from django.conf import settings
import uuid
import face_recognition
import os
from apps.hrm.models import Employee
from apps.hrm.tasks import update_all_user_facedata_cache
from apps.system.models import User
from django.core.cache import cache

class HRMService:

    @classmethod
    def face_compare_from_path(cls, path):
        filepath = settings.BASE_DIR +path
        try:
            unknown_picture = face_recognition.load_image_file(filepath)
            unknown_face_encoding = face_recognition.face_encodings(unknown_picture, num_jitters=2)[0]
            # os.remove(filepath)
        except:
            # os.remove(filepath)
            return None, '识别失败,请调整位置'

        # 匹配人脸库
        face_datas = cache.get('face_datas')
        if face_datas is None:
            update_all_user_facedata_cache()
            face_datas = cache.get('face_datas')
        face_users = cache.get('face_users')
        results = face_recognition.compare_faces(face_datas, 
        unknown_face_encoding, tolerance=0.46)
        for index, value in enumerate(results):
            if value:
                # 识别成功
                user = User.objects.get(id=face_users[index])
                return user, ''   
        return None, '人脸未匹配,请调整位置'

    @classmethod
    def face_compare_from_base64(cls, base64_data):
        filename = str(uuid.uuid4())
        filepath = settings.BASE_DIR +'/temp/' + filename +'.png'
        with open(filepath, 'wb') as f:
            f.write(base64_data)
        try:
            unknown_picture = face_recognition.load_image_file(filepath)
            unknown_face_encoding = face_recognition.face_encodings(unknown_picture, num_jitters=2)[0]
            os.remove(filepath)
        except:
            os.remove(filepath)
            return None, '识别失败,请调整位置'

        # 匹配人脸库
        face_datas = cache.get('face_datas')
        if face_datas is None:
            update_all_user_facedata_cache()
            face_datas = cache.get('face_datas')
        face_users = cache.get('face_users')
        results = face_recognition.compare_faces(face_datas, 
        unknown_face_encoding, tolerance=0.46)
        for index, value in enumerate(results):
            if value:
                # 识别成功
                user = User.objects.get(id=face_users[index])
                return user, ''
        user_index = cls.get_user_index(results)
        user_index_len = len(user_index)
        if user_index_len == 1:
            user = User.objects.get(id=face_users[user_index[0]])
            return user, ''
        elif user_index_len == 0:
            return None, '人脸未匹配,请调整位置'
        else:
            user_ids = []
            for i in user_index:
                user_ids.append(face_users[i])
            user_name_str = ','.join(list(User.objects.filter(id__in=user_ids).values_list('name', flat=True)))
            return None, '匹配多张人脸:' + user_name_str
        

    @classmethod
    def get_user_index(cls, results):
        """
        返回user_index列表
        """
        true_num = 0
        user_index = []
        for index, value in enumerate(results):
            if value:
                true_num = true_num + 1
                user_index.append(index)
        return user_index

    @classmethod
    def get_facedata_from_img(cls, img_path):
        try:
            photo_path = settings.BASE_DIR + img_path
            picture_of_me = face_recognition.load_image_file(photo_path)
            my_face_encoding = face_recognition.face_encodings(picture_of_me, num_jitters=2)[0]
            face_data_list = my_face_encoding.tolist()
            return face_data_list, ''
        except:
            return None, '人脸数据获取失败请重新上传图片'