未分類」カテゴリーアーカイブ

jetson nanoでcv2(cuda有効化)

ソースからインストール

python3でcv2をimportすると crashしてコアーダンプ。

問題の解決:export OPENBLAS_CORETYPE=ARMV8

こちらを参照して解決。Jetson NanoのPython3環境でIllegal instruction (cpre dumped)

処理速度の比較測定:約3倍

$ sudo nvpmodel -m 0
$ sudo jetson_clocks
$ python3 opencv_cuda.py
CPU = 2.7655137538909913[msec]
GPU = 1.0501614570617677[msec]
1
$ python3 opencv_cuda.py
CPU = 2.7816075325012206[msec]
GPU = 0.9869620561599731[msec]
1

opencv_cuda.py

import sys
import time
import cv2

### VALUES
NUM_REPEAT = 10000

### Read source image
img_src = cv2.imread("resource/lena.jpg")
cv2.imshow('img_src', img_src)


### Run with CPU
time_start = time.time()
for i in range (NUM_REPEAT):
    img_dst = cv2.resize(img_src, (300, 300))
time_end = time.time()
print ("CPU = {0}".format((time_end - time_start) * 1000 / NUM_REPEAT) + "[msec]")
cv2.imshow('CPU', img_dst)


### Run with GPU
img_gpu_src = cv2.cuda_GpuMat() # Allocate device memory only once, as memory allocation seems to take time...
img_gpu_dst = cv2.cuda_GpuMat()
time_start = time.time()
for i in range (NUM_REPEAT):
    img_gpu_src.upload(img_src)
    img_gpu_dst = cv2.cuda.resize(img_gpu_src, (300, 300))
    img_dst = img_gpu_dst.download()
time_end = time.time()
print ("GPU = {0}".format((time_end - time_start) * 1000 / NUM_REPEAT) + "[msec]")
cv2.imshow('GPU', img_dst)


key = cv2.waitKey(0)
cv2.destroyAllWindows()

print(cv2.cuda.getCudaEnabledDeviceCount())

