cntk-image-recon.md

CNTK Image Recognition

This service uses CNTK Image Recognition to perform image recognition on photos.

It is part of our third party DNN Model Services.

Welcome

The service receives an image and uses it as an input for a pre-trained ResNet152 model.

There are two pre-trained models available, one trained with a flowers dataset from the Oxford Visual Geometry Group, with 102 different categories of flowers common to the UK.

The second model was trained using the Columbia Dogs Dataset, with 133 different dog breeds.

What’s the point?

The service makes prediction using computer vision and machine learning techniques.

The service outputs a top 5 prediction list (ordered by confidence) based on the specified dataset (flowers or dogs).

How does it work?

The user must provide the following inputs in order to start the service and get a response:

Inputs:

• gRPC method: flowers or dogs.
• model: DNN Model ("ResNet152").
• img_path: An image URL.

You can use this service from SingularityNET DApp, clicking on SNET/ImageRecon.

You can also call the service from SingularityNET CLI (snet).

Assuming that you have an open channel to this service:

$ snet client call snet cntk-image-recon default_group flowers '{"model": "ResNet152", "img_path": "https://www.fiftyflowers.com/site_files/FiftyFlowers/Image/Product/Mini-Black-Eye-bloom-350_c7d02e72.jpg"}'
...
Read call params from cmdline...

Calling service...

    response:
        delta_time: '1.5536'
        top_5: '{1: ''98.93%: sunflower'', 2: ''00.64%: black-eyed susan'', 3: ''00.16%:
            barbeton daisy'', 4: ''00.14%: oxeye daisy'', 5: ''00.03%: daffodil''}'

What to expect from this service?

Input image:

Response:

1: '99.66%: rose'
2: '00.11%: mallow'
3: '00.04%: globe-flower'
4: '00.03%: bougainvillea'
5: '00.03%: anthurium'

Input image:

Response:

1: '98.28%: Bulldog'
2: '00.54%: Bullmastiff'
3: '00.41%: American_staffordshire_terrier'
4: '00.16%: Chinese_shar-pei'
5: '00.12%: Dogue_de_bordeaux'