将#!/usr/bin/env python2.7 -- coding: UTF-8 -- import time import cv2 from PIL import Image import numpy as np from PIL import Image if name == 'main': rtsp_url = "rtsp://127.0.0.1:8554/live" cap = cv2.VideoCapture(rtsp_url) #判断摄像头是否可用 #若可用，则获取视频返回值ref和每一帧返回值frame if cap.isOpened(): ref, frame = cap.read() else: ref = False #间隔帧数 imageNum = 0 sum=0 timeF = 24 while ref: ref,frame=cap.read() sum+=1 #每隔timeF获取一张图片并保存到指定目录 #"D:/photo/"根据自己的目录修改 if (sum % timeF == 0): # 格式转变，BGRtoRGB frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) # 转变成Image frame = Image.fromarray(np.uint8(frame)) frame = np.array(frame) # RGBtoBGR满足opencv显示格式 frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR) imageNum = imageNum + 1 cv2.imwrite("/root/Pictures/Pictures" + str(imageNum) + '.png', frame) print("success to get frame") #1毫秒刷新一次 k = cv2.waitKey(1) #按q退出 #if k==27：则为按ESC退出 if k == ord('q'): cap.release() break和#!/usr/bin/env python2.7 coding=UTF-8 import os import sys import cv2 from pyzbar import pyzbar def main(image_folder_path, output_file_name): img_files = [f for f in os.listdir(image_folder_path) if f.endswith(('.png'))] qr_codes_found = [] print("Image files:") for img_file in img_files: print(img_file) for img_file in img_files: img_path = os.path.join(image_folder_path,img_file) img = cv2.imread(img_path) barcodes = pyzbar.decode(img) for barcode in barcodes: if barcode.type == 'QRCODE': qr_data = barcode.data.decode("utf-8") qr_codes_found.append((img_file, qr_data)) unique_qr_codes = [] for file_name, qr_content in qr_codes_found: if qr_content not in unique_qr_codes: unique_qr_codes.append(qr_content) with open(output_file_name,'w') as f: for qr_content in unique_qr_codes: f.write("{}\n".format(qr_content)) if name == "main": image_folder_path = '/root/Pictures' output_file_name = 'qr_codes_found.txt' main(image_folder_path,output_file_name)合并一下

您可以将两个代码合并为一个ROS节点，以便在同一个程序中运行。下面是合并后的代码：

#!/usr/bin/env python2.7
# -*- coding: UTF-8 -*-

import time
import cv2
from PIL import Image
import numpy as np
from PIL import Image
import os
import sys
from pyzbar import pyzbar
from std_msgs.msg import String
import rospy

def capture_and_recognize():

    # 初始化ROS节点
    rospy.init_node('capture_and_recognize_node', anonymous=True)
    
    # 创建图像识别结果的发布者
    pub = rospy.Publisher('recognition_result', String, queue_size=10)

    # 设置摄像头参数
    rtsp_url = "rtsp://127.0.0.1:8554/live"
    cap = cv2.VideoCapture(rtsp_url)

    # 判断摄像头是否可用
    # 若可用，则获取视频返回值ref和每一帧返回值frame
    if cap.isOpened():
        ref, frame = cap.read()
    else:
        ref = False

    # 间隔帧数
    imageNum = 0
    sum = 0
    timeF = 24

    while ref:
        ref, frame = cap.read()
        sum += 1

        # 每隔timeF获取一张图片并保存到指定目录
        # "D:/photo/"根据自己的目录修改
        if (sum % timeF == 0):

            # 格式转变，BGRtoRGB
            frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
            # 转变成Image
            frame = Image.fromarray(np.uint8(frame))
            frame = np.array(frame)
            # RGBtoBGR满足opencv显示格式
            frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)

            imageNum = imageNum + 1
            cv2.imwrite("/root/Pictures/Pictures" + str(imageNum) + '.png', frame)

            print("success to get frame")

            # 图像识别
            img_path = "/root/Pictures/Pictures" + str(imageNum) + '.png'
            img = cv2.imread(img_path)
            barcodes = pyzbar.decode(img)
            qr_codes_found = []

            for barcode in barcodes:
                if barcode.type == 'QRCODE':
                    qr_data = barcode.data.decode("utf-8")
                    qr_codes_found.append(qr_data)

            unique_qr_codes = []
            for qr_content in qr_codes_found:
                if qr_content not in unique_qr_codes:
                    unique_qr_codes.append(qr_content)

            # 发布图像识别结果
            for qr_content in unique_qr_codes:
                pub.publish(qr_content)

        # 1毫秒刷新一次
        k = cv2.waitKey(1)

        # 按q退出
        # 如果按下的是q键，则退出循环
        if k == ord('q'):
            cap.release()
            break

if __name__ == '__main__':
    try:
        capture_and_recognize()
    except rospy.ROSInterruptException:
        pass

在这个合并的代码中，我们使用了ROS的Python库rospy来创建一个ROS节点。我们初始化了一个节点，创建了一个用于发布图像识别结果的话题，并在适当的位置发布识别结果。您可以根据需要进一步调整代码以满足您的机器人运行环境的要求。