怎样做二维码识别脚本

wen 实用脚本 2026-07-01 173

本文目录导读：

怎样做二维码识别脚本

方案一：使用OpenCV（推荐，支持实时视频）
方案二：使用zbarlight（轻量级）
安装依赖
使用示例
高级功能版本

我来帮你创建一个二维码识别脚本,以下是使用Python和OpenCV的实现方法：

使用OpenCV（推荐，支持实时视频）

import cv2
import numpy as np
from pyzbar.pyzbar import decode
import sys
def decode_qr_from_image(image_path):
    """从图片文件识别二维码"""
    # 读取图片
    img = cv2.imread(image_path)
    if img is None:
        print(f"无法读取图片: {image_path}")
        return
    # 解码二维码
    decoded_objects = decode(img)
    for obj in decoded_objects:
        print(f"二维码类型: {obj.type}")
        print(f"二维码数据: {obj.data.decode('utf-8')}")
        # 在图片上绘制边框
        points = obj.polygon
        if len(points) > 4:
            hull = cv2.convexHull(np.array([point for point in points], dtype=np.float32))
            points = hull
        n = len(points)
        for j in range(n):
            cv2.line(img, tuple(points[j]), tuple(points[(j+1) % n]), (0, 255, 0), 3)
        # 显示解码内容
        x, y, w, h = obj.rect
        cv2.putText(img, obj.data.decode('utf-8'), (x, y-10), 
                   cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2)
    # 显示结果
    cv2.imshow("QR Code Decoder", img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()
def decode_qr_from_camera():
    """从摄像头实时识别二维码"""
    cap = cv2.VideoCapture(0)
    if not cap.isOpened():
        print("无法打开摄像头")
        return
    print("按 'q' 键退出")
    while True:
        ret, frame = cap.read()
        if not ret:
            break
        # 解码二维码
        decoded_objects = decode(frame)
        for obj in decoded_objects:
            # 绘制边框
            points = obj.polygon
            if len(points) > 4:
                hull = cv2.convexHull(np.array([point for point in points], dtype=np.float32))
                points = hull
            n = len(points)
            for j in range(n):
                cv2.line(frame, tuple(points[j]), tuple(points[(j+1) % n]), (0, 255, 0), 3)
            # 显示数据
            x, y, w, h = obj.rect
            data = obj.data.decode('utf-8')
            cv2.putText(frame, data, (x, y-10), 
                       cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
            print(f"识别到二维码: {data}")
        # 显示视频
        cv2.imshow("QR Code Scanner", frame)
        # 按 'q' 退出
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    cap.release()
    cv2.destroyAllWindows()
def decode_qr_from_screen():
    """从屏幕截图识别二维码（Windows）"""
    try:
        from PIL import ImageGrab
        import pyautogui
    except ImportError:
        print("需要安装 Pillow 和 pyautogui")
        print("pip install Pillow pyautogui")
        return
    print("程序将运行5秒，请将二维码放在屏幕上")
    print("按 Ctrl+C 退出")
    import time
    for i in range(5):
        # 截取屏幕
        screen = ImageGrab.grab()
        screen_np = np.array(screen)
        screen_bgr = cv2.cvtColor(screen_np, cv2.COLOR_RGB2BGR)
        # 解码
        decoded_objects = decode(screen_bgr)
        for obj in decoded_objects:
            data = obj.data.decode('utf-8')
            print(f"识别到二维码: {data}")
            # 绘制边框
            points = obj.polygon
            if len(points) > 4:
                hull = cv2.convexHull(np.array([point for point in points], dtype=np.float32))
                points = hull
            n = len(points)
            for j in range(n):
                cv2.line(screen_bgr, tuple(points[j]), tuple(points[(j+1) % n]), (0, 255, 0), 3)
        cv2.imshow("Screen QR Scanner", screen_bgr)
        cv2.waitKey(1)
        time.sleep(1)
    cv2.destroyAllWindows()
if __name__ == "__main__":
    if len(sys.argv) > 1:
        # 命令行参数处理
        if sys.argv[1] == "camera":
            decode_qr_from_camera()
        elif sys.argv[1] == "screen":
            decode_qr_from_screen()
        else:
            decode_qr_from_image(sys.argv[1])
    else:
        print("使用方法:")
        print("  识别图片: python qr_scanner.py image.jpg")
        print("  摄像头识别: python qr_scanner.py camera")
        print("  屏幕识别: python qr_scanner.py screen")

