Esempio n. 1
0
def main():
    res = ncc.load_fw("./moviUsbBoot", "fw/flicRefApp.mvcmd")
    if res < 0:
        printf('load firmware error!')
        sys.exit(1)

    print("get usb %d sdk versin %s" %
          (ncc.get_usb_version(), ncc.get_sdk_version()))

    print("get fw version: %s and ncc id %s" %
          (ncc.camera_get_fw_version(), ncc.camera_get_ncc_id()))

    sensors = ncc.CameraSensor()
    sensor1 = ncc.SensorModesConfig()
    if sensors.GetFirstSensor(sensor1) == 0:
        print(
            "camera: %s, %dX%d@%dfps, AFmode:%d, maxEXP:%dus,gain[%d, %d]\n" %
            (sensor1.moduleName, sensor1.camWidth, sensor1.camHeight,
             sensor1.camFps, sensor1.AFmode, sensor1.maxEXP, sensor1.minGain,
             sensor1.maxGain))

    sensor2 = ncc.SensorModesConfig()
    while sensors.GetNextSensor(sensor2) == 0:
        print(
            "camera: %s, %dX%d@%dfps, AFmode:%d, maxEXP:%dus,gain[%d, %d]\n" %
            (sensor2.moduleName, sensor2.camWidth, sensor2.camHeight,
             sensor2.camFps, sensor2.AFmode, sensor2.maxEXP, sensor2.minGain,
             sensor2.maxGain))

    ncc.camera_select_sensor(0)  #0 1080p 1 4k
    cameraCfg = sensor1

    cam_info = ncc.CameraInfo()
    cam_info.inputFormat = ncc.IMG_FORMAT_BGR_PLANAR
    #cam_info.meanValue = [float(0.0)]*3
    cam_info.stdValue = 1

    cam_info.isOutputYUV = 1
    cam_info.isOutputH26X = 1
    cam_info.isOutputJPEG = 1

    cam_info.imageWidth = cameraCfg.camWidth
    cam_info.imageHeight = cameraCfg.camHeight
    cam_info.startX = 0
    cam_info.startY = 0
    cam_info.endX = cameraCfg.camWidth
    cam_info.endY = cameraCfg.camHeight
    cam_info.inputDimWidth = 0
    cam_info.inputDimHeight = 0
    ncc.SetMeanValue(cam_info, 0.0, 0.0, 0.0)

    ret = ncc.sdk_init(
        None, None,
        "./blob/2020.3/face-detection-retail-0004/face-detection-retail-0004.blob",
        cam_info, struct.calcsize("13I4f"))  #struct CameraInfo
    metasize = ncc.get_meta_size()
    print("xlink_init ret=%d  %d" % (ret, metasize))
    if (ret < 0):
        return

    oft_x = cam_info.startX
    oft_y = cam_info.startY
    dis_w = cam_info.endX - cam_info.startX
    dis_h = cam_info.endY - cam_info.startY

    offset = struct.calcsize(media_head)
    size = cameraCfg.camWidth * cameraCfg.camHeight * 2
    yuvbuf = bytearray(size + offset)
    metabuf = bytearray(metasize + offset)

    ncc.camera_video_out(ncc.YUV420p, ncc.VIDEO_OUT_CONTINUOUS)
    while (True):
        size = ncc.GetYuvData(yuvbuf)
        if (size <= 0):
            time.sleep(0.1)  #0.1 second
            continue

        numarry = np.array(
            yuvbuf[offset:size])  #skip head frameSpecOut 64 bytes
        #print("buf   len=%d/%d" % (numarry.size,size))
        yuv = numarry.reshape(
            (int(cameraCfg.camHeight * 3 / 2), cameraCfg.camWidth))
        bgr = cv2.cvtColor(yuv, cv2.COLOR_YUV2BGR_I420, 3)

        size = ncc.GetMetaData(metabuf)
        if (size > 0):
            #spec=metabuf[0:offset]
            #print(spec)
            #type,seq,size=get_header_info(metabuf[0:offset])
            #print("meta type=%d seq=%d  size=%d" % (type,seq,size))

            barray = metabuf[offset + ncc.OUTPUT_INDEX_SIZE:size]
            #print("meta len=%d/%d" % (len(barray),size))
            #print_hex(barray[0:14])
            count = len(barray) // 2
            sarry = struct.unpack('H' * count, barray)
            #print(sarry[0:7])

