version: v0.0.1

parsing_msg.py

@@ -0,0 +1,147 @@
+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.parsed_msg = None
+
+    def set(self, msg:list, img):
+        self.msg = None
+        self.img = None
+        
+        self.msg = msg
+        self.img = img
+        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)
+
+        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= "WARD_001",
+            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()
+