使用zbarlight（轻量级）

import zbarlight
from PIL import Image
def decode_qr_with_zbarlight(image_path):
    """使用zbarlight库识别二维码"""
    try:
        # 打开图片
        with open(image_path, 'rb') as image_file:
            image = Image.open(image_file)
            image = image.convert('L')  # 转换为灰度图
            # 解码所有二维码
            codes = zbarlight.scan_codes('qrcode', image)
            if codes:
                for code in codes:
                    print(f"二维码内容: {code.decode('utf-8')}")
            else:
                print("未识别到二维码")
    except Exception as e:
        print(f"识别失败: {e}")
def batch_decode_qr(folder_path):
    """批量识别文件夹中的二维码图片"""
    import os
    for filename in os.listdir(folder_path):
        if filename.lower().endswith(('.png', '.jpg', '.jpeg', '.bmp')):
            filepath = os.path.join(folder_path, filename)
            print(f"处理: {filename}")
            decode_qr_with_zbarlight(filepath)
            print("-" * 30)

安装依赖

# 主要依赖
pip install opencv-python
pip install pyzbar
pip install Pillow
pip install numpy
# 以下为可选
pip install zbarlight  # 轻量级二维码识别
pip install pyautogui  # 屏幕截图功能

使用示例

# 单张图片识别
python qr_scanner.py qrcode.jpg
# 摄像头实时识别
python qr_scanner.py camera
# 屏幕识别
python qr_scanner.py screen

高级功能版本

import cv2
import numpy as np
from pyzbar.pyzbar import decode
import json
import requests
from urllib.parse import urlparse
class AdvancedQRScanner:
    def __init__(self):
        self.scanned_codes = set()  # 避免重复识别
    def decode_qr(self, image):
        """解码二维码并返回详细结果"""
        results = []
        decoded_objects = decode(image)
        for obj in decoded_objects:
            data = obj.data.decode('utf-8')
            # 避免重复识别
            if data in self.scanned_codes:
                continue
            self.scanned_codes.add(data)
            # 检测是否为URL
            is_url = self.is_valid_url(data)
            result = {
                'data': data,
                'type': obj.type,
                'is_url': is_url,
                'rect': {
                    'x': obj.rect.left,
                    'y': obj.rect.top,
                    'width': obj.rect.width,
                    'height': obj.rect.height
                },
                'points': [(p.x, p.y) for p in obj.polygon]
            }
            results.append(result)
            # 如果是URL，可以自动访问
            if is_url:
                self.check_url_accessibility(data)
        return results
    def is_valid_url(self, text):
        """检查是否为有效URL"""
        try:
            result = urlparse(text)
            return all([result.scheme, result.netloc])
        except:
            return False
    def check_url_accessibility(self, url):
        """检查URL是否可访问"""
        try:
            response = requests.head(url, timeout=5)
            print(f"URL状态: {response.status_code}")
        except:
            print(f"无法访问URL: {url}")
    def save_results(self, results, filename='qr_results.json'):
        """保存识别结果到文件"""
        with open(filename, 'w', encoding='utf-8') as f:
            json.dump(results, f, ensure_ascii=False, indent=2)
        print(f"结果已保存到 {filename}")
    def visualize_results(self, image, results):
        """在图片上可视化识别结果"""
        for result in results:
            points = result['points']
            if len(points) > 4:
                hull = cv2.convexHull(np.array(points, dtype=np.float32))
                points = hull
            n = len(points)
            for j in range(n):
                cv2.line(image, tuple(points[j]), tuple(points[(j+1) % n]), (0, 255, 0), 3)
            x, y = result['rect']['x'], result['rect']['y']
            cv2.putText(image, result['data'][:20] + '...' if len(result['data']) > 20 else result['data'], 
                       (x, y-10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
        return image
# 使用示例
if __name__ == "__main__":
    scanner = AdvancedQRScanner()
    # 识别图片
    img = cv2.imread("qrcode.jpg")
    results = scanner.decode_qr(img)
    for result in results:
        print(f"识别到: {result['data']}")
        print(f"类型: {result['type']}")
        print(f"是否URL: {result['is_url']}")
    # 保存结果
    scanner.save_results(results)

这个脚本支持：