cudaで利用できる機能を表示してみる

import cv2
cv2.__version__
dir(cv2.cuda)
['ALPHA_ATOP',
 'ALPHA_ATOP_PREMUL',
 'ALPHA_IN',
 'ALPHA_IN_PREMUL',
 'ALPHA_OUT',
 'ALPHA_OUT_PREMUL',
 'ALPHA_OVER',
 'ALPHA_OVER_PREMUL',
 'ALPHA_PLUS',
 'ALPHA_PLUS_PREMUL',
 'ALPHA_PREMUL',
 'ALPHA_XOR',
 'ALPHA_XOR_PREMUL',
 'BroxOpticalFlow_create',
 'COLOR_BAYER_BG2BGR_MHT',
 'COLOR_BAYER_BG2GRAY_MHT',
 'COLOR_BAYER_BG2RGB_MHT',
 'COLOR_BAYER_GB2BGR_MHT',
 'COLOR_BAYER_GB2GRAY_MHT',
 'COLOR_BAYER_GB2RGB_MHT',
 'COLOR_BAYER_GR2BGR_MHT',
 'COLOR_BAYER_GR2GRAY_MHT',
 'COLOR_BAYER_GR2RGB_MHT',
 'COLOR_BAYER_RG2BGR_MHT',
 'COLOR_BAYER_RG2GRAY_MHT',
 'COLOR_BAYER_RG2RGB_MHT',
 'COLOR_BayerBG2BGR_MHT',
 'COLOR_BayerBG2GRAY_MHT',
 'COLOR_BayerBG2RGB_MHT',
 'COLOR_BayerGB2BGR_MHT',
 'COLOR_BayerGB2GRAY_MHT',
 'COLOR_BayerGB2RGB_MHT',
 'COLOR_BayerGR2BGR_MHT',
 'COLOR_BayerGR2GRAY_MHT',
 'COLOR_BayerGR2RGB_MHT',
 'COLOR_BayerRG2BGR_MHT',
 'COLOR_BayerRG2GRAY_MHT',
 'COLOR_BayerRG2RGB_MHT',
 'CascadeClassifier_create',
 'DEVICE_INFO_COMPUTE_MODE_DEFAULT',
 'DEVICE_INFO_COMPUTE_MODE_EXCLUSIVE',
 'DEVICE_INFO_COMPUTE_MODE_EXCLUSIVE_PROCESS',
 'DEVICE_INFO_COMPUTE_MODE_PROHIBITED',
 'DYNAMIC_PARALLELISM',
 'DensePyrLKOpticalFlow_create',
 'DescriptorMatcher_createBFMatcher',
 'DeviceInfo_ComputeModeDefault',
 'DeviceInfo_ComputeModeExclusive',
 'DeviceInfo_ComputeModeExclusiveProcess',
 'DeviceInfo_ComputeModeProhibited',
 'EVENT_BLOCKING_SYNC',
 'EVENT_DEFAULT',
 'EVENT_DISABLE_TIMING',
 'EVENT_INTERPROCESS',
 'Event_BLOCKING_SYNC',
 'Event_DEFAULT',
 'Event_DISABLE_TIMING',
 'Event_INTERPROCESS',
 'Event_elapsedTime',
 'FEATURE_SET_COMPUTE_10',
 'FEATURE_SET_COMPUTE_11',
 'FEATURE_SET_COMPUTE_12',
 'FEATURE_SET_COMPUTE_13',
 'FEATURE_SET_COMPUTE_20',
 'FEATURE_SET_COMPUTE_21',
 'FEATURE_SET_COMPUTE_30',
 'FEATURE_SET_COMPUTE_32',
 'FEATURE_SET_COMPUTE_35',
 'FEATURE_SET_COMPUTE_50',
 'FarnebackOpticalFlow_create',
 'FastFeatureDetector_create',
 'GLOBAL_ATOMICS',
 'GpuMat_defaultAllocator',
 'GpuMat_setDefaultAllocator',
 'HOG_create',
 'HOST_MEM_PAGE_LOCKED',
 'HOST_MEM_SHARED',
 'HOST_MEM_WRITE_COMBINED',
 'HostMem_PAGE_LOCKED',
 'HostMem_SHARED',
 'HostMem_WRITE_COMBINED',
 'NATIVE_DOUBLE',
 'NVIDIA_OPTICAL_FLOW_1_0_NV_OF_PERF_LEVEL_FAST',
 'NVIDIA_OPTICAL_FLOW_1_0_NV_OF_PERF_LEVEL_MAX',
 'NVIDIA_OPTICAL_FLOW_1_0_NV_OF_PERF_LEVEL_MEDIUM',
 'NVIDIA_OPTICAL_FLOW_1_0_NV_OF_PERF_LEVEL_SLOW',
 'NVIDIA_OPTICAL_FLOW_1_0_NV_OF_PERF_LEVEL_UNDEFINED',
 'NvidiaOpticalFlow_1_0_NV_OF_PERF_LEVEL_FAST',
 'NvidiaOpticalFlow_1_0_NV_OF_PERF_LEVEL_MAX',
 'NvidiaOpticalFlow_1_0_NV_OF_PERF_LEVEL_MEDIUM',
 'NvidiaOpticalFlow_1_0_NV_OF_PERF_LEVEL_SLOW',
 'NvidiaOpticalFlow_1_0_NV_OF_PERF_LEVEL_UNDEFINED',
 'NvidiaOpticalFlow_1_0_create',
 'ORB_create',
 'OpticalFlowDual_TVL1_create',
 'SHARED_ATOMICS',
 'SURF_CUDA_ANGLE_ROW',
 'SURF_CUDA_HESSIAN_ROW',
 'SURF_CUDA_LAPLACIAN_ROW',
