التعرف على رمز المسح الضوئي

فيديو تعليمي 15 - التعرف على رمز المسح الضوئي: https://singtown.com/learn/50017/

QRشفرة

http://cli.im/\ بإمكانك استخدام رمز الاستجابة السريعة الخاص بالعشب لإنشاء المحتوى الذي تريده.

import csi, image
csi0 = csi.CSI()

csi0.reset()
csi0.pixformat(csi.RGB565)
csi0.framesize(csi.QQVGA) # can be QVGA on M7...
csi0.snapshot(frames=30)
csi0.auto_gain(False) # must turn this off to prevent image washout...
while(True):
    img = csi0.snapshot()
    img.lens_corr(1.8) # strength of 1.8 is good for the 2.8mm lens.
    for code in img.find_qrcodes():
        print(code)

{x:46, y:38, w:78, h:81, payload:"openmv", version:1, ecc_level:2, mask:6, data_type:4, eci:0}

الباركود

http://barcode.tec-it.com/zh/Code128?data=OpenMV\ بإمكانك استخدام هذا الموقع لإنشاء رمز شريطي.

import csi, image, time, math
csi0 = csi.CSI()

csi0.reset()
csi0.pixformat(csi.GRAYSCALE)
csi0.framesize(csi.VGA) # High Res!
csi0.window((640, 80)) # V Res of 80 == less work (40 for 2X the speed).
csi0.snapshot(frames=30)
csi0.auto_gain(False)  # must turn this off to prevent image washout...
csi0.auto_whitebal(False)  # must turn this off to prevent image washout...
clock = time.clock()

# Barcode detection can run at the full 640x480 resolution of your OpenMV Cam's
# OV7725 camera module. Barcode detection will also work in RGB565 mode but at
# a lower resolution. That said, barcode detection requires a higher resolution
# to work well so it should always be run at 640x480 in grayscale...

def barcode_name(code):
    if(code.type == image.EAN2):
        return "EAN2"
    if(code.type == image.EAN5):
        return "EAN5"
    if(code.type == image.EAN8):
        return "EAN8"
    if(code.type == image.UPCE):
        return "UPCE"
    if(code.type == image.ISBN10):
        return "ISBN10"
    if(code.type == image.UPCA):
        return "UPCA"
    if(code.type == image.EAN13):
        return "EAN13"
    if(code.type == image.ISBN13):
        return "ISBN13"
    if(code.type == image.I25):
        return "I25"
    if(code.type == image.DATABAR):
        return "DATABAR"
    if(code.type == image.DATABAR_EXP):
        return "DATABAR_EXP"
    if(code.type == image.CODABAR):
        return "CODABAR"
    if(code.type == image.CODE39):
        return "CODE39"
    if(code.type == image.PDF417):
        return "PDF417"
    if(code.type == image.CODE93):
        return "CODE93"
    if(code.type == image.CODE128):
        return "CODE128"

while(True):
    clock.tick()
    img = csi0.snapshot()
    codes = img.find_barcodes()
    for code in codes:
        img.draw_rectangle(code.rect)
        print_args = (barcode_name(code), code.payload, (180 * code.rotation) / math.pi, code.quality, clock.fps())
        print("Barcode %s, Payload \"%s\", rotation %f (degrees), quality %d, FPS %f" % print_args)
    if not codes:
        print("FPS %f" % clock.fps())

Data Matrix

import csi, image
csi0 = csi.CSI()

csi0.reset()
csi0.pixformat(csi.RGB565)
csi0.framesize(csi.QQVGA) # can be QVGA on M7...
csi0.snapshot(frames=30)
csi0.auto_gain(False) # must turn this off to prevent image washout...
while(True):
    img = csi0.snapshot()
    img.lens_corr(1.8) # strength of 1.8 is good for the 2.8mm lens.
    for code in img.find_datamatrices():
        print(code)

{x:48, y:27, w:58, h:56, payload:"OpenMV", rotation:0.052360, rows:14, columns:14, capacity:8, padding:1}