            for i in range(100):
                image_id = ncc.f16Tof32(sarry[i * 7 + 0])
                #print("face id %d" % image_id)
                if (image_id < 0):
                    break

                score = ncc.f16Tof32(sarry[i * 7 + 2])
                x0 = ncc.f16Tof32(sarry[i * 7 + 3])
                y0 = ncc.f16Tof32(sarry[i * 7 + 4])
                x1 = ncc.f16Tof32(sarry[i * 7 + 5])
                y1 = ncc.f16Tof32(sarry[i * 7 + 6])
                #print("score:%.2f<->min:%.2f  rec:(%.3f,%.3f)<->(%.3f,%.3f) " %(score,min_score,x0,y0,x1,y1))
                if ((not coordinate_is_valid(x0, y0, x1, y1))
                        or (score < min_score)):
                    continue

                x = int(x0 * dis_w + oft_x)
                y = int(y0 * dis_h + oft_y)
                w = int((x1 - x0) * dis_w)
                h = int((y1 - y0) * dis_h)
                cv2.rectangle(bgr, (x, y), (x + w, y + h), (0, 255, 0), 2)

                result = ("score:%d") % (int(100 * score))
                #print("%d,%d[%dx%d] score:%s" %(x,y,w,h,result))
                cv2.putText(bgr, result, (x, y + 32), cv2.FONT_HERSHEY_COMPLEX,
                            1, (255, 0, 0), 1)

        img_scaled = cv2.resize(bgr,
                                None,
                                fx=0.7,
                                fy=0.7,
                                interpolation=cv2.INTER_CUBIC)
        cv2.namedWindow('openncc', cv2.WINDOW_AUTOSIZE)
        cv2.imshow('openncc', img_scaled)
        if (cv2.waitKey(20) == 27): break
    ncc.sdk_uninit()
    cv2.destroyAllWindows()
Esempio n. 2
0
def main():
    res = ncc.load_fw("./moviUsbBoot", "fw/flicRefApp.mvcmd")
    if res < 0:
        printf('load firmware error!')
        sys.exit(1)

    print("get usb %d sdk versin %s" % (ncc.get_usb_version(), ncc.get_sdk_version()))

    print("get fw version: %s and ncc id %s" % (ncc.camera_get_fw_version(),
                                                ncc.camera_get_ncc_id()))

    sensors = ncc.CameraSensor()
    sensor1 = ncc.SensorModesConfig()
    if sensors.GetFirstSensor(sensor1) == 0:
        print("camera: %s, %dX%d@%dfps, AFmode:%d, maxEXP:%dus,gain[%d, %d]\n" % (
            sensor1.moduleName, sensor1.camWidth, sensor1.camHeight, sensor1.camFps,
            sensor1.AFmode, sensor1.maxEXP, sensor1.minGain, sensor1.maxGain))

    sensor2 = ncc.SensorModesConfig()
    while sensors.GetNextSensor(sensor2) == 0:
        print("camera: %s, %dX%d@%dfps, AFmode:%d, maxEXP:%dus,gain[%d, %d]\n" % (
            sensor2.moduleName, sensor2.camWidth, sensor2.camHeight, sensor2.camFps,
            sensor2.AFmode, sensor2.maxEXP, sensor2.minGain, sensor2.maxGain))

    ncc.camera_select_sensor(0)  # 0 1080p 1 4k
    cameraCfg = sensor1

    net1_info = ncc.Network1Par()
    net1_info.inputFormat = ncc.IMG_FORMAT_BGR_PLANAR
    net1_info.meanValue = [0.0, 0.0, 0.0]
    net1_info.stdValue = 1

    net1_info.isOutputYUV = 1
    net1_info.isOutputH26X = 1
    net1_info.isOutputJPEG = 1

    net1_info.imageWidth = cameraCfg.camWidth
    net1_info.imageHeight = cameraCfg.camHeight
    net1_info.startX = 0
    net1_info.startY = 0
    net1_info.endX = cameraCfg.camWidth
    net1_info.endY = cameraCfg.camHeight
    net1_info.inputDimWidth = 300
    net1_info.inputDimHeight = 300