 'SURF_CUDA_OCTAVE_ROW',
 'SURF_CUDA_ROWS_COUNT',
 'SURF_CUDA_SIZE_ROW',
 'SURF_CUDA_X_ROW',
 'SURF_CUDA_Y_ROW',
 'SparsePyrLKOpticalFlow_create',
 'StereoBeliefPropagation_estimateRecommendedParams',
 'StereoConstantSpaceBP_estimateRecommendedParams',
 'Stream_Null',
 'TargetArchs_has',
 'TargetArchs_hasBin',
 'TargetArchs_hasEqualOrGreater',
 'TargetArchs_hasEqualOrGreaterBin',
 'TargetArchs_hasEqualOrGreaterPtx',
 'TargetArchs_hasEqualOrLessPtx',
 'TargetArchs_hasPtx',
 'WARP_SHUFFLE_FUNCTIONS',
 '__doc__',
 '__loader__',
 '__name__',
 '__package__',
 '__spec__',
 'abs',
 'absSum',
 'absdiff',
 'add',
 'addWeighted',
 'alphaComp',
 'bilateralFilter',
 'bitwise_and',
 'bitwise_not',
 'bitwise_or',
 'bitwise_xor',
 'blendLinear',
 'buildWarpAffineMaps',
 'buildWarpPerspectiveMaps',
 'calcAbsSum',
 'calcHist',
 'calcNorm',
 'calcNormDiff',
 'calcSqrSum',
 'calcSum',
 'cartToPolar',
 'compare',
 'copyMakeBorder',
 'countNonZero',
 'createBackgroundSubtractorMOG',
 'createBackgroundSubtractorMOG2',
 'createBoxFilter',
 'createBoxMaxFilter',
 'createBoxMinFilter',
 'createCLAHE',
 'createCannyEdgeDetector',
 'createColumnSumFilter',
 'createContinuous',
 'createConvolution',
 'createDFT',
 'createDerivFilter',
 'createDisparityBilateralFilter',
 'createGaussianFilter',
 'createGeneralizedHoughBallard',
 'createGeneralizedHoughGuil',
 'createGoodFeaturesToTrackDetector',
 'createHarrisCorner',
 'createHoughCirclesDetector',
 'createHoughLinesDetector',
 'createHoughSegmentDetector',
 'createLaplacianFilter',
 'createLinearFilter',
 'createLookUpTable',
 'createMedianFilter',
 'createMinEigenValCorner',
 'createMorphologyFilter',
 'createRowSumFilter',
 'createScharrFilter',
 'createSeparableLinearFilter',
 'createSobelFilter',
 'createStereoBM',
 'createStereoBeliefPropagation',
 'createStereoConstantSpaceBP',
 'createTemplateMatching',
 'cvtColor',
 'demosaicing',
 'dft',
 'divide',
 'drawColorDisp',
 'ensureSizeIsEnough',
 'equalizeHist',
 'evenLevels',
 'exp',
 'findMinMax',
 'findMinMaxLoc',
 'flip',
 'gammaCorrection',
 'gemm',
 'getCudaEnabledDeviceCount',
 'getDevice',
 'histEven',
 'histRange',
 'integral',
 'log',
 'magnitude',
 'magnitudeSqr',
 'max',
 'meanShiftFiltering',
 'meanShiftProc',
 'meanShiftSegmentation',
 'meanStdDev',
 'merge',
 'min',
 'minMax',
 'minMaxLoc',
 'mulAndScaleSpectrums',
 'mulSpectrums',
 'multiply',
 'norm',
 'normalize',
 'phase',
 'polarToCart',
 'pow',
 'printCudaDeviceInfo',
 'printShortCudaDeviceInfo',
 'pyrDown',
 'pyrUp',
 'rectStdDev',
 'reduce',
 'registerPageLocked',
 'remap',
 'reprojectImageTo3D',
 'resetDevice',
 'resize',
 'rotate',
 'setBufferPoolConfig',
 'setBufferPoolUsage',
 'setDevice',
 'split',
 'sqr',
 'sqrIntegral',
 'sqrSum',
 'sqrt',
 'subtract',
 'sum',
 'threshold',
 'transpose',
 'unregisterPageLocked',
 'warpAffine',
 'warpPerspective']

