This week I’ve been attempting to interface the front end website to the image manipulation library Image Plot. Aside from the difficulties of making an API interface for ImagePlot, one very large setback, the hardware requirements for running ImagePlot are outside of my web-hosting plan’s limits. I may still implement it as a proof of concept using my personal computer as the workhorse instead of my web-host.
The filtering I added last week seems to be keeping the nonsense InstaGrams down to a minimum. I may still need to enable some kind of crowd-sourced verification of images, but I think this is good enough for now.
I also made progress in adding the ability to filter images based on location. I still have a lot to do to make this easy to use on the website, but the mathematics involved is working.
This week I set out to understand Instagram’s api and how it will work within my application.
I started working with the Instagram API Console. The console and documentation revealed that the API returns a JSON object that I could work with.
JSON is a way of transmitting information that can be interpreted by other programs. It’s similar to XML but has much fewer tags and white-spacing which makes it ideal for web applications.
I created a simple web-application to demonstrate the API. It works by making a request to the API, searching for the tag “Tree” and only displaying results that have a geographical location.
What are the most photogenic locations in the United States? My next project intends to find out by scrapping Instagram for data.
The first steps are to get familiar with Instagram’s api and Amazon’s mechanical turk to analyze as many Instagram photos with the hash tag #spring, as possible.
From there the data will be sorted into regions to determine what areas of the United States get the most photos of the environment.