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我尝试将图像发送到另一个模块，但我收到连接被拒绝。图像通过 Post 请求从 CameraCapture 发送到 Classify 模块。分类器以拒绝连接响应我。DockerFile 中暴露了 80 端口

来自“iotedge logs CameraCapture”的代码错误：

HTTPConnectionPool(host='classifier', port=80): Max retries exceeded with url: /image (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0xf6b447f0>: Failed to establish a new connection: [Errno 111] Connection refused'))

来自 CameraCapture 的 python 脚本：

import time
import sys
import os
import requests
import json
from azure.iot.device import IoTHubModuleClient, Message

# global counters
SENT_IMAGES = 0

# global client
CLIENT = None

# Send a message to IoT Hub
# Route output1 to $upstream in deployment.template.json
def send_to_hub(strMessage):
    message = Message(bytearray(strMessage, 'utf8'))
    CLIENT.send_message_to_output(message, "output1")
    global SENT_IMAGES
    SENT_IMAGES += 1
    print( "Total images sent: {}".format(SENT_IMAGES) )

# Send an image to the image classifying server
# Return the JSON response from the server with the prediction result
def sendFrameForProcessing(imagePath, imageProcessingEndpoint):
    headers = {'Content-Type': 'application/octet-stream'}

    with open(imagePath, mode="rb") as test_image:
        try:
            response = requests.post(imageProcessingEndpoint, headers = headers, data = test_image)
            print("Response from classification service: (" + str(response.status_code) + ") " + json.dumps(response.json()) + "\n")
        except Exception as e:
            print(e)
            print("No response from classification service")
            print("------------------------------------------------------------------------")
            return None

    return json.dumps(response.json())

def main(imagePath, imageProcessingEndpoint):
    try:
        print ( "Simulated camera module for Azure IoT Edge. Press Ctrl-C to exit." )

        try:
            global CLIENT
            CLIENT = IoTHubModuleClient.create_from_edge_environment()
        except Exception as iothub_error:
            print ( "Unexpected error {} from IoTHub".format(iothub_error) )
            return

        print ( "The sample is now sending images for processing and will indefinitely.")

        while True:
            classification = sendFrameForProcessing(imagePath, imageProcessingEndpoint)
            if classification:
                send_to_hub(classification)
            time.sleep(100)

    except KeyboardInterrupt:
        print ( "IoT Edge module sample stopped" )

if __name__ == '__main__':
    try:
        # Retrieve the image location and image classifying server endpoint from container environment
        IMAGE_PATH = os.getenv('IMAGE_PATH', "")
        IMAGE_PROCESSING_ENDPOINT = os.getenv('IMAGE_PROCESSING_ENDPOINT', "http://classifier/image")
    except ValueError as error:
        print ( error )
        sys.exit(1)

    if ((IMAGE_PATH and IMAGE_PROCESSING_ENDPOINT) != ""):
        main(IMAGE_PATH, IMAGE_PROCESSING_ENDPOINT)
    else: 
        print ( "Error: Image path or image-processing endpoint missing" )

和自定义愿景的代码：

import json
import os
import io

# Imports for the REST API
from flask import Flask, request, jsonify

# Imports for image procesing
from PIL import Image

# Imports for prediction
from predict import initialize, predict_image, predict_url

app = Flask(__name__)

# 4MB Max image size limit
app.config['MAX_CONTENT_LENGTH'] = 4 * 1024 * 1024 

# Default route just shows simple text
@app.route('/')
def index():
    return 'CustomVision.ai model host harness'

# Like the CustomVision.ai Prediction service /image route handles either
#     - octet-stream image file 
#     - a multipart/form-data with files in the imageData parameter
@app.route('/image', methods=['POST'])
@app.route('/<project>/image', methods=['POST'])
@app.route('/<project>/image/nostore', methods=['POST'])
@app.route('/<project>/classify/iterations/<publishedName>/image', methods=['POST'])
@app.route('/<project>/classify/iterations/<publishedName>/image/nostore', methods=['POST'])
@app.route('/<project>/detect/iterations/<publishedName>/image', methods=['POST'])
@app.route('/<project>/detect/iterations/<publishedName>/image/nostore', methods=['POST'])
def predict_image_handler(project=None, publishedName=None):
    try:
        imageData = None
        if ('imageData' in request.files):
            imageData = request.files['imageData']
        elif ('imageData' in request.form):
            imageData = request.form['imageData']
        else:
            imageData = io.BytesIO(request.get_data())

        img = Image.open(imageData)
        results = predict_image(img)
        return jsonify(results)
    except Exception as e:
        print("Par ici 1")
        print('EXCEPTION:', str(e))
        return 'Error processing image', 500


# Like the CustomVision.ai Prediction service /url route handles url's
# in the body of hte request of the form:
#     { 'Url': '<http url>'}  
@app.route('/url', methods=['POST'])
@app.route('/<project>/url', methods=['POST'])
@app.route('/<project>/url/nostore', methods=['POST'])
@app.route('/<project>/classify/iterations/<publishedName>/url', methods=['POST'])
@app.route('/<project>/classify/iterations/<publishedName>/url/nostore', methods=['POST'])
@app.route('/<project>/detect/iterations/<publishedName>/url', methods=['POST'])
@app.route('/<project>/detect/iterations/<publishedName>/url/nostore', methods=['POST'])
def predict_url_handler(project=None, publishedName=None):
    try:
        image_url = json.loads(request.get_data().decode('utf-8'))['url']
        results = predict_url(image_url)
        return jsonify(results)
    except Exception as e:
        print('EXCEPTION:', str(e))
        return 'Error processing image'

if __name__ == '__main__':
    # Load and intialize the model
    initialize()

    # Run the server
    app.run(host='0.0.0.0', port=80)
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