Import cv2 From MatplotLib Import Pyplot As PLT # Upload the image image

import cv2 From MatplotLib Import Pyplot As PLT # Upload the image image = cv2.imread('path/to/image.jpg') # Load the pre-trained face detection model modelo_deteccao = cv2. CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml') # Convert the image to grayscale imagem_cinza = cv2.cvtColor(image, cv2. COLOR_BGR2GRAY) # Detect the faces in the image faces = modelo_deteccao.detectMultiScale(imagem_cinza, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30)) # Check if faces have been found if len(faces) > 0: # Select only the first face found x, y, w, h = faces[0] # Crop the face region face = image[y:y+h, x:x+w] # Resize the face to the appearance of 16 years rosto_redimensionado = cv2.resize(face, (0, 0), fx=0.8, fy=0.8) # Load the template body image modelo_corpo = cv2.imread('path/to/imagem_modelo.jpg') # Resize the template body to the desired size modelo_corpo_redimensionado = cv2.resize(modelo_corpo, (w, h)) # Merge the resized face with the template body imagem_final = cv2.addWeighted(rosto_redimensionado, 0.5, modelo_corpo_redimensionado, 0.5, 0) # Display the final image plt.imshow(cv2.cvtColor(imagem_final, cv2. COLOR_BGR2RGB)) plt.axis('off') plt.show() else: print("No face was found in the image.")

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