Posting Images With Apache NiFi 1.7 and a Custom Processor

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Posting Images With Apache NiFi 1.7 and a Custom Processor

In this article, we go over how to post images to an Apache MXNet model server in order to work with deep learning classification.

· Big Data Zone ·
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Posting Images With Apache NiFi 1.7 and a Custom Processor

I have been using a shell script for this since Apache NiFi did not have a good way to natively post an image to HTTP servers, such as the model server for Apache MXNet.

So I wrote a quick and dirty processor that posts an image there and gathers the headers, result body, status text, and status code and returns them to you as attributes.

In this example, I am downloading images from the picsum.photos free photo service.

To use this new processor, download it to your lib directory and restart Apache NiFi, then you can add the PostImageProcessor.

Eclipse for Building My Processor

Configure the Post Image Processor With Your URL, fieldname, imagename, and imagetype.

MXNet Model Server Results

The Attribute Results From the Data


Example Results

{Server=[Werkzeug/0.14.1 Python/3.6.6], Access-Control-Allow-Origin=[*], 
 Content-Length=[396], Date=[Fri, 05 Oct 2018 17:47:22 GMT], 
                 "class":"n02281406 sulphur butterfly, sulfur butterfly"},
                {"probability":0.19173663854599,"class":"n02190166 fly"},
                 "class":"n02280649 cabbage butterfly"},
                 "class":"n03485794 handkerchief, hankie, hanky, hankey"},
                {"probability":0.048753462731838226,"class":"n02834397 bib"}]]}    post.status    OK    post.statuscode    200   

Results from HTTP Posting an Image to MXNet Model Server

      [INFO 2018-10-05 13:47:22,217 PID:88561 /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/mms/serving_frontend.py:predict_callback:467] Request input: data should be image with jpeg format.    [INFO 2018-10-05 13:47:22,218 PID:88561 /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/mms/request_handler/flask_handler.py:get_file_data:137] Getting file data from request.    [INFO 2018-10-05 13:47:22,262 PID:88561 /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/mms/serving_frontend.py:predict_callback:510] Response is text.    [INFO 2018-10-05 13:47:22,262 PID:88561 /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/mms/request_handler/flask_handler.py:jsonify:159] Jsonifying the response: {'prediction': [[{'probability': 0.24173378944396973, 'class': 'n02281406 sulphur butterfly, sulfur butterfly'}, {'probability': 0.19173663854599, 'class': 'n02190166 fly'}, {'probability': 0.052654966711997986, 'class': 'n02280649 cabbage butterfly'}, {'probability': 0.05147545784711838, 'class': 'n03485794 handkerchief, hankie, hanky, hankey'}, {'probability': 0.048753462731838226, 'class': 'n02834397 bib'}]]}    [INFO 2018-10-05 13:47:22,263 PID:88561 /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/werkzeug/_internal.py:_log:88] - - [05/Oct/2018 13:47:22] "POST /squeezenet/predict HTTP/1.1" 200 -  

Example HTTP Server


Source Code For Processor


Pre-Built NAR To Install


apache nifi, big data, http, post, tutorial

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