    # extInputs = np.zeros(ncc.MAX_EXTINPUT_SIZE,dtype = np.uint8)
    # print('input size {}'.format(extInputs.size))
    net1_info.extInputs = [0] * ncc.MAX_EXTINPUT_SIZE  # tobytes()
    net1_info.modelCascade = 1
    net1_info.inferenceACC = 1

    net2_info = ncc.Network2Par()
    net2_info.startXAdj = -5
    net2_info.startYAdj = -5
    net2_info.endXAdj = 5
    net2_info.endYAdj = 5

    labelMask = [0]*ncc.MAX_LABEL_SIZE
    labelMask[2]=1
    net2_info.labelMask = labelMask
    net2_info.minConf = 0.7

    net2_info.inputDimWidth = 94
    net2_info.inputDimHeight = 24
    net2_info.inputFormat = ncc.IMG_FORMAT_BGR_PLANAR

    net2_info.meanValue = [0.0, 0.0, 0.0]
    net2_info.stdValue = 1

    count=ncc.MAX_EXTINPUT_SIZE//2
    extInputs = array('h',[0]*count)
    extInputs[0] = int(ncc.f32Tof16(0))
    for i in range(1, 88):
        extInputs[i] = int(ncc.f32Tof16(1.0))
    net2_info.extInputs = extInputs.tobytes()
    net2_info.modelCascade = 0
    print("input  0={} 1={} type={}".format(int(ncc.f32Tof16(1.0)),extInputs[1],type(extInputs[1])));
    blob1 = "./blob/2020.3/vehicle-license-plate-detection-barrier-0106/vehicle-license-plate-detection-barrier-0106.blob";
    blob2 = "./blob/2020.3/license-plate-recognition-barrier-0001/license-plate-recognition-barrier-0001.blob";  # if par_Len=0 , cal param_size auto
    ret = ncc.sdk_net2_init(None, None, \
                            blob1, net1_info, 0, \
                            blob2, net2_info, 0)
    metasize = 2 * 1024 * 1024
    print("xlink_init ret=%d  %d" % (ret, metasize))
    if (ret < 0):
        return

    oft_x = net1_info.startX
    oft_y = net1_info.startY
    dis_w = net1_info.endX - net1_info.startX
    dis_h = net1_info.endY - net1_info.startY

    offset = struct.calcsize(media_head)  # 64
    size = cameraCfg.camWidth * cameraCfg.camHeight * 2
    yuvbuf = bytearray(size + offset)
    metabuf = bytearray(metasize)

    ncc.camera_video_out(ncc.YUV420p, ncc.VIDEO_OUT_CONTINUOUS)
    bmeta=False;
    while (True):
        size = ncc.GetYuvData(yuvbuf)
        if (size <= 0):
            time.sleep(0.1)  # 0.1 second
            continue

        numarry = np.array(yuvbuf[offset:size])  # skip head frameSpecOut 64 bytes
        # print("buf   len=%d/%d" % (numarry.size,size))
        yuv = numarry.reshape((int(cameraCfg.camHeight * 3 / 2), cameraCfg.camWidth))
        bgr = cv2.cvtColor(yuv, cv2.COLOR_YUV2BGR_I420, 3)

        size, outsize0,outsize1,item_num = ncc.GetMetaDataExt(metabuf)
        if (size > 0)and (item_num>0):
            bmeta=True
        #if(bmeta):
            print("ret=%d size0=%d size1=%d,num=%d" %(size,outsize0,outsize1,item_num ))
            # spec=metabuf[0:offset]
            #type1,seq,m_size=get_header_info(metabuf[0:offset])
            #print("meta type=%d seq=%d  size=%d" % (type1,seq,m_size))

            #f = open("sample.txt", "wb")
            #f.write(metabuf)
            #f.close()

            from_i=offset + ncc.OUTPUT_INDEX_SIZE
            count=outsize0//2
            detMetadata = struct.unpack('H'*count,metabuf[from_i:from_i+outsize0])

            from_i+=outsize0   #skip output 0
            count=outsize1//2
            #print("out1 count %d from %d to %d" % (count,from_i,size))
            secondMeta= struct.unpack('H'*count*item_num,metabuf[from_i:size])

            for i in range(item_num):
                image_id = int(ncc.f16Tof32(detMetadata[i * 7 + 0]))
                if (image_id < 0):
                    break

