import cv2,json
from base64 import b64encode

from schema import *


class ParsingMsg():
    
    IMAGE_FORMAT = 'jpg'
    
    def __init__(self):
        self.msg = None
        self.img = None
        self.ward_id = None
        
        self.parsed_msg = None

    def set(self, msg:list, img, ward_id):
        self.msg = None
        self.img = None
        self.ward_id = None
        
        self.msg = msg
        self.img = img
        self.ward_id = ward_id
        self.parsed_msg = None
    
    def get(self):
        result = self.parsed_msg
        return result
    
    def image_encoding(self, img_data):
        """
        이미지데이터(np.ndarray) 를 바이너리 데이터로 변환
        :param img_data: 이미지 데이터
        :return: base64 format
        """
        _, JPEG = cv2.imencode(".jpg", img_data, [int(cv2.IMWRITE_JPEG_QUALITY), 80])
        # Base64 encode
        b64 = b64encode(JPEG.tobytes())

        return b64.decode("utf-8")
    
    def image_cropping(self, img_data, bbox):
        """
        이미지데이터(np.ndarray) 를 bbox 기준으로 크롭
        :param img_data: 이미지 데이터
        :param bbox: [x1, y1, x2, y2]
        :return: cropped image data
        """
        x1, y1, x2, y2 = bbox
        cropped_img = img_data[y1:y2, x1:x2]
        return cropped_img
    
    def parse_header(self):
        """
        *camera_id, ward_id, frame_id 미구현
        """
        msg = Header(
            camera_id= "CAMERA_001",
            ward_id= self.ward_id,
            timestamp= datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
            frame_id= 0
        )
        return msg
    
    def parse_summary(self, activate_cnt, total_cnt):
        """
        *system_health 미구현
        """
        msg = Summary(
            total_objects_count= total_cnt,
            active_alerts_count= activate_cnt,
            system_health= SyestemHealth.ok
        )
        return msg
    
    def parse_object(self):
        """
        *bbox,skeleton 제외 전부 미구현
        """
        msg = []
        activate_cnt = 0
        total_cnt = 0
        
        if self.msg:
            
            for i in self.msg:
                
                has_img = True if i.get('person') and self.img is not None else False
                b64_img = self.image_encoding(self.image_cropping(self.img, i.get('person'))) if has_img else ''
                if i['result']['pose_type'] > 0:
                    activate_cnt += 1
                total_cnt += 1
                
                sub_msg = DetectedObject(
                    tracking_id= i['result']['object_id'],
                    status= Status.stable if i['result']['pose_type'] == 0 else Status.fall_detected,
                    status_detail= None if i['result']['pose_type'] == 0 else StatusDetail.sudden_fall,
                    severity= None if i['result']['pose_type'] == 0 else Severity.critical,
                    location_zone= 'ZONE_001',
                    duration= 0.0,
                    bbox= i.get('person'),
                    skeleton= [[round(x, 0) for x in kpt] + [round(conf,2)] for kpt, conf in zip(i.get('keypoints'), i.get('kpt_conf'))],
                    metrics=Metrics(
                        velocity=0.0,
                        angle=0.0
                    ),
                    visual_data=ObjectVisualData(
                        format=self.IMAGE_FORMAT,
                        has_image= has_img,
                        base64_str= b64_img
                    )
                )
                msg.append(sub_msg)
        return msg, activate_cnt, total_cnt
                    
    def parse_virtual(self):
        has_img = True if self.img is not None else False
        b64_img = self.image_encoding(self.img) if has_img else ''
            
        msg= VisualData(
            format=self.IMAGE_FORMAT,
            has_image= has_img,
            base64_str= b64_img
        )
        
        return msg
    
    def parse(self):
        """
        * 위험note 여부는 수정 필요
        """
        object_msg, activate_cnt, total_cnt = self.parse_object()
        
        if activate_cnt == 0:
            return None
        
        header_msg = self.parse_header()
        summary_msg = self.parse_summary(activate_cnt, total_cnt)
        visual_msg = self.parse_virtual()
        
        parsing_msg = FallDetectionSchema(
            header= header_msg,
            summary= summary_msg,
            objects= object_msg,
            visual_data= visual_msg
        )
        
        return parsing_msg.model_dump_json()