HCIRA Project 1

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//**HOW TO USE**//
To run, open the executable located in the dist folder.
Once the canvas is open you can go ahead and draw and the $1 algorithms guess will pop up following your single-stroke drawing.
Following your drawing clear the canvas using the TAB key and then you are free to draw again.

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//**COMPONENTS**//
1. Resampling:
Resample(points, n) function begins on line 131 and ends on line 150 and utilizes the point class which holds an x and y value in each point object and is defined on 10-20.
This function also utilizes the pathLength(points) function that is defined on lines 125-129

2. Rotation:
This component utilizes 3 functions: centroid(points), rotateBy(points, theta), and rotateToZero(points).
These functions are defined from lines 154-175, and also utilize the point class.

3. Scaling+Translation:
This component utilizes 3 functions: boundingBox(points), scaleToSquare(points,size), and translateToOrigin(points)
These functions are defined from lines 178-208, and also utilize the point class.

4. Matching Process:
This component utilizes 4 functions: pathDistance(pointsA, pointsB), distanceAtBestAngle(points, T, thetaA, thetaB, threshold), recognize(points, templates), and distanceAtAngle(points, T, theta)
These functions are defined from lines 212-255, and also utilize the point class as well as the constant PHI which is defined on line 117.

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//**HOW TO USE**//
To run, open the executable located in the dist folder.
This will take some time to process, but will slowly fill up the logfile with data, and once it reaches the end of the logfile it will showcase the total average accuracy for each user and for all users inside of the csv file.

//**COMPONENTS**//
1. Read in Dataset:
Function readXML(rootDir) on line 53 serves to read in all the data from the folder labeled xml. This iterative process goes through each file in a top down approach and creates Shape() objects from the provided points. Later after resampling, the data is separated on lines 349-374 by user, speed, gesture, and trial (NOTE: this part of the code is currently bugged, the users[] array presents differently in the loop where data is added vs outside of the loop)

2. Connect to Recognizer:
Lines 330-340 serve to resample the input data. The data is then run through the recognizer on line 485 during the loop over the dataset.

3. Loop over Dataset:
Lines 385-420 serve to recreate the random-100 loop that was covered in class.

4. Output the Result:
Currently, the result of the looped tests are printed to the console on lines 413-417. CSV exporting functionality is being implemented following line 420.