                label = int(ncc.f16Tof32(detMetadata[i * 7 + 1]))
                score = ncc.f16Tof32(detMetadata[i * 7 + 2])
                x0 = ncc.f16Tof32(detMetadata[i * 7 + 3])
                y0 = ncc.f16Tof32(detMetadata[i * 7 + 4])
                x1 = ncc.f16Tof32(detMetadata[i * 7 + 5])
                y1 = ncc.f16Tof32(detMetadata[i * 7 + 6])
               # print("item sise=%d score:%.2f<->min:%.2f  rec:(%.3f,%.3f)<->(%.3f,%.3f) " %(item_num,score,min_score,x0,y0,x1,y1))
                if ((not coordinate_is_valid(x0, y0, x1, y1)) or (score < min_score) or (labelMask[label]==0)):
                    continue

                x = int(x0 * dis_w + oft_x)
                y = int(y0 * dis_h + oft_y)
                w = int((x1 - x0) * dis_w)
                h = int((y1 - y0) * dis_h)

                cv2.rectangle(bgr, (x, y), (x + w, y + h), (255, 128, 128), 2)
                regMetadata=secondMeta[i*count:i*count+count]
                
                regRet = array('i')
                for j in range(88):
                    regRet.append(int(ncc.f16Tof32(regMetadata[j])))

                items = [
                    "0", "1", "2", "3", "4", "5", "6", "7", "8", "9", \
                    "<Anhui>", "<Beijing>", "<Chongqing>", "<Fujian>", \
                    "<Gansu>", "<Guangdong>", "<Guangxi>", "<Guizhou>", \
                    "<Hainan>", "<Hebei>", "<Heilongjiang>", "<Henan>", \
                    "<HongKong>", "<Hubei>", "<Hunan>", "<InnerMongolia>", \
                    "<Jiangsu>", "<Jiangxi>", "<Jilin>", "<Liaoning>", \
                    "<Macau>", "<Ningxia>", "<Qinghai>", "<Shaanxi>", \
                    "<Shandong>", "<Shanghai>", "<Shanxi>", "<Sichuan>", \
                    "<Tianjin>", "<Tibet>", "<Xinjiang>", "<Yunnan>", \
                    "<Zhejiang>", "<police>", \
                    "A", "B", "C", "D", "E", "F", "G", "H", "I", "J", \
                    "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", \
                    "U", "V", "W", "X", "Y", "Z" \
                    ];

                result = ''
                for j in range(0, len(regRet)):
                    if (regRet[j] == -1):
                        break
                    #result = result.join(items[regRet[j]])
                    result = result+items[regRet[j]]
                cv2.putText(bgr, result, (x, y - 20), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 255), 1)

        img_scaled = cv2.resize(bgr, None, fx=0.7, fy=0.7, interpolation=cv2.INTER_CUBIC)
        cv2.namedWindow('openncc', cv2.WINDOW_AUTOSIZE)
        cv2.imshow('openncc', img_scaled)
        if (cv2.waitKey(20) == 27):
            break
    ncc.sdk_uninit()
    cv2.destroyAllWindows()
Esempio n. 3
0
def main():
    res = ncc.load_fw("./moviUsbBoot", "fw/flicRefApp.mvcmd")
    if res < 0:
        printf('load firmware error!')
        sys.exit(1)

    print("get usb %d sdk versin %s" %
          (ncc.get_usb_version(), ncc.get_sdk_version()))

    sensors = ncc.CameraSensor()
    sensor1 = ncc.SensorModesConfig()
    if sensors.GetFirstSensor(sensor1) == 0:
        print(
            "camera: %s, %dX%d@%dfps, AFmode:%d, maxEXP:%dus,gain[%d, %d]\n" %
            (sensor1.moduleName, sensor1.camWidth, sensor1.camHeight,
             sensor1.camFps, sensor1.AFmode, sensor1.maxEXP, sensor1.minGain,
             sensor1.maxGain))

    sensor2 = ncc.SensorModesConfig()
    while sensors.GetNextSensor(sensor2) == 0:
        print(
            "camera: %s, %dX%d@%dfps, AFmode:%d, maxEXP:%dus,gain[%d, %d]\n" %
            (sensor2.moduleName, sensor2.camWidth, sensor2.camHeight,
             sensor2.camFps, sensor2.AFmode, sensor2.maxEXP, sensor2.minGain,
             sensor2.maxGain))

