import os
import warnings

os.environ['TF_ENABLE_ONEDNN_OPTS']=str(0)
warnings.filterwarnings('ignore')

#import pandas as pd
import numpy as np

from deepface import DeepFace
from db import create_db, get_student_row
from helper_fns import  binary_to_pil, extract_faces




def verify_student(db_path, last_name, matric_no, input_image):
    data = get_student_row(db_path, last_name, matric_no)
    
    if data is not None:
        binary_image = data['image']
    else: 
        raise ValueError('No student having last name {last_name} and matric no: {matric_no} exists in this database.')
    actual_image =np.array(binary_to_pil(binary_image))

    webcam_image = input_image
    if webcam_image is None:
        raise ValueError(f'No image')
    else:
        print('Received image')
        print(type(webcam_image))
    results = DeepFace.verify(#webcam_image,
                            actual_image,
                            actual_image,
                            model_name='Facenet',
                            detector_backend="retinaface",
                            distance_metric="cosine",
                            enforce_detection=True,
                            anti_spoofing=True,
                            align=True,
                            normalization="Facenet")
    result = results['verified']
    if results['verified'] == True:
        result = f"Verification check complete! Successfully verified student: {data['last_name']} {data['first_name']} with matriculation number {data['matric_no']}"
    else:
        result = f"Verification check complete! You are not student {data['last_name']} {data['first_name']} with matriculation number {data['matric_no']}"
        
    cropped_input_image, cropped_returned_image = extract_faces(webcam_image, actual_image, results)
    return result, cropped_input_image, cropped_returned_image, actual_image


def main(last_name, matric_no, input_image):

    #df = pd.read_csv('students_df.csv')
    db_path = 'students_database.db'
    #create_db(db_path, df)
        
    result, cropped_input_image, cropped_returned_image, actual_image = verify_student(db_path,
                                                                                        last_name,
                                                                                        matric_no,
                                                                                        input_image)

    #os.remove('students_database.db')
    return result, cropped_input_image, cropped_returned_image, actual_image

if __name__ ==  '__main__':
    main()