多尺度模板匹配

效果特别差 只能用来识别简单的东西
仅供练手

import cv2
import numpy as np
import os
import time

cap=cv2.VideoCapture('Camera Roll/3.mp4')#视频加载 读摄像头就填0
temp=cv2.imread('Camera Roll/temp3.jpg') #模板

gray_temp=cv2.cvtColor(temp, cv2.COLOR_BGR2GRAY)

h_t,w_t,c_t=temp.shape[:]
cv2.imshow('gray-',gray_temp)

if cap.isOpened() !=True:#判断视频是否打开
    os._exit(-1)
counter=0 #计数初始化
while True:
    start =time.clock() 
    success,frame=cap.read()
    if success != True:
        break
    if counter%3==0:#隔三帧处理一次

        h, w, c = frame.shape[:]
        print('h,w',h,w)
        H=0.6*h
        W1=0.1*w
        W2=0.9*w
        dst = frame[int(H):h, int(W1):int(W2)]#视频剪裁 减少其他区域的误识别
        h_c,w_c,c_c=dst.shape[:]
        #print('h_c,w_c:',h_c,w_c)

        gray_frame = cv2.cvtColor(dst, cv2.COLOR_BGR2GRAY)

        for r in np.linspace(1, 2,10 )[::-1]:
            # 根据尺度大小对模板图片进行缩放
            resized = cv2.resize(gray_temp, (0, 0), fx=r, fy=r, interpolation=cv2.INTER_NEAREST)
            # 匹配模板
            if resized.shape[0]> frame.shape[0] or resized.shape[1]> frame.shape[1]:
                print('模板比图片大')
                break
            res = cv2.matchTemplate(gray_frame, resized, cv2.TM_CCOEFF_NORMED)
            loc = np.where(res >= 0.6)
            for pt in zip(*loc[::-1]):
                #print(pt)
                (startx, starty) = (int(pt[0]+W1), int(pt[1]+H))
                (endx, endy) = (int(pt[0]+W1 + h_t*r), int(pt[1]+H + w_t *r))
                cv2.rectangle(frame, (startx, starty), (endx, endy), (0, 255, 0), 3)
                #cv2.rectangle(frame,pt,(pt[0]+h_t*r,pt[1]+w_t*r), (0, 255, 0), 3)
        cv2.imshow('result',frame)
    counter +=1
    if cv2.waitKey(40) & 0xFF == ord('q'):  
        break
    end=time.clock()
    print('=============')
    print('time', end-start)
cap.release()  # 释放资源
cv2.destroyWindow()  #关闭窗口