    ncc.camera_select_sensor(0)  #0 1080p 1 4k
    cameraCfg = sensor1

    cam_info = ncc.CameraInfo()
    cam_info.inputFormat = ncc.IMG_FORMAT_BGR_PLANAR
    #cam_info.meanValue = [float(0.0)]*3
    cam_info.stdValue = 1

    cam_info.isOutputYUV = 1
    cam_info.isOutputH26X = 1
    cam_info.isOutputJPEG = 1

    cam_info.imageWidth = cameraCfg.camWidth
    cam_info.imageHeight = cameraCfg.camHeight
    cam_info.startX = 0
    cam_info.startY = 0
    cam_info.endX = cameraCfg.camWidth
    cam_info.endY = cameraCfg.camHeight
    cam_info.inputDimWidth = 0
    cam_info.inputDimHeight = 0
    ncc.SetMeanValue(cam_info, 0.0, 0.0, 0.0)

    ret = ncc.sdk_init(
        None, None,
        "./blob/2020.3/human-pose-estimation-0001/human-pose-estimation-0001.blob",
        cam_info, 0)  #struct CameraInfo,0 will auto cal
    #metasize=ncc.get_meta_size()#only support one module now
    #print("xlink_init ret=%d  %d" % (ret,metasize))
    #if (ret<0):
    #	return

    oft_x = cam_info.startX
    oft_y = cam_info.startY
    dis_w = cam_info.endX - cam_info.startX
    dis_h = cam_info.endY - cam_info.startY

    offset = struct.calcsize(media_head)
    size = cameraCfg.camWidth * cameraCfg.camHeight * 2
    yuvbuf = bytearray(size + offset)
    metabuf = bytearray(300 * 1024)

    ncc.camera_video_out(ncc.YUV420p, ncc.VIDEO_OUT_CONTINUOUS)
    while (True):
        size = ncc.GetYuvData(yuvbuf)
        if (size <= 0):
            time.sleep(0.1)  #0.1 second
            continue

        numarry = np.array(
            yuvbuf[offset:size])  #skip head frameSpecOut 64 bytes
        #print("buf   len=%d/%d" % (numarry.size,size))
        yuv = numarry.reshape(
            (int(cameraCfg.camHeight * 3 / 2), cameraCfg.camWidth))

        size = ncc.GetMetaData(metabuf)
        if (size > 0):
            #spec=metabuf[0:offset]
            #print(spec)
            #type,seq,size=get_header_info(metabuf[0:offset])
            #print("meta type=%d seq=%d  size=%d" % (type,seq,size))

            barray = metabuf[offset + ncc.OUTPUT_INDEX_SIZE:size]
            print("meta len=%d/%d" % (len(barray), size))
            #print_hex(barray[0:14])
            count = len(barray) // 2
            sarry = struct.unpack('H' * count, barray)
            #print(sarry[0:7])

            farry = array('f')
            for i in range(count):
                farry.append(ncc.f16Tof32(
                    sarry[i]))  #get all float data from output

            dim_paf = [1, 38, 32, 57]
            dim_heat = [1, 19, 32, 57]
            paf_len = dim_paf[0] * dim_paf[1] * dim_paf[2] * dim_paf[3]

            print("farry len=%d paf_len =%d" % (len(farry), paf_len))

            pafs_arry = np.array(farry[0:paf_len])
            heat_arry = np.array(farry[paf_len:])
            print("pafs array len=%d heat array len=%d" %
                  (pafs_arry.size, heat_arry.size))
            pafs_blob = pafs_arry.reshape(dim_paf)
            print("pafs_blob:")
            print(pafs_blob)
            heat_blob = heat_arry.reshape(dim_heat)
            print("heat_blob:")
            print(heat_blob)
    ncc.sdk_uninit()
Esempio n. 4
0
def main():
    global faceLib
    res = ncc.load_fw("./moviUsbBoot", "fw/flicRefApp.mvcmd")
    if res < 0:
        printf('load firmware error!')
        sys.exit(1)

    print("get usb %d sdk versin %s" %
          (ncc.get_usb_version(), ncc.get_sdk_version()))

    print("get fw version: %s and ncc id %s" %
          (ncc.camera_get_fw_version(), ncc.camera_get_ncc_id()))