センサーのデータをinfluxdbへ送る

python版

参考URL(ラズパイ+BME280で温度・湿度・気圧を計測(BMP280は湿度なし)

次のpythonコードをcronで定期的(例えば3分毎)に実行し、influxdbのホストへ送信する。

#coding: utf-8
#encoding: utf-8

from influxdb import InfluxDBClient
client = InfluxDBClient(host='xxx.xxx.xxx.xxx', port=8086, username='****', password='****', database='iot01')
measurement = 'air5'
tags = {'place': 'leaf-bme280','host': 'RockPi4'}

from smbus2 import SMBus
import time

bus_number  = 7 # RockPi4の場合。 Raspiでは 1
i2c_address = 0x76

bus = SMBus(bus_number)

digT = []
digP = []
digH = []

t_fine = 0.0

def writeReg(reg_address, data):
        bus.write_byte_data(i2c_address,reg_address,data)

def get_calib_param():
        calib = []

        for i in range (0x88,0x88+24):
                calib.append(bus.read_byte_data(i2c_address,i))
        calib.append(bus.read_byte_data(i2c_address,0xA1))
        for i in range (0xE1,0xE1+7):
                calib.append(bus.read_byte_data(i2c_address,i))

        digT.append((calib[1] << 8) | calib[0])
        digT.append((calib[3] << 8) | calib[2])
        digT.append((calib[5] << 8) | calib[4])
        digP.append((calib[7] << 8) | calib[6])
        digP.append((calib[9] << 8) | calib[8])
        digP.append((calib[11]<< 8) | calib[10])
        digP.append((calib[13]<< 8) | calib[12])
        digP.append((calib[15]<< 8) | calib[14])
        digP.append((calib[17]<< 8) | calib[16])
        digP.append((calib[19]<< 8) | calib[18])
        digP.append((calib[21]<< 8) | calib[20])
        digP.append((calib[23]<< 8) | calib[22])
        digH.append( calib[24] )
        digH.append((calib[26]<< 8) | calib[25])
        digH.append( calib[27] )
        digH.append((calib[28]<< 4) | (0x0F & calib[29]))
        digH.append((calib[30]<< 4) | ((calib[29] >> 4) & 0x0F))
        digH.append( calib[31] )

        for i in range(1,2):
                if digT[i] & 0x8000:
                        digT[i] = (-digT[i] ^ 0xFFFF) + 1

        for i in range(1,8):
                if digP[i] & 0x8000:
                        digP[i] = (-digP[i] ^ 0xFFFF) + 1

        for i in range(0,6):
                if digH[i] & 0x8000:
                        digH[i] = (-digH[i] ^ 0xFFFF) + 1

def readData():
        data = []
        for i in range (0xF7, 0xF7+8):
                data.append(bus.read_byte_data(i2c_address,i))
        pres_raw = (data[0] << 12) | (data[1] << 4) | (data[2] >> 4)
        temp_raw = (data[3] << 12) | (data[4] << 4) | (data[5] >> 4)
        hum_raw  = (data[6] << 8)  |  data[7]

        temp = compensate_T(temp_raw)
        pres = compensate_P(pres_raw)
        humi = compensate_H(hum_raw)
        print (round(temp,2))
        print (round(pres,2))
        print (round(humi,2))
        json_body = [
                {
                        'measurement': measurement,
                        'tags': tags,
                        'fields': {'temp': round(temp,2) , 'humi': round(humi,2) , 'hpa': round(pres,2)}
                }
        ]
        client.write_points(json_body)
        print(json_body)


