1 pyzbar二維碼檢測模塊

• pyzbar的github主頁：https://github.com/NaturalHistoryMuseum/pyzbar
• pyzbar的pypi主頁：https://pypi.org/project/pyzbar/

1.1. pyzbar模塊介紹

1、該模塊是一個日本的author開源的一個二維碼檢測的專案，可以用來檢測：

• 二維碼
• 條形碼

同時可以回傳檢測二維碼和條形碼的相關資訊：

• 二維碼中包含的資訊
• 檢測二維碼的矩形框
• 檢測二維碼的最小外接多邊形框

2、pyzbar支持兩種資料型別輸入：

• PIL讀取的PIL.Image資料型別
• opencv讀取的ndarray資料型別

1.2 pyzbar模塊的安裝

1、Mac OS X：

brew install zbar

2、Linux：

sudo apt-get install libzbar0

3、直接使用pip安裝

pip install pyzbar

1.3 pyzbar模塊測驗用例

1、pyzbar的decode接受測PIL.Image的實體

圖片：

>>> from pyzbar.pyzbar import decode
>>> from PIL import Image
>>> decode(Image.open('pyzbar/tests/code128.png'))
[
    Decoded(
        data=b'Foramenifera', type='CODE128',
        rect=Rect(left=37, top=550, width=324, height=76),
        polygon=[
            Point(x=37, y=551), Point(x=37, y=625), Point(x=361, y=626),
            Point(x=361, y=550)
        ]
    )
    Decoded(
        data=b'Rana temporaria', type='CODE128',
        rect=Rect(left=4, top=0, width=390, height=76),
        polygon=[
            Point(x=4, y=1), Point(x=4, y=75), Point(x=394, y=76),
            Point(x=394, y=0)
        ]
    )
]

從上面的內容可以看到，回傳檢測到兩個條形二維碼，每個條形二維碼包含內容：

• 條形碼中存盤的內容
• 條形碼的型別，例如這里的CODE128
• 檢測到條形碼的矩形框，矩形框的左上角坐標和矩形框的寬與高
• 檢測到條形碼的外接多邊形框的四個點坐標

2、檢測二維碼

測驗圖片（圖片來源pyzbar的github專案）：

from PIL import Image, ImageDraw

from pyzbar.pyzbar import decode


image = Image.open('./qrcode_rotated.png').convert('RGB')
draw = ImageDraw.Draw(image)
for barcode in decode(image):
    rect = barcode.rect
    draw.rectangle(
        (
            (rect.left, rect.top),
            (rect.left + rect.width, rect.top + rect.height)
        ),
        outline='#0080ff'
    )

    draw.polygon(barcode.polygon, outline='#e945ff')


image.save('bounding_box_and_polygon.png')
image.show()

檢測結果：

2 python3 + opencv +pyzbar實時檢測二維碼，并繪制二維碼的矩形框

• 連接攝像頭，運行程式即可實時檢測二維碼
• 按q鍵，退出顯示和程式運行

__Author__ = "Shliang"
__Email__ = "shliang0603@gmail.com"

# coding:utf8

import cv2
import pyzbar.pyzbar as pyzbar
import numpy as np


def decodeDisplay(image):
    barcodes = pyzbar.decode(image)
    rects_list = []
    polygon_points_list = []
    QR_info = []

    # 這里回圈，因為畫面中可能有多個二維碼
    for barcode in barcodes:
        # 提取條形碼的邊界框的位置
        # 畫出影像中條形碼的邊界框
        (x, y, w, h) = barcode.rect
        rects_list.append((x, y, w, h))
        cv2.rectangle(image, (x, y), (x + w, y + h), (0, 0, 255), 2)
        polygon_points = barcode.polygon
        # print(f"polygon_points: {polygon_points}")  # polygon_points: [Point(x=217, y=174), Point(x=257, y=353), Point(x=433, y=316), Point(x=394, y=140)]
        # print(f"polygon_points: {polygon_points[0]}")  # polygon_points: Point(x=217, y=174)
        point_x, point_y = polygon_points[0]
        # print(f"point_x, point_y: {point_x, point_y}")  # point_x, point_y: (217, 174)

        extract_polygon_points = np.zeros((4, 2), dtype=np.int)
        for idx, points in enumerate(polygon_points):
            point_x, point_y = points  # 默認得到的point_x, point_y是float64型別
            extract_polygon_points[idx] = [point_x, point_y]

        print(extract_polygon_points.shape)  # (4, 2)

        # 不reshape成 (4,1 2)也是可以的
        extract_polygon_points = extract_polygon_points.reshape((-1, 1, 2))
        polygon_points_list.append(extract_polygon_points)

        # 要加上中括號，否則只會繪制四個點
        # cv2.polylines(image, extract_polygon_points, isClosed=True, color=(255, 0, 255), thickness=2)

        # 繪制多邊形
        cv2.polylines(image, [extract_polygon_points], isClosed=True, color=(255, 0, 255), thickness=2,
                      lineType=cv2.LINE_AA)

        # 條形碼資料為位元組物件，所以如果我們想在輸出影像上畫出來，就需要先將它轉換成字串
        barcodeData = barcode.data.decode("utf-8")
        barcodeType = barcode.type

        # 繪出影像上條形碼的資料和條形碼型別
        text = "{} ({})".format(barcodeData, barcodeType)
        QR_info.append(text)
        cv2.putText(image, text, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX,
                    .5, (0, 0, 125), 2)

        # 向終端列印條形碼資料和條形碼型別
        print("[INFO] Found {} barcode: {}".format(barcodeType, barcodeData))
    return image, rects_list, polygon_points_list, QR_info


def detect():
    cap = cv2.VideoCapture(0)

    while True:
        # 讀取當前幀
        ret, frame = cap.read()
        # 轉換為灰度圖是為了檢測到二維碼，如果是BGR圖很大概率是檢測不到二維碼
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        im, rects_list, polygon_points_list, QR_info = decodeDisplay(gray)

        # 把檢測到二維碼的資訊再繪制到BGR彩色影像上
        for data in zip(rects_list, polygon_points_list, QR_info):
            print(f"data: {data}")
            x, y, w, h = data[0]
            polygon_points = data[1]
            text = data[2]
            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2)
            cv2.polylines(frame, [polygon_points], isClosed=True, color=(255, 0, 255), thickness=2,
                          lineType=cv2.LINE_AA)
            cv2.putText(frame, text, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX,
                        .5, (0, 0, 125), 2)

        # 因為一個是單通道的灰度圖，一個是BGR三通道的彩色圖，因此不能夠拼接在一起顯示，這里就用兩個視窗顯示
        cv2.imshow("camera", im)
        cv2.imshow("frame", frame)

        # 按q鍵退出畫面顯示
        k = cv2.waitKey(1)
        if k == ord('q'):
            break


    cap.release()
    cv2.destroyAllWindows()



if __name__ == '__main__':
    detect()

顯示結果如下：