    sensors = ncc.CameraSensor()
    sensor1 = ncc.SensorModesConfig()
    if sensors.GetFirstSensor(sensor1) == 0:
        print(
            "camera: %s, %dX%d@%dfps, AFmode:%d, maxEXP:%dus,gain[%d, %d]\n" %
            (sensor1.moduleName, sensor1.camWidth, sensor1.camHeight,
             sensor1.camFps, sensor1.AFmode, sensor1.maxEXP, sensor1.minGain,
             sensor1.maxGain))

    sensor2 = ncc.SensorModesConfig()
    while sensors.GetNextSensor(sensor2) == 0:
        print(
            "camera: %s, %dX%d@%dfps, AFmode:%d, maxEXP:%dus,gain[%d, %d]\n" %
            (sensor2.moduleName, sensor2.camWidth, sensor2.camHeight,
             sensor2.camFps, sensor2.AFmode, sensor2.maxEXP, sensor2.minGain,
             sensor2.maxGain))

    ncc.camera_select_sensor(0)  # 0 1080p 1 4k
    cameraCfg = sensor1

    net1_info = ncc.Network1Par()
    net1_info.inputFormat = ncc.IMG_FORMAT_BGR_PLANAR
    net1_info.meanValue = [0.0, 0.0, 0.0]
    net1_info.stdValue = 1

    net1_info.isOutputYUV = 1
    net1_info.isOutputH26X = 0
    net1_info.isOutputJPEG = 0

    net1_info.imageWidth = cameraCfg.camWidth
    net1_info.imageHeight = cameraCfg.camHeight
    net1_info.startX = 0
    net1_info.startY = 0
    net1_info.endX = cameraCfg.camWidth
    net1_info.endY = cameraCfg.camHeight
    net1_info.inputDimWidth = 300
    net1_info.inputDimHeight = 300

    # extInputs = np.zeros(ncc.MAX_EXTINPUT_SIZE,dtype = np.uint8)
    # print('input size {}'.format(extInputs.size))
    net1_info.extInputs = [0] * ncc.MAX_EXTINPUT_SIZE  # tobytes()
    net1_info.modelCascade = 1
    net1_info.inferenceACC = 0

    net2_info = ncc.Network2Par()
    net2_info.startXAdj = -5
    net2_info.startYAdj = -5
    net2_info.endXAdj = 5
    net2_info.endYAdj = 5

    labelMask = [0] * ncc.MAX_LABEL_SIZE
    labelMask[1] = 1
    net2_info.labelMask = labelMask
    net2_info.minConf = 0.7

    net2_info.inputDimWidth = 128
    net2_info.inputDimHeight = 128
    net2_info.inputFormat = ncc.IMG_FORMAT_BGR_PLANAR

    net2_info.meanValue = [0.0, 0.0, 0.0]
    net2_info.stdValue = 1

    count = ncc.MAX_EXTINPUT_SIZE // 2
    extInputs = array('h', [0] * count)
    net2_info.extInputs = extInputs.tobytes()
    net2_info.modelCascade = 0
    #print("input  0={} 1={} type={}".format(int(ncc.f32Tof16(1.0)),extInputs[1],type(extInputs[1])));
    blob1 = "./blob/2020.3/face-detection-retail-0004/face-detection-retail-0004.blob"
    blob2 = "./blob/2020.3/face-reidentification-retail-0095/face-reidentification-retail-0095.blob"
    ret = ncc.sdk_net2_init(None, None, \
                            blob1, net1_info, 0, \
                            blob2, net2_info, 0)
    metasize = 3 * 1024 * 1024
    print("xlink_init ret=%d  %d" % (ret, metasize))
    if (ret < 0):
        return

    oft_x = net1_info.startX
    oft_y = net1_info.startY
    dis_w = net1_info.endX - net1_info.startX
    dis_h = net1_info.endY - net1_info.startY

    offset = struct.calcsize(media_head)  # 64
    size = cameraCfg.camWidth * cameraCfg.camHeight * 2
    yuvbuf = bytearray(size + offset)
    metabuf = bytearray(metasize)

    ncc.camera_video_out(ncc.YUV420p, ncc.VIDEO_OUT_CONTINUOUS)
    bmeta = False
    bsave_face = False
    if os.access("face.txt", os.F_OK):
        faceLib = np.loadtxt('face.txt', dtype=float).tolist()
        print(faceLib)