def compensate_P(adc_P):
        global  t_fine
        pressure = 0.0

        v1 = (t_fine / 2.0) - 64000.0
        v2 = (((v1 / 4.0) * (v1 / 4.0)) / 2048) * digP[5]
        v2 = v2 + ((v1 * digP[4]) * 2.0)
        v2 = (v2 / 4.0) + (digP[3] * 65536.0)
        v1 = (((digP[2] * (((v1 / 4.0) * (v1 / 4.0)) / 8192)) / 8)  + ((digP[1] * v1) / 2.0)) / 262144
        v1 = ((32768 + v1) * digP[0]) / 32768

        if v1 == 0:
                return 0
        pressure = ((1048576 - adc_P) - (v2 / 4096)) * 3125
        if pressure < 0x80000000:
                pressure = (pressure * 2.0) / v1
        else:
                pressure = (pressure / v1) * 2
        v1 = (digP[8] * (((pressure / 8.0) * (pressure / 8.0)) / 8192.0)) / 4096
        v2 = ((pressure / 4.0) * digP[7]) / 8192.0
        pressure = pressure + ((v1 + v2 + digP[6]) / 16.0)

        return (pressure/100)
        #print "pressure : %7.2f hPa" % (pressure/100)

def compensate_T(adc_T):
        global t_fine
        v1 = (adc_T / 16384.0 - digT[0] / 1024.0) * digT[1]
        v2 = (adc_T / 131072.0 - digT[0] / 8192.0) * (adc_T / 131072.0 - digT[0] / 8192.0) * digT[2]
        t_fine = v1 + v2
        temperature = t_fine / 5120.0

        return temperature
        #print "temp : %-6.2f ℃" % (temperature)

def compensate_H(adc_H):
        global t_fine
        var_h = t_fine - 76800.0
        if var_h != 0:
                var_h = (adc_H - (digH[3] * 64.0 + digH[4]/16384.0 * var_h)) * (digH[1] / 65536.0 * (1.0 + digH[5] / 67108864.0 * var_h * (1.0 + digH[2] / 67108864.0 * var_h)))
        else:
                return 0
        var_h = var_h * (1.0 - digH[0] * var_h / 524288.0)
        if var_h > 100.0:
                var_h = 100.0
        elif var_h < 0.0:
                var_h = 0.0

        return var_h
        #print "hum : %6.2f %" % (var_h)

def setup():
        osrs_t = 1                      #Temperature oversampling x 1
        osrs_p = 1                      #Pressure oversampling x 1
        osrs_h = 1                      #Humidity oversampling x 1
        mode   = 3                      #Normal mode
        t_sb   = 5                      #Tstandby 1000ms
        filter = 0                      #Filter off
        spi3w_en = 0                    #3-wire SPI Disable

        ctrl_meas_reg = (osrs_t << 5) | (osrs_p << 2) | mode
        config_reg    = (t_sb << 5) | (filter << 2) | spi3w_en
        ctrl_hum_reg  = osrs_h

        writeReg(0xF2,ctrl_hum_reg)
        writeReg(0xF4,ctrl_meas_reg)
        writeReg(0xF5,config_reg)

setup()
get_calib_param()

if __name__ == '__main__':
        try:
                readData()
        except KeyboardInterrupt:
                pass

Golang版

参考URL Armoris日記 ラズパイと BME280 で温度・湿度・気圧を測って グラフ化して表示する

Raspberry Pi4B 32biOSの場合

$ uname -a
Linux ps2 5.10.63-v7l+ #1457 SMP Tue Sep 28 11:26:14 BST 2021 armv7l GNU/Linux

