#!/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 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': 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 # 如果按下的是q键，则退出循环 if k == ord('q'): cap.release() image_folder_path = '/root/Pictures' output_file_name = 'qr_codes_found.txt' main(image_folder_path,output_file_name)无法生成所需文本

根据您提供的代码，我注意到您的`main`函数缩进不正确，这可能导致代码执行时出现问题。确保在定义`main`函数时函数体内的所有代码都正确缩进请尝试使用以下代码替换您的代码，以确保`main`函数及其调用位于正确位置：

import time
import cv2
from PIL import Image
import numpy as np
import os
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__':
    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
    # 如果按下的是q键，则退出循环
    if k == ord('q'):
        cap.release()

    image_folder_path = '/root/Pictures'
    output_file_name = 'qr_codes_found.txt'
    main(image_folder_path, output_file_name)

请注意，上述代码假设`image_folder_path`是您要处理的图像文件所在的实际文件夹路径，并将结果写入名为`qr_codes_found.txt`的输出文件中。确保根据需要修改这些值。另外，请确保您的代码中没有其他语法错误或逻辑错误，这可能会导致生成所需文本的问题。