    while (True):
        size = ncc.GetYuvData(yuvbuf)
        if (size <= 0):
            time.sleep(0.1)  # 0.1 second
            continue

        numarry = np.array(
            yuvbuf[offset:size])  # skip head frameSpecOut 64 bytes
        # print("buf   len=%d/%d" % (numarry.size,size))
        yuv = numarry.reshape(
            (int(cameraCfg.camHeight * 3 / 2), cameraCfg.camWidth))
        bgr = cv2.cvtColor(yuv, cv2.COLOR_YUV2BGR_I420, 3)

        size, outsize0, outsize1, item_num = ncc.GetMetaDataExt(metabuf)
        if (size > 0) and (item_num > 0):
            bmeta = True
            print("ret=%d size0=%d size1=%d,num=%d" %
                  (size, outsize0, outsize1, item_num))
            # spec=metabuf[0:offset]
            #type1,seq,m_size=get_header_info(metabuf[0:offset])
            #print("meta type=%d seq=%d  size=%d" % (type1,seq,m_size))

            #f = open("sample.txt", "wb")
            #f.write(metabuf)
            #f.close()

            from_i = offset + ncc.OUTPUT_INDEX_SIZE
            count = outsize0 // 2
            detMetadata = struct.unpack('H' * count,
                                        metabuf[from_i:from_i + outsize0])

            from_i += outsize0  #skip output 0
            count = outsize1 // 2
            print("out2 count %d from %d to %d" % (count, from_i, size))
            secondMeta = struct.unpack('H' * count * item_num,
                                       metabuf[from_i:size])

            for i in range(item_num):
                image_id = int(ncc.f16Tof32(detMetadata[i * 7 + 0]))
                if (image_id < 0):
                    break

                label = int(ncc.f16Tof32(detMetadata[i * 7 + 1]))
                score = ncc.f16Tof32(detMetadata[i * 7 + 2])
                x0 = ncc.f16Tof32(detMetadata[i * 7 + 3])
                y0 = ncc.f16Tof32(detMetadata[i * 7 + 4])
                x1 = ncc.f16Tof32(detMetadata[i * 7 + 5])
                y1 = ncc.f16Tof32(detMetadata[i * 7 + 6])
                # print("item sise=%d score:%.2f<->min:%.2f  rec:(%.3f,%.3f)<->(%.3f,%.3f) " %(item_num,score,min_score,x0,y0,x1,y1))
                if ((not coordinate_is_valid(x0, y0, x1, y1))
                        or (score < min_score) or (labelMask[label] == 0)):
                    continue

                x = int(x0 * dis_w + oft_x)
                y = int(y0 * dis_h + oft_y)
                w = int((x1 - x0) * dis_w)
                h = int((y1 - y0) * dis_h)

                cv2.rectangle(bgr, (x, y), (x + w, y + h), (255, 128, 128), 2)
                regMetadata = secondMeta[i * count:i * count + count]

                regRet = array('f')

                for j in range(256):
                    regRet.append(ncc.f16Tof32(regMetadata[j]))

                if bsave_face:
                    print("!!!!save face!!!!")
                    cv2.imwrite('face.png', bgr)
                    nf = np.array(regRet)
                    np.savetxt('face.txt', np.array(nf), fmt='%.2f')
                    bsave_face = False

                similarVal = calc_similar(regRet, faceLib)
                result = ''
                print("get similar {:.2f}".format(similarVal))
                if similarVal > SIMI_VAL:
                    result = 'RET{:2.2f}, OK'.format(similarVal)
                else:
                    result = 'RET{:2.2f}, NG'.format(similarVal)
                cv2.putText(bgr, result, (x, y - 20), cv2.FONT_HERSHEY_COMPLEX,
                            1, (0, 0, 255), 1)

        img_scaled = cv2.resize(bgr,
                                None,
                                fx=0.7,
                                fy=0.7,
                                interpolation=cv2.INTER_CUBIC)
        cv2.namedWindow('openncc', cv2.WINDOW_AUTOSIZE)
        cv2.imshow('openncc', img_scaled)
        c = cv2.waitKey(10)
        if c == 115:  #s
            bsave_face = True
        elif (c == 27):
            break
    ncc.sdk_uninit()
    cv2.destroyAllWindows()