コンパイル時に次を設定

$ GOOS=linux && GOARCH=arm && GOARM=6

const recordIntervalSec = 180で、データを投げる周期を指定します。(自分の環境では $HOME/influx/配下に配置)

package main

import (
    "context"
    "fmt"
    "time"

    influxdb2 "github.com/influxdata/influxdb-client-go/v2"
    "github.com/influxdata/influxdb-client-go/v2/api"
    "github.com/quhar/bme280"
    "golang.org/x/exp/io/i2c"
)

func initBme280() (*bme280.BME280, error) {
    d, err := i2c.Open(&i2c.Devfs{Dev: "/dev/i2c-1"}, 0x76) // 0x76は今回使用す るBME280のI2Cアドレス
    if err != nil {
        return nil, err
    }

    b := bme280.New(d)
    err = b.Init()
    return b, err
}

func recordSensorValues(b *bme280.BME280, w api.WriteAPIBlocking, measurement string) (err error) {
    t, p, h, err := b.EnvData()
    if err != nil {
        return
    }
    point := influxdb2.NewPoint(
        measurement,
        map[string]string{},
        map[string]interface{}{
            "temperature": t,
            "humidity":    h,
            "pressure":    p,
        },
        time.Now(),
    )
    err = w.WritePoint(context.Background(), point)
    if err != nil {
        return
    }
    fmt.Printf("Temp: %.2fC, Hum: %.2f%%, Press: %.2fhpa\n", t, h, p)
    return
}

func main() {
    const influxURL = "http://xxx.xxx.xxx.xxx:8086"      // InfluxDB APIのURL
    const userName = "*****"                      // influxDBのUser名
    const password = "*****"                       // influxDBのUserのPassword
    const db = "iot01"                             // influxDBのDatabase
    const measurement = "sensors"                  // influxDBのMeasurement(存在しない場合は実行時に生成される)
    const recordIntervalSec = 180                  // 値を書き込む間隔(秒)

    b, err := initBme280()
    if err != nil {
        panic(err)
    }
    c := influxdb2.NewClient(influxURL, fmt.Sprintf("%s:%s", userName, password))
    w := c.WriteAPIBlocking("", db+"/autogen")

    ticker := time.NewTicker(recordIntervalSec * time.Second)
    defer ticker.Stop()
    for {
        select {
        case <-ticker.C:
            err = recordSensorValues(b, w, measurement)
            if err != nil {
                panic(err)
            }
        }
    }
}

RockPi4で64bit OSの場合

$ uname -a
Linux rock 4.4.154-110-rockchip-gcef30e88a9f5 #1 SMP Mon Jun 22 07:37:10 UTC 2020 aarch64 aarch64 aarch64 GNU/Linux

aptでインストールしたgolangのバージョンが古いので、新しいバージョンを取得

$ GOOS=linux && GOARCH=arm64 && GOARM=6 でコンパイルはできるが、実行時にエラーとなる。(chip IDが違うよ! というエラー)

mars@rock:~/influx$ ~/go/bin/go build iot-sensor-logger.go
go: downloading github.com/influxdata/influxdb-client-go/v2 v2.5.1
go: downloading golang.org/x/net v0.0.0-20210119194325-5f4716e94777
go: downloading github.com/deepmap/oapi-codegen v1.8.2
go: downloading github.com/pkg/errors v0.9.1
go: downloading gopkg.in/yaml.v2 v2.3.0
go: downloading github.com/influxdata/line-protocol v0.0.0-20200327222509-2487e7298839

$ ./iot-sensor-logger
panic: chip ID is different than expected, want(60), got(58)

goroutine 1 [running]:
main.main()
        /home/mars/influx/iot-sensor-logger.go:58 +0x1bc

自分の環境では、実行時にエラーとなってデータを取得できない。 GOARM=7も試してみたがNG。コンパイルで生成されたコードの情報は、問題なさそうなので、参照しているライブラリーに問題があるのか???

