from rembg import remove
import cv2
import numpy as np
import os
import time
from datetime import datetime, timedelta


def delete_old_files(folder_path, days_old):
    # 獲取當前時間
    now = time.time()
    # 計算指定的時間差
    cutoff = now - (days_old * 86400)  # 86400 是一天的秒數

    # 遍歷資料夾中的所有檔案
    for filename in os.listdir(folder_path):
        file_path = os.path.join(folder_path, filename)
        # 確認這是個檔案
        if os.path.isfile(file_path):
            # 獲取檔案的最後修改時間
            file_mtime = os.path.getmtime(file_path)
            # 如果最後修改時間早於指定的時間差，則刪除該檔案
            if file_mtime < cutoff:
                os.remove(file_path)
                print(f"Deleted {file_path}")

async def remove_background(input_path:str,output_path:str):
    input = cv2.imread(input_path)
    output = remove(input,bgcolor=(255,255,255,0))


    cv2.imwrite(output_path, output)
    
    delete_old_files(f"{os.path.split(os.path.abspath('main.py'))[0]}/static/image",2)

async def detect_face(image_file_path):
    try :
        img = cv2.imread(image_file_path)

        file_list = image_file_path.split("/")
        filename = f"{os.path.split(os.path.abspath('main.py'))[0]}/static/image/check/{file_list[-1]}"

        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)   # 將圖片轉成灰階

        face_cascade = cv2.CascadeClassifier(f"{os.path.split(os.path.abspath('main.py'))[0]}/static/haarcascade_frontalface_default.xml")   # 載入人臉模型
        faces = face_cascade.detectMultiScale(gray)    # 偵測人臉

        print(len(faces))

        if len(faces ) == 0 :
            return {"state":"fail","msg":"no face"}

        for (x, y, w, h) in faces:
            cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 8)    # 利用 for 迴圈，抓取每個人臉屬性，繪製方框
            break

        cv2.imwrite(filename, img)

        delete_old_files(f"{os.path.split(os.path.abspath('main.py'))[0]}/static/image/remove",2)
    
        return {"state":"success","filename":f"static/image/remove/{file_list[-1]}"}

    except Exception as e :
        return {"state":"fail","msg":str(e)}