Remove Blur or Mask from Image

Python
1

I am using MTCNN to detect face in an image, FACENET to extract and save features from each detected face and OpenCV Gaussian Blur filter to mask the detected faces. My end goal is to find a target face in the masked image using saved features and unmask target face only. Any idea or advice ?
test1
face0
blur_face

def face_and_features(img):
    boxes, _ = mtcnn.detect(img)
    print(boxes)

    for i, box in enumerate(boxes):
        # Crop the face from the image
        a,b,c,d = box
        x1,y1,x2,y2 = int(a), int(b), int(c), int(d)
        face = img[y1:y2, x1:x2]
        cv2.imwrite(f"face{i}.jpg",face)
        
        face = cv2.resize(face, (160, 160))
        face = face.transpose((2, 0, 1))
        face = torch.from_numpy(face).float()
        face = face.unsqueeze(0)

        features = facenet(face)

        filename = "face_{}.npy".format(i)
        np.save(filename, features.detach().numpy())
        with open("bounding_boxes.txt", "a") as f:
            f.write("{}, {}, {}, {}, {}, {}, {} \n".format(x1, y1, x2, y2, filename, datetime.datetime.now(), frame_number))
    return features
       
def masking(img):
    filename = "bounding_boxes.txt"
    masked_img = img.copy()
    with open(filename,'r') as file:
        for line in file:
            x,y,w,h,f_name,time, f_no = line.split(",")
            x,y,w,h = int(x), int(y), int(w), int(h)
            roi_color = masked_img[y:h, x:w]
            masked_img[y:h, x:w] = cv2.GaussianBlur(roi_color, (51,51), 0)
    return masked_img, f_name, time, f_no
2

undeclared crosspost:

3

Any idea how to match the features and than unmask the corresponding face.