$ file iot-sensor-logger
iot-sensor-logger: ELF 64-bit LSB executable, ARM aarch64, version 1 (SYSV), dynamically linked, interpreter /lib/ld-linux-aarch64.so.1, not stripped

ちなみに、【Golang】がサポートしている GOOS と GOARCH の一覧

$ go tool dist list
aix/ppc64
android/386
android/amd64
android/arm
android/arm64
darwin/amd64
darwin/arm64
dragonfly/amd64
freebsd/386
freebsd/amd64
freebsd/arm
freebsd/arm64
illumos/amd64
ios/amd64
ios/arm64
js/wasm
linux/386
linux/amd64
linux/arm
linux/arm64
linux/mips
linux/mips64
linux/mips64le
linux/mipsle
linux/ppc64
linux/ppc64le
linux/riscv64
linux/s390x
netbsd/386
netbsd/amd64
netbsd/arm
netbsd/arm64
openbsd/386
openbsd/amd64
openbsd/arm
openbsd/arm64
openbsd/mips64
plan9/386
plan9/amd64
plan9/arm
solaris/amd64
windows/386
windows/amd64
windows/arm
windows/arm64

10月の星雲

おうし座/超新星残骸、かに星雲

現代では、M1は西暦1054年に出現した超新星の残骸であることがわかっています。爆発した星の中心核は中性子星(16等)として残っていて、約1/30秒周期で電波やX線を出すパルサーとして有名です。

いっかくじゅう座のバラ星雲
オリオン座の隣には、 いっかくじゅう座という星座が輝いていますが、 暗い星ばかりで構成されているため、知名度は低く、存在を知らない方も多い星座です。 しかし、そのいっかくじゅう座の中には、薔薇とそっくりな形をした「ばら星雲」が輝いていて、こちらの天体の方が有名になっています。 ばら星雲は天体写真ファンの人気の被写体で、写真に撮ると赤っぽい色合いに写り、本当のばらの花が咲いたような姿を楽しめます。

ーーーー

8秒露光、104枚スタック

右下へ偏った構図になってしまったので、次のチャンスには中心になるように撮影したい。

とも座の散開星団 M46

星団の中心から10′ほど北にある小さな惑星状星雲NGC 2438が写っている

BME280センサーのexporter

https://github.com/ashtreefarms/bme280-exporter

CPUがrock Pi4の場合、I2Cバス番号が7なので、一部修正が必要

$ /home/mars/.pyenv/versions/3.8.10/bin/bme280_exporter -a 0x76
2021-09-30 14:07:43,226 - initializing BME280 at 0x76 filter: 0 oversampling(h: 4, p: 4, t: 4)
2021-09-30 14:07:43,259 - initializing exporter with labels None
2021-09-30 14:07:43,260 - starting exporter on port 9500
2021-09-30 14:07:43,267 - starting sampling with 2.0s interval
2021-09-30 14:07:43,295 - temp: 30.31 C   humidity: 0.00%   pressure: 998.05 hPa
2021-09-30 14:07:45,302 - temp: 30.33 C   humidity: 0.00%   pressure: 998.02 hPa
2021-09-30 14:07:47,310 - temp: 30.34 C   humidity: 0.00%   pressure: 998.01 hPa

修正箇所 Adafruit_GPIO/I2C.py

def get_default_bus():
    """Return the default bus number based on the device platform.  For a
    Raspberry Pi either bus 0 or 1 (based on the Pi revision) will be returned.
    For a Beaglebone Black the first user accessible bus, 1, will be returned.
    """
    return 7

Usage

$ bme280_exporter -h
usage: bme280_exporter [-h] [-v] [-p PORT] [-a ADDRESS] [-l LABELS]
                       [-i INTERVAL] [-f FILTER] [-ho HO] [-po PO] [-to TO]

optional arguments:
  -h, --help            show this help message and exit
  -v, --verbose         increase output verbosity
  -p PORT, --port PORT  exporter port (default: 9500
  -a ADDRESS, --address ADDRESS
                        BME280 I2C address (default: 0x77)
  -l LABELS, --labels LABELS
                        JSON object of Prometheus labels to apply
  -i INTERVAL, --interval INTERVAL
                        measurement sample interval (default: 2)
  -f FILTER, --filter FILTER
                        filter value to apply (0-4, default: 0)
  -ho HO                humidity oversampling value (1-5, default: 4)
  -po PO                pressure oversampling value (1-5, default: 4)
  -to TO                temperature oversampling value (1-5, default: 4)