Im new to neural network development
i got pretrained YOLO8s model and trained it on my custom dataset, made a python class, using cv2 to display the results
now i need help passing my cv2 yolov8s video feed to a django application i got for my project, how do i do that?

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from ultralytics import YOLO
from pathlib import Path
import cv2, onnx, onnxoptimizer,numpy,onnxruntime
import torch.onnx
import torchvision.models as models
from database.db import *
from pprint import pprint as pt


class Main_field: 

    def __init__(self, model, size, source, conf_):
        self.model = self.load_model(model) 
        self.size = size                    
        self.source = source               
        self.conf_ = conf_                  

    def __call__(self): 
        self.process_video()

    def load_model(self, model):
        model.fuse()                      
        return model

    def process_video(self):
        cap = cv2.VideoCapture(self.source) 
        while True:
            ret, frame = cap.read() 
            if not ret: break
            
            results = self.model.predict(frame, conf=self.conf_, imgsz=self.size) 

            masks_dict=[result.names for result in results][0] 
            xyxys=[result.boxes.cpu().numpy().xyxy for result in results][0] #xyxy 
            mask_ids=[result.boxes.cpu().numpy().cls.astype(int).tolist() for result in results][0] 
            masks=[masks_dict[itr] for itr in mask_ids] 

            db_output=[check_(local_list,str(itr)) for itr in mask_ids if itr] 
            
            video_outp=cv2.imshow("_________", results[0].plot()) 
            pt(mask_ids)

            if cv2.waitKey(1) & 0xFF == ord('q'): break
        
        def __del__():
            cap.release()
            cv2.destroyAllWindows()

def init_model(path: str) -> any: return YOLO(path)

”’

looking for examples on how can i pass constant video feed to my web page