General approach to developing an image classification algorithm for Dilbert cartoons

Question

As a self-development exercise, I want to develop a simple classification algorithm that, given a particular cell of a Dilbert cartoon, is able to identify which characters are

Answer 1

You can try building a model by uploading your training data (images of comics) to demo.nanonets.ai (free to use)

Then query the API using the following (Python Code):

import requests
import json
import urllib
model_name = "Enter-Your-Model-Name-Here"
url = "http://static5.businessinsider.com/image/525464f969bedd0b0422cfb6/dilbert-creator-scott-adams-presents-his-10-favorite-comics-of-all-time.jpg"
files = {'uploadfile': urllib.urlopen(url).read()}
url = "http://demo.nanonets.ai/classify/?appId="+model_name
r = requests.post(url, files=files)
print json.loads(r.content)

the response looks like:

{
  "message": "Model trained",
  "result": [
    {
      "label": "Dilbert",
      "probability": 0.97
    },
    {
      "label": "PHB",
      "probability": 0.025
    },
    {
      "label": "Ratbert",
      "probability": 0.005
    }
  ]
}