Progress Report Due: 1/10/16

Progress:

Tasks Accomplished:

-We have successfully implemented a code into our app that converts what the camera sees from BGR to HSV vision, aside from a few minor errors that can be solved within the coming week. Essentially, we changed the default "BGR to Grayscale" of Mr. Lin's code, so that the camera would take footage and alter it from "BGR to HSV."

Questions Answered:

-How we will have our app single out certain objects. Converting from BGR to HSV allows for the app's camera to track objects by extracting whichever colors we implement in our code.

Lessons Learned:

-We won't be able to find an exact code for each capability we want our app to have, but rather we can take bits and pieces and learn from them to create what we need to accomplish.

Problem:

Difficulties Encountered:

-Part of an online code that worked well with our app (http://docs.opencv.org/master/df/d9d/tutorial_py_colorspaces.html#gsc.tab=0) was not compatible with our app. This caused us to have to go in and alter the code to meet our needs (which we had expected and expect to do in the future).

Equipments Required: 

-Mac Laptops

-Mr. Lin's iPad & Chord

Show Stopper/Open Issues/New Risks: 

- The code we have been working off of is configured to identify red objects. We have to look more into ranges of color features (such as hue/saturation/etc.) which is where HSV plays in.

• Plan:

Proposals/Steps to Attack the Problems/Action Items for the Coming Week: 

- Fix any minor malfunctions that occurred while switching the app from "BGR to Grayscale" to "BGR to HSV".

- Alter the app so that it will detect the color of our choice so we can begin testing it out on subway signs.

Experiments to Conduct, Ideas to Try, Vendors to Contact, Updated Schedule, etc.

-Continue to make sure our app works off of Mr. Lin's iPad as we add new code.

-Detect different colored objects as we alter our code to make sure the camera is tracking the correct objects.