Meilleure détection d'objet et algorithme de suivi

Je suis Newbie pour OpenCV. Je souhaite créer un algorithme de détection d'objet qui suit un joueur de football. Je veux savoir qui est ce joueur quel est son numéro de maillot. Je veux savoir est la meilleure façon de le trouver. Quel algorithme dois-je utiliser? J'ai fait un projet qui suit l'utilisateur avec la plage de couleurs dans laquelle j'ai converti chaque image vidéo en HSV code>. Mais le défi me vient à moi, c'est qu'après avoir détecté le joueur, comment puis-je trouver le numéro de maillot.

Voici mon code - P>

#Import libraries
import cv2
import os
import numpy as np

# import the necessary packages
from collections import deque
import numpy as np
import cv2
import imutils
import time


#Reading the video
vidcap = cv2.VideoCapture('football.mp4')
success,image = vidcap.read()

count = 0
success = True
idx = 0

#Read the video frame by frame
while success:
    #converting into hsv image
    hsv = cv2.cvtColor(image,cv2.COLOR_BGR2HSV)
    #green range
    lower_green = np.array([40,40, 40])
    upper_green = np.array([70, 255, 255])
    #blue range
    lower_blue = np.array([110,50,50])
    upper_blue = np.array([130,255,255])

    #Red range
    lower_red = np.array([0,31,255])
    upper_red = np.array([176,255,255])

    #white range
    lower_white = np.array([0,0,0])
    upper_white = np.array([0,0,255])

    #Define a mask ranging from lower to uppper
    mask = cv2.inRange(hsv, lower_green, upper_green)
    #Do masking
    res = cv2.bitwise_and(image, image, mask=mask)

    #convert to hsv to gray
    res_bgr = cv2.cvtColor(res,cv2.COLOR_HSV2BGR)
    res_gray = cv2.cvtColor(res,cv2.COLOR_BGR2GRAY)

    #Defining a kernel to do morphological operation in threshold image to 
    #get better output.
    kernel = np.ones((13,13),np.uint8)
    thresh = cv2.threshold(res_gray,127,255,cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
    thresh = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)


    #find contours in threshold image     
    im2,contours,hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)

    prev = 0
    font = cv2.FONT_HERSHEY_SIMPLEX

    for c in contours:
        x,y,w,h = cv2.boundingRect(c)
        #Detect players
        if(h>=(1.5)*w):
            if(w>15 and h>= 15):
                idx = idx+1
                player_img = image[y:y+h,x:x+w]
                player_hsv = cv2.cvtColor(player_img,cv2.COLOR_BGR2HSV)
                #If player has blue jersy
                mask1 = cv2.inRange(player_hsv, lower_blue, upper_blue)
                res1 = cv2.bitwise_and(player_img, player_img, mask=mask1)
                res1 = cv2.cvtColor(res1,cv2.COLOR_HSV2BGR)
                res1 = cv2.cvtColor(res1,cv2.COLOR_BGR2GRAY)

                nzCount = cv2.countNonZero(res1)
                #If player has red jersy
                mask2 = cv2.inRange(player_hsv, lower_red, upper_red)
                res2 = cv2.bitwise_and(player_img, player_img, mask=mask2)
                res2 = cv2.cvtColor(res2,cv2.COLOR_HSV2BGR)
                res2 = cv2.cvtColor(res2,cv2.COLOR_BGR2GRAY)
                nzCountred = cv2.countNonZero(res2)

                if(nzCount >= 20):
                    #Mark blue jersy players as france
                    cv2.putText(image, 'France', (x-2, y-2), font, 0.8, (255,0,0), 2, cv2.LINE_AA)
                    cv2.rectangle(image,(x,y),(x+w,y+h),(255,0,0),3)
                else:
                    pass
                if(nzCountred>=20):
                    #Mark red jersy players as belgium
                    cv2.putText(image, 'Belgium', (x-2, y-2), font, 0.8, (0,0,255), 2, cv2.LINE_AA)
                    cv2.rectangle(image,(x,y),(x+w,y+h),(0,0,255),3)
                else:
                    pass
        if((h>=1 and w>=1) and (h<=30 and w<=30)):
            player_img = image[y:y+h,x:x+w]

            player_hsv = cv2.cvtColor(player_img,cv2.COLOR_BGR2HSV)
            #white ball  detection
            mask1 = cv2.inRange(player_hsv, lower_white, upper_white)
            res1 = cv2.bitwise_and(player_img, player_img, mask=mask1)
            res1 = cv2.cvtColor(res1,cv2.COLOR_HSV2BGR)
            res1 = cv2.cvtColor(res1,cv2.COLOR_BGR2GRAY)
            nzCount = cv2.countNonZero(res1)


            if(nzCount >= 3):
                # detect football
                cv2.putText(image, 'football', (x-2, y-2), font, 0.8, (0,255,0), 2, cv2.LINE_AA)
                cv2.rectangle(image,(x,y),(x+w,y+h),(0,255,0),3)


    cv2.imwrite("./Cropped/frame%d.jpg" % count, res)
    # print('Read a new frame: ', success)    # save frame as JPEG file 
    count += 1
    cv2.imshow('Match Detection',image)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
    success,image = vidcap.read()

vidcap.release()
cv2.destroyAllWindows()