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#import necessary libraries

from deepface import DeepFace import os

import cv2

import matplotlib.pyplot as plt

import glob

from concurrent.futures import ThreadPoolExecutor

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# define the paths to the original (training) images folder and the generated images folder org_images_folder_path = r"C:script testcompare_imgs" generated_images_folder_path = r"C:script testtest2"

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The Script Shared On Patreon You Can Download There

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# define the name of the model to use model_name = 'Facenet512'

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# define the path to the folder where the detected faces of the training images will be saved detected_faces_folder_path = r"C:script testdetected_faces"

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# create a list to hold the original images

org images = []

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# create the detected faces folder if it doesn't exist if not os.path.exists(detected_faces_folder_path): os.makedirs(detected_faces_folder_path)

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# loop through the original images folder and detect faces using DeepFace

for org_image_file in os.listdir(org_images_folder_path):

if org_image_file.endswith('.jpg') or org_image_file.endswith('.png') or org_image_file.endswith('.JPG'): org_image_path = os.path.join(org_images_folder_path, org_image_file) generated_image_path = os.path.join(generated_images_folder_path, org_image_file) org_image = cv2.imread(org_image_path)

org_images.append(org_image)

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# detect faces using DeepFace

detected_face = DeepFace.detectFace (org_image_path, detector_backend='opencv')