new_face * 255, 0, 255 ).astype( image.dtype )

    face_mask = numpy.zeros(new_face.shape,dtype=image.dtype)
    image_mask = numpy.zeros(image.shape,dtype=image.dtype)
    cv2.circle(face_mask, (size//2,size//2), int(size*0.6), (255,255,255),-1 )


    cv2.warpAffine( face_mask, mat * size, image_size, image_mask, cv2.WARP_INVERSE_MAP, cv2.BORDER_TRANSPARENT )


    image_mask = cv2.blur(image_mask,(5,5))

    hl = numpy.argwhere( image_mask.mean(axis=-1)==255).mean(axis=0)
    masky,maskx = hl

    base_image = numpy.copy( image )
    new_image = numpy.copy( image )
    
    cv2.warpAffine( new_face, mat * size, image_size, new_image, cv2.WARP_INVERSE_MAP, cv2.BORDER_TRANSPARENT )
    return cv2.seamlessClone(new_image,base_image, image_mask, (int(maskx), int(masky)) , cv2.NORMAL_CLONE   ) 




def main( args ):
    input_dir = Path( args.input_dir )
    assert input_dir.is_dir()

    alignments = input_dir / args.alignments
    with alignments.open() as f:
        alignments = json.load(f)

    output_dir = input_dir / args.output_dir
    output_dir.mkdir( parents=True, exist_ok=True )

    if args.direction == 'AtoB': autoencoder = autoencoder_B
    if args.direction == 'BtoA': autoencoder = autoencoder_A

    for image_file, face_file, mat in tqdm( alignments ):
        image = cv2.imread( str( input_dir / image_file ) )
        face  = cv2.imread( str( input_dir / face_file  ) )

        mat = numpy.array(mat).reshape(2,3)

        if image is None: continue
        if face  is None: continue

        new_image = convert_one_image( autoencoder, image, mat )

        output_file = output_dir / Path(image_file).name
        cv2.imwrite( str(output_file), new_image )

if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument( "input_dir", type=str )
    parser.add_argument( "alignments", type=str, nargs='?', default='alignments.json' )
    parser.add_argument( "output_dir", type=str, nargs='?', default='merged' )
    parser.add_argument( "--direction", type=str, default="AtoB", choices=["AtoB", "BtoA"])
    main( parser.parse_args() )

I am getting this error, someone please help me out!
Tried various parameters to run like "python3 merge_faces.py src alignments modified --direction AtoB"
but always gets error :/

use this script i got an error like this:
cv2.error:/io/opencv/modules/photo/src/seamless_cloning.cpp:94:error:(-215) minxd>=0&&minyd>=0&& ..... infunciton seamlessclone.

but it have output some merged image and the reminded images are not merged.