Updates code structure and README

Readme.md

+# WASP AS 1 Assigment: Activity Recognition,
+# by Frida Heskebeck, Matthias Mayr, Momina Rizwan and Pontus Andersson
+
+Our activity recognition is based on thresholds.
+The approach is to use the mean of the x,y and z accelerometer data.
+Over a time interval of two seconds, we look at the difference of the max and min values of the mean.
+If the differences is lower than a set threshold, the person is predicted to be standing still.
+If the difference is greater than the still treshold but smaller than a set running threshold, the person is predicted to be walking.
+Otherwise, the person is predicted to be running.
+
+This repository contains three scripts used to perform activity recognition and data visualization.
+The data is stored in the `data` directory. To include your own data, add a subfolder to `data` named Data_YourData.
+We assume the scripts are called from the as1-activity-recognition folder.
+
+* `data_visualization.py` allows you to visualize data. Usage: `python data_visualization.py Name DataType`,
+where `Name` is the name of the person whose data you wish to show, and `DataType` is either `ACC` or `GYR` for accelerometer and
+gyro data, respectively. Red bars are used to separate the data files.
+
+* `get_data.py` is a helper function for `activity_recognition.py`. It collects the data used in the latter script.
+
+* `activity_recognition.py` allows you to do activity recognition. Usage: `python activity_recognition.py Name PresentationMode`,
+where `Name` is as in `data_visualization.py` and `PresentationMode` is either `Text` or `ConfusionMatrix`, with
+`Text` yielding console output of each prediction and corresponding ground truth, and `ConfusionMatrix` yielding a confusion matrix.
+For both options, we print the accuracy in the console.
\ No newline at end of file